real-time-object-tracking-using-kalman-filters.ipynb

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    "# create a YOLOv3 Keras model and save it to file\n",
    "# based on https://github.com/experiencor/keras-yolo3\n",
    "import struct\n",
    "import numpy as np\n",
    "import colorsys\n",
    "from keras.layers import Conv2D\n",
    "from keras.layers import Input\n",
    "from keras.layers import BatchNormalization\n",
    "from keras.layers import LeakyReLU\n",
    "from keras.layers import ZeroPadding2D\n",
    "from keras.layers import UpSampling2D\n",
    "from keras.layers import add, concatenate\n",
    "from keras.models import Model\n",
    " \n",
    "def _conv_block(inp, convs, skip=True):\n",
    "    x = inp\n",
    "    count = 0\n",
    "    for conv in convs:\n",
    "        if count == (len(convs) - 2) and skip:\n",
    "            skip_connection = x\n",
    "        count += 1\n",
    "        if conv['stride'] > 1: x = ZeroPadding2D(((1,0),(1,0)))(x) # peculiar padding as darknet prefer left and top\n",
    "        x = Conv2D(conv['filter'],\n",
    "                   conv['kernel'],\n",
    "                   strides=conv['stride'],\n",
    "                   padding='valid' if conv['stride'] > 1 else 'same', # peculiar padding as darknet prefer left and top\n",
    "                   name='conv_' + str(conv['layer_idx']),\n",
    "                   use_bias=False if conv['bnorm'] else True)(x)\n",
    "        if conv['bnorm']: x = BatchNormalization(epsilon=0.001, name='bnorm_' + str(conv['layer_idx']))(x)\n",
    "        if conv['leaky']: x = LeakyReLU(alpha=0.1, name='leaky_' + str(conv['layer_idx']))(x)\n",
    "    return add([skip_connection, x]) if skip else x\n",
    "\n",
    "def make_yolov3_model():\n",
    "    input_image = Input(shape=(None, None, 3))\n",
    "    # Layer  0 => 4\n",
    "    x = _conv_block(input_image, [{'filter': 32, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 0},\n",
    "                                  {'filter': 64, 'kernel': 3, 'stride': 2, 'bnorm': True, 'leaky': True, 'layer_idx': 1},\n",
    "                                  {'filter': 32, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 2},\n",
    "                                  {'filter': 64, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 3}])\n",
    "    # Layer  5 => 8\n",
    "    x = _conv_block(x, [{'filter': 128, 'kernel': 3, 'stride': 2, 'bnorm': True, 'leaky': True, 'layer_idx': 5},\n",
    "                        {'filter':  64, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 6},\n",
    "                        {'filter': 128, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 7}])\n",
    "    # Layer  9 => 11\n",
    "    x = _conv_block(x, [{'filter':  64, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 9},\n",
    "                        {'filter': 128, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 10}])\n",
    "    # Layer 12 => 15\n",
    "    x = _conv_block(x, [{'filter': 256, 'kernel': 3, 'stride': 2, 'bnorm': True, 'leaky': True, 'layer_idx': 12},\n",
    "                        {'filter': 128, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 13},\n",
    "                        {'filter': 256, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 14}])\n",
    "    # Layer 16 => 36\n",
    "    for i in range(7):\n",
    "        x = _conv_block(x, [{'filter': 128, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 16+i*3},\n",
    "                            {'filter': 256, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 17+i*3}])\n",
    "    skip_36 = x\n",
    "    # Layer 37 => 40\n",
    "    x = _conv_block(x, [{'filter': 512, 'kernel': 3, 'stride': 2, 'bnorm': True, 'leaky': True, 'layer_idx': 37},\n",
    "                        {'filter': 256, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 38},\n",
    "                        {'filter': 512, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 39}])\n",
    "    # Layer 41 => 61\n",
    "    for i in range(7):\n",
    "        x = _conv_block(x, [{'filter': 256, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 41+i*3},\n",
    "                            {'filter': 512, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 42+i*3}])\n",
    "    skip_61 = x\n",
    "    # Layer 62 => 65\n",
    "    x = _conv_block(x, [{'filter': 1024, 'kernel': 3, 'stride': 2, 'bnorm': True, 'leaky': True, 'layer_idx': 62},\n",
    "                        {'filter':  512, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 63},\n",
    "                        {'filter': 1024, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 64}])\n",
    "    # Layer 66 => 74\n",
    "    for i in range(3):\n",
    "        x = _conv_block(x, [{'filter':  512, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 66+i*3},\n",
    "                            {'filter': 1024, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 67+i*3}])\n",
    "    # Layer 75 => 79\n",
    "    x = _conv_block(x, [{'filter':  512, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 75},\n",
    "                        {'filter': 1024, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 76},\n",
    "                        {'filter':  512, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 77},\n",
    "                        {'filter': 1024, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 78},\n",
    "                        {'filter':  512, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 79}], skip=False)\n",
    "    # Layer 80 => 82\n",
    "    yolo_82 = _conv_block(x, [{'filter': 1024, 'kernel': 3, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 80},\n",
    "                              {'filter':  255, 'kernel': 1, 'stride': 1, 'bnorm': False, 'leaky': False, 'layer_idx': 81}], skip=False)\n",
    "    # Layer 83 => 86\n",
    "    x = _conv_block(x, [{'filter': 256, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 84}], skip=False)\n",
    "    x = UpSampling2D(2)(x)\n",
    "    x = concatenate([x, skip_61])\n",
    "    # Layer 87 => 91\n",
    "    x = _conv_block(x, [{'filter': 256, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 87},\n",
    "                        {'filter': 512, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 88},\n",
    "                        {'filter': 256, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 89},\n",
    "                        {'filter': 512, 'kernel': 3, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 90},\n",
    "                        {'filter': 256, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True, 'layer_idx': 91}], skip=False)\n",
    "    # Layer 92 => 94\n",
    "    yolo_94 = _conv_block(x, [{'filter': 512, 'kernel': 3, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 92},\n",
    "                              {'filter': 255, 'kernel': 1, 'stride': 1, 'bnorm': False, 'leaky': False, 'layer_idx': 93}], skip=False)\n",
    "    # Layer 95 => 98\n",
    "    x = _conv_block(x, [{'filter': 128, 'kernel': 1, 'stride': 1, 'bnorm': True, 'leaky': True,   'layer_idx': 96}], skip=False)\n",
    "    x = UpSampling2D(2)(x)\n",
    "    x = concatenate([x, skip_36])\n",
    "    # Layer 99 => 106\n",
    "    yolo_106 = _conv_block(x, [{'filter': 128, 'kernel': 1, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 99},\n",
    "                               {'filter': 256, 'kernel': 3, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 100},\n",
    "                               {'filter': 128, 'kernel': 1, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 101},\n",
    "                               {'filter': 256, 'kernel': 3, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 102},\n",
    "                               {'filter': 128, 'kernel': 1, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 103},\n",
    "                               {'filter': 256, 'kernel': 3, 'stride': 1, 'bnorm': True,  'leaky': True,  'layer_idx': 104},\n",
    "                               {'filter': 255, 'kernel': 1, 'stride': 1, 'bnorm': False, 'leaky': False, 'layer_idx': 105}], skip=False)\n",
    "    model = Model(input_image, [yolo_82, yolo_94, yolo_106])\n",
    "    return model\n",
    "\n",
    "class WeightReader:\n",
    "    def __init__(self, weight_file):\n",
    "        with open(weight_file, 'rb') as w_f:\n",
    "            major,\t= struct.unpack('i', w_f.read(4))\n",
    "            minor,\t= struct.unpack('i', w_f.read(4))\n",
    "            revision, = struct.unpack('i', w_f.read(4))\n",
    "            if (major*10 + minor) >= 2 and major < 1000 and minor < 1000:\n",
    "                w_f.read(8)\n",
    "            else:\n",
    "                w_f.read(4)\n",
    "            transpose = (major > 1000) or (minor > 1000)\n",
    "            binary = w_f.read()\n",
    "        self.offset = 0\n",
    "        self.all_weights = np.frombuffer(binary, dtype='float32')\n",
    " \n",
    "    def read_bytes(self, size):\n",
    "        self.offset = self.offset + size\n",
    "        return self.all_weights[self.offset-size:self.offset]\n",
    "\n",
    "    def load_weights(self, model):\n",
    "        for i in range(106):\n",
    "            try:\n",
    "                conv_layer = model.get_layer('conv_' + str(i))\n",
    "                print(\"loading weights of convolution #\" + str(i))\n",
    "                if i not in [81, 93, 105]:\n",
    "                    norm_layer = model.get_layer('bnorm_' + str(i))\n",
    "                    size = np.prod(norm_layer.get_weights()[0].shape)\n",
    "                    beta  = self.read_bytes(size) # bias\n",
    "                    gamma = self.read_bytes(size) # scale\n",
    "                    mean  = self.read_bytes(size) # mean\n",
    "                    var   = self.read_bytes(size) # variance\n",
    "                    weights = norm_layer.set_weights([gamma, beta, mean, var])\n",
    "                if len(conv_layer.get_weights()) > 1:\n",
    "                    bias   = self.read_bytes(np.prod(conv_layer.get_weights()[1].shape))\n",
    "                    kernel = self.read_bytes(np.prod(conv_layer.get_weights()[0].shape))\n",
    "                    kernel = kernel.reshape(list(reversed(conv_layer.get_weights()[0].shape)))\n",
    "                    kernel = kernel.transpose([2,3,1,0])\n",
    "                    conv_layer.set_weights([kernel, bias])\n",
    "                else:\n",
    "                    kernel = self.read_bytes(np.prod(conv_layer.get_weights()[0].shape))\n",
    "                    kernel = kernel.reshape(list(reversed(conv_layer.get_weights()[0].shape)))\n",
    "                    kernel = kernel.transpose([2,3,1,0])\n",
    "                    conv_layer.set_weights([kernel])\n",
    "            except ValueError:\n",
    "                print(\"no convolution #\" + str(i))\n",
    "\n",
    "    def reset(self):\n",
    "        self.offset = 0"
   ]
  },
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   "source": [
    "from matplotlib import pyplot\n",
    "from matplotlib.patches import Rectangle\n",
    "from numpy import expand_dims\n",
    "#from keras.preprocessing.image import load_img, img_to_array\n",
    "from tensorflow.keras.utils import load_img , img_to_array\n",
    "import cv2\n",
    "import random\n",
    "\n",
    "label_map = {\n",
    "    \"person\": \"blue\",\n",
    "    \"bicycle\": \"yellow\", \n",
    "    \"car\": \"red\",\n",
    "    \"truck\": \"green\",\n",
    "    \"motorbike\": \"white\", \n",
    "    \"aeroplane\": \"white\", \n",
    "    \"bus\": \"white\",\n",
    "    \"train\": \"white\", \n",
    "    \"boat\": \"white\"\n",
    "}\n",
    " \n",
    "class BoundBox:\n",
    "    def __init__(self, xmin, ymin, xmax, ymax, objness = None, classes = None):\n",
    "        self.xmin = xmin\n",
    "        self.ymin = ymin\n",
    "        self.xmax = xmax\n",
    "        self.ymax = ymax\n",
    "        self.objness = objness\n",
    "        self.classes = classes\n",
    "        self.label = -1\n",
    "        self.score = -1\n",
    "\n",
    "    def get_label(self):\n",
    "        if self.label == -1:\n",
    "            self.label = np.argmax(self.classes)\n",
    "\n",
    "        return self.label\n",
    "\n",
    "    def get_score(self):\n",
    "        if self.score == -1:\n",
    "            self.score = self.classes[self.get_label()]\n",
    " \n",
    "        return self.score\n",
    " \n",
    "def _sigmoid(x):\n",
    "    return 1. / (1. + np.exp(-x))\n",
    " \n",
    "def decode_netout(netout, anchors, obj_thresh, net_h, net_w):\n",
    "    grid_h, grid_w = netout.shape[:2]\n",
    "    nb_box = 3\n",
    "    netout = netout.reshape((grid_h, grid_w, nb_box, -1))\n",
    "    nb_class = netout.shape[-1] - 5\n",
    "    boxes = []\n",
    "    netout[..., :2]  = _sigmoid(netout[..., :2])\n",
    "    netout[..., 4:]  = _sigmoid(netout[..., 4:])\n",
    "    netout[..., 5:]  = netout[..., 4][..., np.newaxis] * netout[..., 5:]\n",
    "    netout[..., 5:] *= netout[..., 5:] > obj_thresh\n",
    " \n",
    "    for i in range(grid_h*grid_w):\n",
    "        row = i / grid_w\n",
    "        col = i % grid_w\n",
    "        for b in range(nb_box):\n",
    "            # 4th element is objectness score\n",
    "            objectness = netout[int(row)][int(col)][b][4]\n",
    "            if(objectness.all() <= obj_thresh): continue\n",
    "            # first 4 elements are x, y, w, and h\n",
    "            x, y, w, h = netout[int(row)][int(col)][b][:4]\n",
    "            x = (col + x) / grid_w # center position, unit: image width\n",
    "            y = (row + y) / grid_h # center position, unit: image height\n",
    "            w = anchors[2 * b + 0] * np.exp(w) / net_w # unit: image width\n",
    "            h = anchors[2 * b + 1] * np.exp(h) / net_h # unit: image height\n",
    "            # last elements are class probabilities\n",
    "            classes = netout[int(row)][col][b][5:]\n",
    "            box = BoundBox(x-w/2, y-h/2, x+w/2, y+h/2, objectness, classes)\n",
    "            boxes.append(box)\n",
    "    return boxes\n",
    " \n",
    "def correct_yolo_boxes(boxes, image_h, image_w, net_h, net_w):\n",
    "    new_w, new_h = net_w, net_h\n",
    "    for i in range(len(boxes)):\n",
    "        x_offset, x_scale = (net_w - new_w)/2./net_w, float(new_w)/net_w\n",
    "        y_offset, y_scale = (net_h - new_h)/2./net_h, float(new_h)/net_h\n",
    "        boxes[i].xmin = int((boxes[i].xmin - x_offset) / x_scale * image_w)\n",
    "        boxes[i].xmax = int((boxes[i].xmax - x_offset) / x_scale * image_w)\n",
    "        boxes[i].ymin = int((boxes[i].ymin - y_offset) / y_scale * image_h)\n",
    "        boxes[i].ymax = int((boxes[i].ymax - y_offset) / y_scale * image_h)\n",
    "\n",
    "def _interval_overlap(interval_a, interval_b):\n",
    "    x1, x2 = interval_a\n",
    "    x3, x4 = interval_b\n",
    "    if x3 < x1:\n",
    "        if x4 < x1:\n",
    "            return 0\n",
    "        else:\n",
    "            return min(x2,x4) - x1\n",
    "    else:\n",
    "        if x2 < x3:\n",
    "            return 0\n",
    "        else:\n",
    "            return min(x2,x4) - x3\n",
    "\n",
    "def bbox_iou(box1, box2):\n",
    "    intersect_w = _interval_overlap([box1.xmin, box1.xmax], [box2.xmin, box2.xmax])\n",
    "    intersect_h = _interval_overlap([box1.ymin, box1.ymax], [box2.ymin, box2.ymax])\n",
    "    intersect = intersect_w * intersect_h\n",
    "    w1, h1 = box1.xmax-box1.xmin, box1.ymax-box1.ymin\n",
    "    w2, h2 = box2.xmax-box2.xmin, box2.ymax-box2.ymin\n",
    "    union = w1*h1 + w2*h2 - intersect\n",
    "    return float(intersect) / union\n",
    " \n",
    "def do_nms(boxes, nms_thresh):\n",
    "    if len(boxes) > 0:\n",
    "        nb_class = len(boxes[0].classes)\n",
    "    else:\n",
    "        return\n",
    "    for c in range(nb_class):\n",
    "        sorted_indices = np.argsort([-box.classes[c] for box in boxes])\n",
    "        for i in range(len(sorted_indices)):\n",
    "            index_i = sorted_indices[i]\n",
    "            if boxes[index_i].classes[c] == 0: continue\n",
    "            for j in range(i+1, len(sorted_indices)):\n",
    "                index_j = sorted_indices[j]\n",
    "                if bbox_iou(boxes[index_i], boxes[index_j]) >= nms_thresh:\n",
    "                    boxes[index_j].classes[c] = 0\n",
    "\n",
    "# load and prepare an image\n",
    "def load_image_pixels(filename, shape):\n",
    "    # load the image to get its shape\n",
    "    image = load_img(filename)\n",
    "    width, height = image.size\n",
    "    # load the image with the required size\n",
    "    image = load_img(filename, target_size=shape)\n",
    "    # convert to numpy array\n",
    "    image = img_to_array(image)\n",
    "    # scale pixel values to [0, 1]\n",
    "    image = image.astype('float32')\n",
    "    image /= 255.0\n",
    "    # add a dimension so that we have one sample\n",
    "    image = expand_dims(image, 0)\n",
    "    return image, width, height\n",
    "\n",
    "# Preprocess the given image\n",
    "def image_preprocess(image, target_size):\n",
    "    ih, iw    = target_size\n",
    "    h,  w, _  = image.shape\n",
    "\n",
    "    scale = min(iw/w, ih/h)\n",
    "    nw, nh  = int(scale * w), int(scale * h)\n",
    "    image_resized = cv2.resize(image, (nw, nh))\n",
    "\n",
    "    image_paded = np.full(shape=[ih, iw, 3], fill_value=128.0)\n",
    "    dw, dh = (iw - nw) // 2, (ih-nh) // 2\n",
    "    image_paded[dh:nh+dh, dw:nw+dw, :] = image_resized\n",
    "    image_paded = image_paded / 255.\n",
    "\n",
    "    image_expanded = expand_dims(image_paded, 0)\n",
    "\n",
    "    return image_expanded, w, h\n",
    " \n",
    "# get all of the results above a threshold\n",
    "def get_boxes(boxes, labels, thresh):\n",
    "    v_boxes, v_labels, v_scores = list(), list(), list()\n",
    "    # enumerate all boxes\n",
    "    for box in boxes:\n",
    "        # enumerate all possible labels\n",
    "        for i in range(len(labels)):\n",
    "            # check if the threshold for this label is high enough\n",
    "            if box.classes[i] > thresh:\n",
    "                v_boxes.append(box)\n",
    "                v_labels.append(labels[i])\n",
    "                v_scores.append(box.classes[i]*100)\n",
    "                # don't break, many labels may trigger for one box\n",
    "    return v_boxes, v_labels, v_scores\n",
    " \n",
    "# draw all results\n",
    "def draw_boxes(filename, v_boxes, v_labels, v_scores):\n",
    "    # load the image\n",
    "    data = pyplot.imread(filename)\n",
    "    # plot the image\n",
    "    pyplot.imshow(data)\n",
    "    # get the context for drawing boxes\n",
    "    ax = pyplot.gca()\n",
    "    # plot each box\n",
    "    for i in range(len(v_boxes)):\n",
    "        box = v_boxes[i]\n",
    "        # get coordinates\n",
    "        y1, x1, y2, x2 = box.ymin, box.xmin, box.ymax, box.xmax\n",
    "        # calculate width and height of the box\n",
    "        width, height = x2 - x1, y2 - y1\n",
    "        # create the shape\n",
    "        rect = Rectangle((x1, y1), width, height, fill=False, color=label_map[v_labels[i]])\n",
    "        # draw the box\n",
    "        ax.add_patch(rect)\n",
    "        # draw text and score in top left corner\n",
    "        label = \"%s (%.3f)\" % (v_labels[i], v_scores[i])\n",
    "        pyplot.text(x1, y1, label, color=label_map[v_labels[i]])\n",
    "    # show the plot\n",
    "    pyplot.show()\n",
    "    \n",
    "def draw_bbox(image, bboxes, CLASSES, show_label=True, show_confidence = True, Text_colors=(255,255,0), rectangle_colors='', tracking=False):   \n",
    "    NUM_CLASS = CLASSES\n",
    "    num_classes = len(NUM_CLASS)\n",
    "    image_h, image_w, _ = image.shape\n",
    "    hsv_tuples = [(1.0 * x / num_classes, 1., 1.) for x in range(num_classes)]\n",
    "    \n",
    "    colors = list(map(lambda x: colorsys.hsv_to_rgb(*x), hsv_tuples))\n",
    "    colors = list(map(lambda x: (int(x[0] * 255), int(x[1] * 255), int(x[2] * 255)), colors))\n",
    "\n",
    "    random.seed(0)\n",
    "    random.shuffle(colors)\n",
    "    random.seed(None)\n",
    "\n",
    "    for i, bbox in enumerate(bboxes):\n",
    "        coor = np.array(bbox[:4], dtype=np.int32)\n",
    "        score = bbox[4]\n",
    "        class_ind = int(bbox[5])\n",
    "        \n",
    "        bbox_color = rectangle_colors if rectangle_colors != '' else colors[class_ind]\n",
    "        bbox_thick = int(0.6 * (image_h + image_w) / 1000)\n",
    "        \n",
    "        if bbox_thick < 1: bbox_thick = 1\n",
    "        fontScale = 0.75 * bbox_thick\n",
    "        (x1, y1), (x2, y2) = (coor[0], coor[1]), (coor[2], coor[3])\n",
    "\n",
    "        # put object rectangle\n",
    "        cv2.rectangle(image, (x1, y1), (x2, y2), bbox_color, bbox_thick*2)\n",
    "\n",
    "        if show_label:\n",
    "            # get text label\n",
    "            score_str = \" {:.2f}\".format(score) if show_confidence else \"\"\n",
    "\n",
    "            if tracking: score_str = \" \"+str(score)\n",
    "\n",
    "            label = \"{}\".format(NUM_CLASS[class_ind]) + score_str\n",
    "\n",
    "            # get text size\n",
    "            (text_width, text_height), baseline = cv2.getTextSize(label, cv2.FONT_HERSHEY_COMPLEX_SMALL,\n",
    "                                                                  fontScale, thickness=bbox_thick)\n",
    "            # put filled text rectangle\n",
    "            cv2.rectangle(image, (x1, y1), (x1 + text_width, y1 - text_height - baseline), bbox_color, thickness=cv2.FILLED)\n",
    "\n",
    "            # put text above rectangle\n",
    "            cv2.putText(image, label, (x1, y1-4), cv2.FONT_HERSHEY_COMPLEX_SMALL,\n",
    "                        fontScale, Text_colors, bbox_thick, lineType=cv2.LINE_AA)\n",
    "\n",
    "    return image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "16e824de",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:41.658754Z",
     "iopub.status.busy": "2023-09-01T03:12:41.657938Z",
     "iopub.status.idle": "2023-09-01T03:12:41.670042Z",
     "shell.execute_reply": "2023-09-01T03:12:41.669193Z"
    },
    "papermill": {
     "duration": 0.029296,
     "end_time": "2023-09-01T03:12:41.672412",
     "exception": false,
     "start_time": "2023-09-01T03:12:41.643116",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "NUM_CLASS = {\n",
    "    0: 'person',\n",
    "    1: 'bicycle',\n",
    "    2: 'car',\n",
    "    3: 'motorbike',\n",
    "    4: 'aeroplane',\n",
    "    5: 'bus',\n",
    "    6: 'train',\n",
    "    7: 'truck',\n",
    "    8: 'boat',\n",
    "    9: 'traffic-light',\n",
    "    10: 'fire-hydrant',\n",
    "    11: 'stop-sign',\n",
    "    12: 'parking-meter',\n",
    "    13: 'bench',\n",
    "    14: 'bird',\n",
    "    15: 'cat',\n",
    "    16: 'dog',\n",
    "    17: 'horse',\n",
    "    18: 'sheep',\n",
    "    19: 'cow',\n",
    "    20: 'elephant',\n",
    "    21: 'bear',\n",
    "    22: 'zebra',\n",
    "    23: 'giraffe',\n",
    "    24: 'backpack',\n",
    "    25: 'umbrella',\n",
    "    26: 'handbag',\n",
    "    27: 'tie',\n",
    "    28: 'suitcase',\n",
    "    29: 'frisbee',\n",
    "    30: 'skis',\n",
    "    31: 'snowboard',\n",
    "    32: 'sports-ball',\n",
    "    33: 'kite',\n",
    "    34: 'baseball-bat',\n",
    "    35: 'baseball-glove',\n",
    "    36: 'skateboard',\n",
    "    37: 'surfboard',\n",
    "    38: 'tennis-racket',\n",
    "    39: 'bottle',\n",
    "    40: 'wine-glass',\n",
    "    41: 'cup',\n",
    "    42: 'fork',\n",
    "    43: 'knife',\n",
    "    44: 'spoon',\n",
    "    45: 'bowl',\n",
    "    46: 'banana',\n",
    "    47: 'apple',\n",
    "    48: 'sandwich',\n",
    "    49: 'orange',\n",
    "    50: 'broccoli',\n",
    "    51: 'carrot',\n",
    "    52: 'hot-dog',\n",
    "    53: 'pizza',\n",
    "    54: 'donut',\n",
    "    55: 'cake',\n",
    "    56: 'chair',\n",
    "    57: 'sofa',\n",
    "    58: 'pottedplant',\n",
    "    59: 'bed',\n",
    "    60: 'diningtable',\n",
    "    61: 'toilet',\n",
    "    62: 'tvmonitor',\n",
    "    63: 'laptop',\n",
    "    64: 'mouse',\n",
    "    65: 'remote',\n",
    "    66: 'keyboard',\n",
    "    67: 'cell-phone',\n",
    "    68: 'microwave',\n",
    "    69: 'oven',\n",
    "    70: 'toaster',\n",
    "    71: 'sink',\n",
    "    72: 'refrigerator',\n",
    "    73: 'book',\n",
    "    74: 'clock',\n",
    "    75: 'vase',\n",
    "    76: 'scissors',\n",
    "    77: 'teddy-bear', \n",
    "    78: 'hair-drier',\n",
    "    79: 'toothbrush'\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "cc7d3e8c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:41.700784Z",
     "iopub.status.busy": "2023-09-01T03:12:41.700004Z",
     "iopub.status.idle": "2023-09-01T03:12:45.095304Z",
     "shell.execute_reply": "2023-09-01T03:12:45.093799Z"
    },
    "papermill": {
     "duration": 3.413229,
     "end_time": "2023-09-01T03:12:45.098735",
     "exception": false,
     "start_time": "2023-09-01T03:12:41.685506",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "#!wget https://pjreddie.com/media/files/yolov3.weights -O yolov3.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "be2e0ea0",
   "metadata": {},
   "outputs": [],
   "source": [
    "#!curl -o yolov3.weights https://pjreddie.com/media/files/yolov3.weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2ce858b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:45.130670Z",
     "iopub.status.busy": "2023-09-01T03:12:45.130133Z",
     "iopub.status.idle": "2023-09-01T03:12:50.812266Z",
     "shell.execute_reply": "2023-09-01T03:12:50.810926Z"
    },
    "papermill": {
     "duration": 5.70166,
     "end_time": "2023-09-01T03:12:50.815402",
     "exception": false,
     "start_time": "2023-09-01T03:12:45.113742",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading weights of convolution #0\n",
      "loading weights of convolution #1\n",
      "loading weights of convolution #2\n",
      "loading weights of convolution #3\n",
      "no convolution #4\n",
      "loading weights of convolution #5\n",
      "loading weights of convolution #6\n",
      "loading weights of convolution #7\n",
      "no convolution #8\n",
      "loading weights of convolution #9\n",
      "loading weights of convolution #10\n",
      "no convolution #11\n",
      "loading weights of convolution #12\n",
      "loading weights of convolution #13\n",
      "loading weights of convolution #14\n",
      "no convolution #15\n",
      "loading weights of convolution #16\n",
      "loading weights of convolution #17\n",
      "no convolution #18\n",
      "loading weights of convolution #19\n",
      "loading weights of convolution #20\n",
      "no convolution #21\n",
      "loading weights of convolution #22\n",
      "loading weights of convolution #23\n",
      "no convolution #24\n",
      "loading weights of convolution #25\n",
      "loading weights of convolution #26\n",
      "no convolution #27\n",
      "loading weights of convolution #28\n",
      "loading weights of convolution #29\n",
      "no convolution #30\n",
      "loading weights of convolution #31\n",
      "loading weights of convolution #32\n",
      "no convolution #33\n",
      "loading weights of convolution #34\n",
      "loading weights of convolution #35\n",
      "no convolution #36\n",
      "loading weights of convolution #37\n",
      "loading weights of convolution #38\n",
      "loading weights of convolution #39\n",
      "no convolution #40\n",
      "loading weights of convolution #41\n",
      "loading weights of convolution #42\n",
      "no convolution #43\n",
      "loading weights of convolution #44\n",
      "loading weights of convolution #45\n",
      "no convolution #46\n",
      "loading weights of convolution #47\n",
      "loading weights of convolution #48\n",
      "no convolution #49\n",
      "loading weights of convolution #50\n",
      "loading weights of convolution #51\n",
      "no convolution #52\n",
      "loading weights of convolution #53\n",
      "loading weights of convolution #54\n",
      "no convolution #55\n",
      "loading weights of convolution #56\n",
      "loading weights of convolution #57\n",
      "no convolution #58\n",
      "loading weights of convolution #59\n",
      "loading weights of convolution #60\n",
      "no convolution #61\n",
      "loading weights of convolution #62\n",
      "loading weights of convolution #63\n",
      "loading weights of convolution #64\n",
      "no convolution #65\n",
      "loading weights of convolution #66\n",
      "loading weights of convolution #67\n",
      "no convolution #68\n",
      "loading weights of convolution #69\n",
      "loading weights of convolution #70\n",
      "no convolution #71\n",
      "loading weights of convolution #72\n",
      "loading weights of convolution #73\n",
      "no convolution #74\n",
      "loading weights of convolution #75\n",
      "loading weights of convolution #76\n",
      "loading weights of convolution #77\n",
      "loading weights of convolution #78\n",
      "loading weights of convolution #79\n",
      "loading weights of convolution #80\n",
      "loading weights of convolution #81\n",
      "no convolution #82\n",
      "no convolution #83\n",
      "loading weights of convolution #84\n",
      "no convolution #85\n",
      "no convolution #86\n",
      "loading weights of convolution #87\n",
      "loading weights of convolution #88\n",
      "loading weights of convolution #89\n",
      "loading weights of convolution #90\n",
      "loading weights of convolution #91\n",
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      "loading weights of convolution #93\n",
      "no convolution #94\n",
      "no convolution #95\n",
      "loading weights of convolution #96\n",
      "no convolution #97\n",
      "no convolution #98\n",
      "loading weights of convolution #99\n",
      "loading weights of convolution #100\n",
      "loading weights of convolution #101\n",
      "loading weights of convolution #102\n",
      "loading weights of convolution #103\n",
      "loading weights of convolution #104\n",
      "loading weights of convolution #105\n",
      "WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
     ]
    }
   ],
   "source": [
    "# define the model\n",
    "model = make_yolov3_model()\n",
    "\n",
    "# load the model weights\n",
    "# I have loaded the pretrained weights in a separate dataset\n",
    "weight_reader = WeightReader('yolov3.weights')\n",
    "\n",
    "# set the model weights into the model\n",
    "weight_reader.load_weights(model)\n",
    "\n",
    "# save the model to file\n",
    "model.save('model.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8fd5fe35",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:50.850250Z",
     "iopub.status.busy": "2023-09-01T03:12:50.849720Z",
     "iopub.status.idle": "2023-09-01T03:12:54.617918Z",
     "shell.execute_reply": "2023-09-01T03:12:54.616601Z"
    },
    "papermill": {
     "duration": 3.7881,
     "end_time": "2023-09-01T03:12:54.621047",
     "exception": false,
     "start_time": "2023-09-01T03:12:50.832947",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.\n"
     ]
    }
   ],
   "source": [
    "# load yolov3 model\n",
    "from keras.models import load_model\n",
    "model = load_model('model.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "996f7911",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Manual compilation\n",
    "model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "a6f31029",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:54.654034Z",
     "iopub.status.busy": "2023-09-01T03:12:54.653549Z",
     "iopub.status.idle": "2023-09-01T03:12:54.660110Z",
     "shell.execute_reply": "2023-09-01T03:12:54.659003Z"
    },
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     "duration": 0.025626,
     "end_time": "2023-09-01T03:12:54.662333",
     "exception": false,
     "start_time": "2023-09-01T03:12:54.636707",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Parameters used in the Dataset, on which YOLOv3 was pretrained\n",
    "anchors = [[116,90, 156,198, 373,326], [30,61, 62,45, 59,119], [10,13, 16,30, 33,23]]\n",
    "\n",
    "# define the expected input shape for the model\n",
    "WIDTH, HEIGHT = 512, 512\n",
    "\n",
    "# define the probability threshold for detected objects\n",
    "class_threshold = 0.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "17f6ec92",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:54.695244Z",
     "iopub.status.busy": "2023-09-01T03:12:54.694793Z",
     "iopub.status.idle": "2023-09-01T03:12:54.993651Z",
     "shell.execute_reply": "2023-09-01T03:12:54.992531Z"
    },
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     "duration": 0.318531,
     "end_time": "2023-09-01T03:12:54.996732",
     "exception": false,
     "start_time": "2023-09-01T03:12:54.678201",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import errno\n",
    "import argparse\n",
    "import numpy as np\n",
    "import cv2\n",
    "import tensorflow.compat.v1 as tf\n",
    "import scipy.linalg\n",
    "from scipy.optimize import linear_sum_assignment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7d6af9b7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:55.030608Z",
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    },
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     "end_time": "2023-09-01T03:12:55.052324",
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class Detection(object):\n",
    "    \"\"\"\n",
    "    This class represents a bounding box detection in a single image.\n",
    "    Parameters\n",
    "    ----------\n",
    "    tlwh : array_like\n",
    "        Bounding box in format `(x, y, w, h)`.\n",
    "    confidence : float\n",
    "        Detector confidence score.\n",
    "    feature : array_like\n",
    "        A feature vector that describes the object contained in this image.\n",
    "    Attributes\n",
    "    ----------\n",
    "    tlwh : ndarray\n",
    "        Bounding box in format `(top left x, top left y, width, height)`.\n",
    "    confidence : ndarray\n",
    "        Detector confidence score.\n",
    "    class_name : ndarray\n",
    "        Detector class.\n",
    "    feature : ndarray | NoneType\n",
    "        A feature vector that describes the object contained in this image.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, tlwh, confidence, class_name, feature):\n",
    "        #self.tlwh = np.asarray(tlwh, dtype=np.float)\n",
    "        self.tlwh = np.asarray(tlwh, dtype=float)\n",
    "        self.confidence = float(confidence)\n",
    "        self.class_name = class_name\n",
    "        self.feature = np.asarray(feature, dtype=np.float32)\n",
    "\n",
    "    def get_class(self):\n",
    "        return self.class_name\n",
    "\n",
    "    def to_tlbr(self):\n",
    "        \"\"\"Convert bounding box to format `(min x, min y, max x, max y)`, i.e.,\n",
    "        `(top left, bottom right)`.\n",
    "        \"\"\"\n",
    "        ret = self.tlwh.copy()\n",
    "        ret[2:] += ret[:2]\n",
    "        return ret\n",
    "\n",
    "    def to_xyah(self):\n",
    "        \"\"\"Convert bounding box to format `(center x, center y, aspect ratio,\n",
    "        height)`, where the aspect ratio is `width / height`.\n",
    "        \"\"\"\n",
    "        ret = self.tlwh.copy()\n",
    "        ret[:2] += ret[2:] / 2\n",
    "        ret[2] /= ret[3]\n",
    "        return ret\n",
    "\n",
    "class ImageEncoder(object):\n",
    "\n",
    "    def __init__(self, checkpoint_filename, input_name=\"images\", output_name=\"features\"):\n",
    "        self.session = tf.Session()\n",
    "        with tf.gfile.GFile(checkpoint_filename, \"rb\") as file_handle:\n",
    "            graph_def = tf.GraphDef()\n",
    "            graph_def.ParseFromString(file_handle.read())\n",
    "        tf.import_graph_def(graph_def)\n",
    "        try:\n",
    "            self.input_var = tf.get_default_graph().get_tensor_by_name(input_name)\n",
    "            self.output_var = tf.get_default_graph().get_tensor_by_name(output_name)\n",
    "        except KeyError:\n",
    "            layers = [i.name for i in tf.get_default_graph().get_operations()]\n",
    "            self.input_var = tf.get_default_graph().get_tensor_by_name(layers[0]+':0')\n",
    "            self.output_var = tf.get_default_graph().get_tensor_by_name(layers[-1]+':0')            \n",
    "\n",
    "        assert len(self.output_var.get_shape()) == 2\n",
    "        assert len(self.input_var.get_shape()) == 4\n",
    "        self.feature_dim = self.output_var.get_shape().as_list()[-1]\n",
    "        self.image_shape = self.input_var.get_shape().as_list()[1:]\n",
    "\n",
    "    def __call__(self, data_x, batch_size=32):\n",
    "        out = np.zeros((len(data_x), self.feature_dim), np.float32)\n",
    "        _run_in_batches(\n",
    "            lambda x: self.session.run(self.output_var, feed_dict=x),\n",
    "            {self.input_var: data_x}, out, batch_size)\n",
    "        return out"
   ]
  },
  {
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   "id": "2c887bc8",
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     "exception": false,
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   "source": [
    "def _run_in_batches(f, data_dict, out, batch_size):\n",
    "    data_len = len(out)\n",
    "    num_batches = int(data_len / batch_size)\n",
    "\n",
    "    s, e = 0, 0\n",
    "    for i in range(num_batches):\n",
    "        s, e = i * batch_size, (i + 1) * batch_size\n",
    "        batch_data_dict = {k: v[s:e] for k, v in data_dict.items()}\n",
    "        out[s:e] = f(batch_data_dict)\n",
    "    if e < len(out):\n",
    "        batch_data_dict = {k: v[e:] for k, v in data_dict.items()}\n",
    "        out[e:] = f(batch_data_dict)\n",
    "\n",
    "\n",
    "def extract_image_patch(image, bbox, patch_shape):\n",
    "    \"\"\"Extract image patch from bounding box.\n",
    "    Parameters\n",
    "    ----------\n",
    "    image : ndarray\n",
    "        The full image.\n",
    "    bbox : array_like\n",
    "        The bounding box in format (x, y, width, height).\n",
    "    patch_shape : Optional[array_like]\n",
    "        This parameter can be used to enforce a desired patch shape\n",
    "        (height, width). First, the `bbox` is adapted to the aspect ratio\n",
    "        of the patch shape, then it is clipped at the image boundaries.\n",
    "        If None, the shape is computed from :arg:`bbox`.\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray | NoneType\n",
    "        An image patch showing the :arg:`bbox`, optionally reshaped to\n",
    "        :arg:`patch_shape`.\n",
    "        Returns None if the bounding box is empty or fully outside of the image\n",
    "        boundaries.\n",
    "    \"\"\"\n",
    "    bbox = np.array(bbox)\n",
    "    if patch_shape is not None:\n",
    "        # correct aspect ratio to patch shape\n",
    "        target_aspect = float(patch_shape[1]) / patch_shape[0]\n",
    "        new_width = target_aspect * bbox[3]\n",
    "        bbox[0] -= (new_width - bbox[2]) / 2\n",
    "        bbox[2] = new_width\n",
    "\n",
    "    # convert to top left, bottom right\n",
    "    bbox[2:] += bbox[:2]\n",
    "    bbox = bbox.astype(int) #modified\n",
    "    # bbox = bbox.astype(np.int)\n",
    "\n",
    "    # clip at image boundaries\n",
    "    bbox[:2] = np.maximum(0, bbox[:2])\n",
    "    bbox[2:] = np.minimum(np.asarray(image.shape[:2][::-1]) - 1, bbox[2:])\n",
    "    if np.any(bbox[:2] >= bbox[2:]):\n",
    "        return None\n",
    "    sx, sy, ex, ey = bbox\n",
    "    image = image[sy:ey, sx:ex]\n",
    "    image = cv2.resize(image, tuple(patch_shape[::-1]))\n",
    "    return image\n",
    "\n",
    "def create_box_encoder(model_filename, input_name=\"images:0\", output_name=\"features:0\", batch_size=32):\n",
    "    image_encoder = ImageEncoder(model_filename, input_name, output_name)\n",
    "    image_shape = image_encoder.image_shape\n",
    "\n",
    "    def encoder(image, boxes):\n",
    "        image_patches = []\n",
    "        for box in boxes:\n",
    "            patch = extract_image_patch(image, box, image_shape[:2])\n",
    "            if patch is None:\n",
    "                print(\"WARNING: Failed to extract image patch: %s.\" % str(box))\n",
    "                patch = np.random.uniform(0., 255., image_shape).astype(np.uint8)\n",
    "            image_patches.append(patch)\n",
    "        image_patches = np.asarray(image_patches)\n",
    "        return image_encoder(image_patches, batch_size)\n",
    "\n",
    "    return encoder\n",
    "\n",
    "\n",
    "def generate_detections(encoder, mot_dir, output_dir, detection_dir=None):\n",
    "    \"\"\"Generate detections with features.\n",
    "    Parameters\n",
    "    ----------\n",
    "    encoder : Callable[image, ndarray] -> ndarray\n",
    "        The encoder function takes as input a BGR color image and a matrix of\n",
    "        bounding boxes in format `(x, y, w, h)` and returns a matrix of\n",
    "        corresponding feature vectors.\n",
    "    mot_dir : str\n",
    "        Path to the MOTChallenge directory (can be either train or test).\n",
    "    output_dir\n",
    "        Path to the output directory. Will be created if it does not exist.\n",
    "    detection_dir\n",
    "        Path to custom detections. The directory structure should be the default\n",
    "        MOTChallenge structure: `[sequence]/det/det.txt`. If None, uses the\n",
    "        standard MOTChallenge detections.\n",
    "    \"\"\"\n",
    "    if detection_dir is None:\n",
    "        detection_dir = mot_dir\n",
    "    try:\n",
    "        os.makedirs(output_dir)\n",
    "    except OSError as exception:\n",
    "        if exception.errno == errno.EEXIST and os.path.isdir(output_dir):\n",
    "            pass\n",
    "        else:\n",
    "            raise ValueError(\n",
    "                \"Failed to created output directory '%s'\" % output_dir)\n",
    "\n",
    "    for sequence in os.listdir(mot_dir):\n",
    "        print(\"Processing %s\" % sequence)\n",
    "        sequence_dir = os.path.join(mot_dir, sequence)\n",
    "\n",
    "        image_dir = os.path.join(sequence_dir, \"img1\")\n",
    "        image_filenames = {\n",
    "            int(os.path.splitext(f)[0]): os.path.join(image_dir, f)\n",
    "            for f in os.listdir(image_dir)}\n",
    "\n",
    "        detection_file = os.path.join(\n",
    "            detection_dir, sequence, \"det/det.txt\")\n",
    "        detections_in = np.loadtxt(detection_file, delimiter=',')\n",
    "        detections_out = []\n",
    "\n",
    "        frame_indices = detections_in[:, 0].astype(np.int)\n",
    "        min_frame_idx = frame_indices.astype(np.int).min()\n",
    "        max_frame_idx = frame_indices.astype(np.int).max()\n",
    "        for frame_idx in range(min_frame_idx, max_frame_idx + 1):\n",
    "            print(\"Frame %05d/%05d\" % (frame_idx, max_frame_idx))\n",
    "            mask = frame_indices == frame_idx\n",
    "            rows = detections_in[mask]\n",
    "\n",
    "            if frame_idx not in image_filenames:\n",
    "                print(\"WARNING could not find image for frame %d\" % frame_idx)\n",
    "                continue\n",
    "            bgr_image = cv2.imread(\n",
    "                image_filenames[frame_idx], cv2.IMREAD_COLOR)\n",
    "            features = encoder(bgr_image, rows[:, 2:6].copy())\n",
    "            detections_out += [np.r_[(row, feature)] for row, feature\n",
    "                               in zip(rows, features)]\n",
    "\n",
    "        output_filename = os.path.join(output_dir, \"%s.npy\" % sequence)\n",
    "        np.save(\n",
    "            output_filename, np.asarray(detections_out), allow_pickle=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "d57274a5",
   "metadata": {
    "execution": {
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     "status": "completed"
    },
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   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'wget' is not recognized as an internal or external command,\n",
      "operable program or batch file.\n"
     ]
    }
   ],
   "source": [
    "!wget https://github.com/anushkadhiman/ObjectTracking-DeepSORT-YOLOv3-TF2/raw/master/model_data/coco/mars-small128.pb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "02ed56eb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T03:12:57.205779Z",
     "iopub.status.busy": "2023-09-01T03:12:57.205290Z",
     "iopub.status.idle": "2023-09-01T03:12:57.236118Z",
     "shell.execute_reply": "2023-09-01T03:12:57.234804Z"
    },
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     "duration": 0.051616,
     "end_time": "2023-09-01T03:12:57.238511",
     "exception": false,
     "start_time": "2023-09-01T03:12:57.186895",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Table for the 0.95 quantile of the chi-square distribution with N degrees of\n",
    "freedom (contains values for N=1, ..., 9). Taken from MATLAB/Octave's chi2inv\n",
    "function and used as Mahalanobis gating threshold.\n",
    "\"\"\"\n",
    "chi2inv95 = {\n",
    "    1: 3.8415,\n",
    "    2: 5.9915,\n",
    "    3: 7.8147,\n",
    "    4: 9.4877,\n",
    "    5: 11.070,\n",
    "    6: 12.592,\n",
    "    7: 14.067,\n",
    "    8: 15.507,\n",
    "    9: 16.919}\n",
    "\n",
    "\n",
    "class KalmanFilter(object):\n",
    "    \"\"\"\n",
    "    A simple Kalman filter for tracking bounding boxes in image space.\n",
    "    The 8-dimensional state space\n",
    "        x, y, a, h, vx, vy, va, vh\n",
    "    contains the bounding box center position (x, y), aspect ratio a, height h,\n",
    "    and their respective velocities.\n",
    "    Object motion follows a constant velocity model. The bounding box location\n",
    "    (x, y, a, h) is taken as direct observation of the state space (linear\n",
    "    observation model).\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self):\n",
    "        ndim, dt = 4, 1.\n",
    "\n",
    "        # Create Kalman filter model matrices.\n",
    "        self._motion_mat = np.eye(2 * ndim, 2 * ndim)\n",
    "        for i in range(ndim):\n",
    "            self._motion_mat[i, ndim + i] = dt\n",
    "        self._update_mat = np.eye(ndim, 2 * ndim)\n",
    "\n",
    "        # Motion and observation uncertainty are chosen relative to the current\n",
    "        # state estimate. These weights control the amount of uncertainty in\n",
    "        # the model. This is a bit hacky.\n",
    "        self._std_weight_position = 1. / 20\n",
    "        self._std_weight_velocity = 1. / 160\n",
    "\n",
    "    def initiate(self, measurement):\n",
    "        \"\"\"Create track from unassociated measurement.\n",
    "        Parameters\n",
    "        ----------\n",
    "        measurement : ndarray\n",
    "            Bounding box coordinates (x, y, a, h) with center position (x, y),\n",
    "            aspect ratio a, and height h.\n",
    "        Returns\n",
    "        -------\n",
    "        (ndarray, ndarray)\n",
    "            Returns the mean vector (8 dimensional) and covariance matrix (8x8\n",
    "            dimensional) of the new track. Unobserved velocities are initialized\n",
    "            to 0 mean.\n",
    "        \"\"\"\n",
    "        mean_pos = measurement\n",
    "        mean_vel = np.zeros_like(mean_pos)\n",
    "        mean = np.r_[mean_pos, mean_vel]\n",
    "\n",
    "        std = [\n",
    "            2 * self._std_weight_position * measurement[3],\n",
    "            2 * self._std_weight_position * measurement[3],\n",
    "            1e-2,\n",
    "            2 * self._std_weight_position * measurement[3],\n",
    "            10 * self._std_weight_velocity * measurement[3],\n",
    "            10 * self._std_weight_velocity * measurement[3],\n",
    "            1e-5,\n",
    "            10 * self._std_weight_velocity * measurement[3]]\n",
    "        covariance = np.diag(np.square(std))\n",
    "        return mean, covariance\n",
    "\n",
    "    def predict(self, mean, covariance):\n",
    "        \"\"\"Run Kalman filter prediction step.\n",
    "        Parameters\n",
    "        ----------\n",
    "        mean : ndarray\n",
    "            The 8 dimensional mean vector of the object state at the previous\n",
    "            time step.\n",
    "        covariance : ndarray\n",
    "            The 8x8 dimensional covariance matrix of the object state at the\n",
    "            previous time step.\n",
    "        Returns\n",
    "        -------\n",
    "        (ndarray, ndarray)\n",
    "            Returns the mean vector and covariance matrix of the predicted\n",
    "            state. Unobserved velocities are initialized to 0 mean.\n",
    "        \"\"\"\n",
    "        std_pos = [\n",
    "            self._std_weight_position * mean[3],\n",
    "            self._std_weight_position * mean[3],\n",
    "            1e-2,\n",
    "            self._std_weight_position * mean[3]]\n",
    "        std_vel = [\n",
    "            self._std_weight_velocity * mean[3],\n",
    "            self._std_weight_velocity * mean[3],\n",
    "            1e-5,\n",
    "            self._std_weight_velocity * mean[3]]\n",
    "        motion_cov = np.diag(np.square(np.r_[std_pos, std_vel]))\n",
    "\n",
    "        mean = np.dot(self._motion_mat, mean)\n",
    "        covariance = np.linalg.multi_dot((\n",
    "            self._motion_mat, covariance, self._motion_mat.T)) + motion_cov\n",
    "\n",
    "        return mean, covariance\n",
    "\n",
    "    def project(self, mean, covariance):\n",
    "        \"\"\"Project state distribution to measurement space.\n",
    "        Parameters\n",
    "        ----------\n",
    "        mean : ndarray\n",
    "            The state's mean vector (8 dimensional array).\n",
    "        covariance : ndarray\n",
    "            The state's covariance matrix (8x8 dimensional).\n",
    "        Returns\n",
    "        -------\n",
    "        (ndarray, ndarray)\n",
    "            Returns the projected mean and covariance matrix of the given state\n",
    "            estimate.\n",
    "        \"\"\"\n",
    "        std = [\n",
    "            self._std_weight_position * mean[3],\n",
    "            self._std_weight_position * mean[3],\n",
    "            1e-1,\n",
    "            self._std_weight_position * mean[3]]\n",
    "        innovation_cov = np.diag(np.square(std))\n",
    "\n",
    "        mean = np.dot(self._update_mat, mean)\n",
    "        covariance = np.linalg.multi_dot((\n",
    "            self._update_mat, covariance, self._update_mat.T))\n",
    "        return mean, covariance + innovation_cov\n",
    "\n",
    "    def update(self, mean, covariance, measurement):\n",
    "        \"\"\"Run Kalman filter correction step.\n",
    "        Parameters\n",
    "        ----------\n",
    "        mean : ndarray\n",
    "            The predicted state's mean vector (8 dimensional).\n",
    "        covariance : ndarray\n",
    "            The state's covariance matrix (8x8 dimensional).\n",
    "        measurement : ndarray\n",
    "            The 4 dimensional measurement vector (x, y, a, h), where (x, y)\n",
    "            is the center position, a the aspect ratio, and h the height of the\n",
    "            bounding box.\n",
    "        Returns\n",
    "        -------\n",
    "        (ndarray, ndarray)\n",
    "            Returns the measurement-corrected state distribution.\n",
    "        \"\"\"\n",
    "        projected_mean, projected_cov = self.project(mean, covariance)\n",
    "\n",
    "        chol_factor, lower = scipy.linalg.cho_factor(\n",
    "            projected_cov, lower=True, check_finite=False)\n",
    "        kalman_gain = scipy.linalg.cho_solve(\n",
    "            (chol_factor, lower), np.dot(covariance, self._update_mat.T).T,\n",
    "            check_finite=False).T\n",
    "        innovation = measurement - projected_mean\n",
    "\n",
    "        new_mean = mean + np.dot(innovation, kalman_gain.T)\n",
    "        new_covariance = covariance - np.linalg.multi_dot((\n",
    "            kalman_gain, projected_cov, kalman_gain.T))\n",
    "        return new_mean, new_covariance\n",
    "\n",
    "    def gating_distance(self, mean, covariance, measurements,\n",
    "                        only_position=False):\n",
    "        \"\"\"Compute gating distance between state distribution and measurements.\n",
    "        A suitable distance threshold can be obtained from `chi2inv95`. If\n",
    "        `only_position` is False, the chi-square distribution has 4 degrees of\n",
    "        freedom, otherwise 2.\n",
    "        Parameters\n",
    "        ----------\n",
    "        mean : ndarray\n",
    "            Mean vector over the state distribution (8 dimensional).\n",
    "        covariance : ndarray\n",
    "            Covariance of the state distribution (8x8 dimensional).\n",
    "        measurements : ndarray\n",
    "            An Nx4 dimensional matrix of N measurements, each in\n",
    "            format (x, y, a, h) where (x, y) is the bounding box center\n",
    "            position, a the aspect ratio, and h the height.\n",
    "        only_position : Optional[bool]\n",
    "            If True, distance computation is done with respect to the bounding\n",
    "            box center position only.\n",
    "        Returns\n",
    "        -------\n",
    "        ndarray\n",
    "            Returns an array of length N, where the i-th element contains the\n",
    "            squared Mahalanobis distance between (mean, covariance) and\n",
    "            `measurements[i]`.\n",
    "        \"\"\"\n",
    "        mean, covariance = self.project(mean, covariance)\n",
    "        if only_position:\n",
    "            mean, covariance = mean[:2], covariance[:2, :2]\n",
    "            measurements = measurements[:, :2]\n",
    "\n",
    "        cholesky_factor = np.linalg.cholesky(covariance)\n",
    "        d = measurements - mean\n",
    "        z = scipy.linalg.solve_triangular(\n",
    "            cholesky_factor, d.T, lower=True, check_finite=False,\n",
    "            overwrite_b=True)\n",
    "        squared_maha = np.sum(z * z, axis=0)\n",
    "        return squared_maha"
   ]
  },
  {
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   "source": [
    "INFTY_COST = 1e+5\n",
    "\n",
    "\n",
    "def min_cost_matching(\n",
    "        distance_metric, max_distance, tracks, detections, track_indices=None,\n",
    "        detection_indices=None):\n",
    "    \"\"\"Solve linear assignment problem.\n",
    "    Parameters\n",
    "    ----------\n",
    "    distance_metric : Callable[List[Track], List[Detection], List[int], List[int]) -> ndarray\n",
    "        The distance metric is given a list of tracks and detections as well as\n",
    "        a list of N track indices and M detection indices. The metric should\n",
    "        return the NxM dimensional cost matrix, where element (i, j) is the\n",
    "        association cost between the i-th track in the given track indices and\n",
    "        the j-th detection in the given detection_indices.\n",
    "    max_distance : float\n",
    "        Gating threshold. Associations with cost larger than this value are\n",
    "        disregarded.\n",
    "    tracks : List[track.Track]\n",
    "        A list of predicted tracks at the current time step.\n",
    "    detections : List[detection.Detection]\n",
    "        A list of detections at the current time step.\n",
    "    track_indices : List[int]\n",
    "        List of track indices that maps rows in `cost_matrix` to tracks in\n",
    "        `tracks` (see description above).\n",
    "    detection_indices : List[int]\n",
    "        List of detection indices that maps columns in `cost_matrix` to\n",
    "        detections in `detections` (see description above).\n",
    "    Returns\n",
    "    -------\n",
    "    (List[(int, int)], List[int], List[int])\n",
    "        Returns a tuple with the following three entries:\n",
    "        * A list of matched track and detection indices.\n",
    "        * A list of unmatched track indices.\n",
    "        * A list of unmatched detection indices.\n",
    "    \"\"\"\n",
    "    if track_indices is None:\n",
    "        track_indices = np.arange(len(tracks))\n",
    "    if detection_indices is None:\n",
    "        detection_indices = np.arange(len(detections))\n",
    "\n",
    "    if len(detection_indices) == 0 or len(track_indices) == 0:\n",
    "        return [], track_indices, detection_indices  # Nothing to match.\n",
    "\n",
    "    cost_matrix = distance_metric(\n",
    "        tracks, detections, track_indices, detection_indices)\n",
    "    cost_matrix[cost_matrix > max_distance] = max_distance + 1e-5\n",
    "    indices = linear_sum_assignment(cost_matrix)\n",
    "    indices = np.asarray(indices)\n",
    "    indices = np.transpose(indices)\n",
    "    matches, unmatched_tracks, unmatched_detections = [], [], []\n",
    "    for col, detection_idx in enumerate(detection_indices):\n",
    "        if col not in indices[:, 1]:\n",
    "            unmatched_detections.append(detection_idx)\n",
    "    for row, track_idx in enumerate(track_indices):\n",
    "        if row not in indices[:, 0]:\n",
    "            unmatched_tracks.append(track_idx)\n",
    "    for row, col in indices:\n",
    "        track_idx = track_indices[row]\n",
    "        detection_idx = detection_indices[col]\n",
    "        if cost_matrix[row, col] > max_distance:\n",
    "            unmatched_tracks.append(track_idx)\n",
    "            unmatched_detections.append(detection_idx)\n",
    "        else:\n",
    "            matches.append((track_idx, detection_idx))\n",
    "    return matches, unmatched_tracks, unmatched_detections\n",
    "\n",
    "\n",
    "def matching_cascade(\n",
    "        distance_metric, max_distance, cascade_depth, tracks, detections,\n",
    "        track_indices=None, detection_indices=None):\n",
    "    \"\"\"Run matching cascade.\n",
    "    Parameters\n",
    "    ----------\n",
    "    distance_metric : Callable[List[Track], List[Detection], List[int], List[int]) -> ndarray\n",
    "        The distance metric is given a list of tracks and detections as well as\n",
    "        a list of N track indices and M detection indices. The metric should\n",
    "        return the NxM dimensional cost matrix, where element (i, j) is the\n",
    "        association cost between the i-th track in the given track indices and\n",
    "        the j-th detection in the given detection indices.\n",
    "    max_distance : float\n",
    "        Gating threshold. Associations with cost larger than this value are\n",
    "        disregarded.\n",
    "    cascade_depth: int\n",
    "        The cascade depth, should be se to the maximum track age.\n",
    "    tracks : List[track.Track]\n",
    "        A list of predicted tracks at the current time step.\n",
    "    detections : List[detection.Detection]\n",
    "        A list of detections at the current time step.\n",
    "    track_indices : Optional[List[int]]\n",
    "        List of track indices that maps rows in `cost_matrix` to tracks in\n",
    "        `tracks` (see description above). Defaults to all tracks.\n",
    "    detection_indices : Optional[List[int]]\n",
    "        List of detection indices that maps columns in `cost_matrix` to\n",
    "        detections in `detections` (see description above). Defaults to all\n",
    "        detections.\n",
    "    Returns\n",
    "    -------\n",
    "    (List[(int, int)], List[int], List[int])\n",
    "        Returns a tuple with the following three entries:\n",
    "        * A list of matched track and detection indices.\n",
    "        * A list of unmatched track indices.\n",
    "        * A list of unmatched detection indices.\n",
    "    \"\"\"\n",
    "    if track_indices is None:\n",
    "        track_indices = list(range(len(tracks)))\n",
    "    if detection_indices is None:\n",
    "        detection_indices = list(range(len(detections)))\n",
    "\n",
    "    unmatched_detections = detection_indices\n",
    "    matches = []\n",
    "    for level in range(cascade_depth):\n",
    "        if len(unmatched_detections) == 0:  # No detections left\n",
    "            break\n",
    "\n",
    "        track_indices_l = [\n",
    "            k for k in track_indices\n",
    "            if tracks[k].time_since_update == 1 + level\n",
    "        ]\n",
    "        if len(track_indices_l) == 0:  # Nothing to match at this level\n",
    "            continue\n",
    "\n",
    "        matches_l, _, unmatched_detections = \\\n",
    "            min_cost_matching(\n",
    "                distance_metric, max_distance, tracks, detections,\n",
    "                track_indices_l, unmatched_detections)\n",
    "        matches += matches_l\n",
    "    unmatched_tracks = list(set(track_indices) - set(k for k, _ in matches))\n",
    "    return matches, unmatched_tracks, unmatched_detections\n",
    "\n",
    "\n",
    "def gate_cost_matrix(\n",
    "        kf, cost_matrix, tracks, detections, track_indices, detection_indices,\n",
    "        gated_cost=INFTY_COST, only_position=False):\n",
    "    \"\"\"Invalidate infeasible entries in cost matrix based on the state\n",
    "    distributions obtained by Kalman filtering.\n",
    "    Parameters\n",
    "    ----------\n",
    "    kf : The Kalman filter.\n",
    "    cost_matrix : ndarray\n",
    "        The NxM dimensional cost matrix, where N is the number of track indices\n",
    "        and M is the number of detection indices, such that entry (i, j) is the\n",
    "        association cost between `tracks[track_indices[i]]` and\n",
    "        `detections[detection_indices[j]]`.\n",
    "    tracks : List[track.Track]\n",
    "        A list of predicted tracks at the current time step.\n",
    "    detections : List[detection.Detection]\n",
    "        A list of detections at the current time step.\n",
    "    track_indices : List[int]\n",
    "        List of track indices that maps rows in `cost_matrix` to tracks in\n",
    "        `tracks` (see description above).\n",
    "    detection_indices : List[int]\n",
    "        List of detection indices that maps columns in `cost_matrix` to\n",
    "        detections in `detections` (see description above).\n",
    "    gated_cost : Optional[float]\n",
    "        Entries in the cost matrix corresponding to infeasible associations are\n",
    "        set this value. Defaults to a very large value.\n",
    "    only_position : Optional[bool]\n",
    "        If True, only the x, y position of the state distribution is considered\n",
    "        during gating. Defaults to False.\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        Returns the modified cost matrix.\n",
    "    \"\"\"\n",
    "    gating_dim = 2 if only_position else 4\n",
    "    gating_threshold = chi2inv95[gating_dim]\n",
    "    measurements = np.asarray(\n",
    "        [detections[i].to_xyah() for i in detection_indices])\n",
    "    for row, track_idx in enumerate(track_indices):\n",
    "        track = tracks[track_idx]\n",
    "        gating_distance = kf.gating_distance(\n",
    "            track.mean, track.covariance, measurements, only_position)\n",
    "        cost_matrix[row, gating_distance > gating_threshold] = gated_cost\n",
    "    return cost_matrix"
   ]
  },
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   "source": [
    "def iou(bbox, candidates):\n",
    "    \"\"\"Computer intersection over union.\n",
    "    Parameters\n",
    "    ----------\n",
    "    bbox : ndarray\n",
    "        A bounding box in format `(top left x, top left y, width, height)`.\n",
    "    candidates : ndarray\n",
    "        A matrix of candidate bounding boxes (one per row) in the same format\n",
    "        as `bbox`.\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        The intersection over union in [0, 1] between the `bbox` and each\n",
    "        candidate. A higher score means a larger fraction of the `bbox` is\n",
    "        occluded by the candidate.\n",
    "    \"\"\"\n",
    "    bbox_tl, bbox_br = bbox[:2], bbox[:2] + bbox[2:]\n",
    "    candidates_tl = candidates[:, :2]\n",
    "    candidates_br = candidates[:, :2] + candidates[:, 2:]\n",
    "\n",
    "    tl = np.c_[np.maximum(bbox_tl[0], candidates_tl[:, 0])[:, np.newaxis],\n",
    "               np.maximum(bbox_tl[1], candidates_tl[:, 1])[:, np.newaxis]]\n",
    "    br = np.c_[np.minimum(bbox_br[0], candidates_br[:, 0])[:, np.newaxis],\n",
    "               np.minimum(bbox_br[1], candidates_br[:, 1])[:, np.newaxis]]\n",
    "    wh = np.maximum(0., br - tl)\n",
    "\n",
    "    area_intersection = wh.prod(axis=1)\n",
    "    area_bbox = bbox[2:].prod()\n",
    "    area_candidates = candidates[:, 2:].prod(axis=1)\n",
    "    return area_intersection / (area_bbox + area_candidates - area_intersection)\n",
    "\n",
    "\n",
    "def iou_cost(tracks, detections, track_indices=None,\n",
    "             detection_indices=None):\n",
    "    \"\"\"An intersection over union distance metric.\n",
    "    Parameters\n",
    "    ----------\n",
    "    tracks : List[deep_sort.track.Track]\n",
    "        A list of tracks.\n",
    "    detections : List[deep_sort.detection.Detection]\n",
    "        A list of detections.\n",
    "    track_indices : Optional[List[int]]\n",
    "        A list of indices to tracks that should be matched. Defaults to\n",
    "        all `tracks`.\n",
    "    detection_indices : Optional[List[int]]\n",
    "        A list of indices to detections that should be matched. Defaults\n",
    "        to all `detections`.\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        Returns a cost matrix of shape\n",
    "        len(track_indices), len(detection_indices) where entry (i, j) is\n",
    "        `1 - iou(tracks[track_indices[i]], detections[detection_indices[j]])`.\n",
    "    \"\"\"\n",
    "    if track_indices is None:\n",
    "        track_indices = np.arange(len(tracks))\n",
    "    if detection_indices is None:\n",
    "        detection_indices = np.arange(len(detections))\n",
    "\n",
    "    cost_matrix = np.zeros((len(track_indices), len(detection_indices)))\n",
    "    for row, track_idx in enumerate(track_indices):\n",
    "        if tracks[track_idx].time_since_update > 1:\n",
    "            cost_matrix[row, :] = linear_assignment.INFTY_COST\n",
    "            continue\n",
    "\n",
    "        bbox = tracks[track_idx].to_tlwh()\n",
    "        candidates = np.asarray([detections[i].tlwh for i in detection_indices])\n",
    "        cost_matrix[row, :] = 1. - iou(bbox, candidates)\n",
    "    return cost_matrix"
   ]
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    "def non_max_suppression(boxes, classes, max_bbox_overlap, scores=None):\n",
    "    \"\"\"Suppress overlapping detections.\n",
    "    Original code from [1]_ has been adapted to include confidence score.\n",
    "    .. [1] http://www.pyimagesearch.com/2015/02/16/\n",
    "           faster-non-maximum-suppression-python/\n",
    "    Examples\n",
    "    --------\n",
    "        >>> boxes = [d.roi for d in detections]\n",
    "        >>> classes = [d.classes for d in detections]\n",
    "        >>> scores = [d.confidence for d in detections]\n",
    "        >>> indices = non_max_suppression(boxes, max_bbox_overlap, scores)\n",
    "        >>> detections = [detections[i] for i in indices]\n",
    "    Parameters\n",
    "    ----------\n",
    "    boxes : ndarray\n",
    "        Array of ROIs (x, y, width, height).\n",
    "    max_bbox_overlap : float\n",
    "        ROIs that overlap more than this values are suppressed.\n",
    "    scores : Optional[array_like]\n",
    "        Detector confidence score.\n",
    "    Returns\n",
    "    -------\n",
    "    List[int]\n",
    "        Returns indices of detections that have survived non-maxima suppression.\n",
    "    \"\"\"\n",
    "    if len(boxes) == 0:\n",
    "        return []\n",
    "\n",
    "    boxes = boxes.astype(np.float)\n",
    "    pick = []\n",
    "\n",
    "    x1 = boxes[:, 0]\n",
    "    y1 = boxes[:, 1]\n",
    "    x2 = boxes[:, 2] + boxes[:, 0]\n",
    "    y2 = boxes[:, 3] + boxes[:, 1]\n",
    "\n",
    "    area = (x2 - x1 + 1) * (y2 - y1 + 1)\n",
    "    if scores is not None:\n",
    "        idxs = np.argsort(scores)\n",
    "    else:\n",
    "        idxs = np.argsort(y2)\n",
    "\n",
    "    while len(idxs) > 0:\n",
    "        last = len(idxs) - 1\n",
    "        i = idxs[last]\n",
    "        pick.append(i)\n",
    "\n",
    "        xx1 = np.maximum(x1[i], x1[idxs[:last]])\n",
    "        yy1 = np.maximum(y1[i], y1[idxs[:last]])\n",
    "        xx2 = np.minimum(x2[i], x2[idxs[:last]])\n",
    "        yy2 = np.minimum(y2[i], y2[idxs[:last]])\n",
    "\n",
    "        w = np.maximum(0, xx2 - xx1 + 1)\n",
    "        h = np.maximum(0, yy2 - yy1 + 1)\n",
    "\n",
    "        overlap = (w * h) / area[idxs[:last]]\n",
    "\n",
    "        idxs = np.delete(\n",
    "            idxs, np.concatenate(\n",
    "                ([last], np.where(overlap > max_bbox_overlap)[0])))\n",
    "\n",
    "    return pick"
   ]
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   "source": [
    "def _pdist(a, b):\n",
    "    \"\"\"Compute pair-wise squared distance between points in `a` and `b`.\n",
    "    Parameters\n",
    "    ----------\n",
    "    a : array_like\n",
    "        An NxM matrix of N samples of dimensionality M.\n",
    "    b : array_like\n",
    "        An LxM matrix of L samples of dimensionality M.\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        Returns a matrix of size len(a), len(b) such that eleement (i, j)\n",
    "        contains the squared distance between `a[i]` and `b[j]`.\n",
    "    \"\"\"\n",
    "    a, b = np.asarray(a), np.asarray(b)\n",
    "    if len(a) == 0 or len(b) == 0:\n",
    "        return np.zeros((len(a), len(b)))\n",
    "    a2, b2 = np.square(a).sum(axis=1), np.square(b).sum(axis=1)\n",
    "    r2 = -2. * np.dot(a, b.T) + a2[:, None] + b2[None, :]\n",
    "    r2 = np.clip(r2, 0., float(np.inf))\n",
    "    return r2\n",
    "\n",
    "\n",
    "def _cosine_distance(a, b, data_is_normalized=False):\n",
    "    \"\"\"Compute pair-wise cosine distance between points in `a` and `b`.\n",
    "    Parameters\n",
    "    ----------\n",
    "    a : array_like\n",
    "        An NxM matrix of N samples of dimensionality M.\n",
    "    b : array_like\n",
    "        An LxM matrix of L samples of dimensionality M.\n",
    "    data_is_normalized : Optional[bool]\n",
    "        If True, assumes rows in a and b are unit length vectors.\n",
    "        Otherwise, a and b are explicitly normalized to lenght 1.\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        Returns a matrix of size len(a), len(b) such that eleement (i, j)\n",
    "        contains the squared distance between `a[i]` and `b[j]`.\n",
    "    \"\"\"\n",
    "    if not data_is_normalized:\n",
    "        a = np.asarray(a) / np.linalg.norm(a, axis=1, keepdims=True)\n",
    "        b = np.asarray(b) / np.linalg.norm(b, axis=1, keepdims=True)\n",
    "    return 1. - np.dot(a, b.T)\n",
    "\n",
    "\n",
    "def _nn_euclidean_distance(x, y):\n",
    "    \"\"\" Helper function for nearest neighbor distance metric (Euclidean).\n",
    "    Parameters\n",
    "    ----------\n",
    "    x : ndarray\n",
    "        A matrix of N row-vectors (sample points).\n",
    "    y : ndarray\n",
    "        A matrix of M row-vectors (query points).\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        A vector of length M that contains for each entry in `y` the\n",
    "        smallest Euclidean distance to a sample in `x`.\n",
    "    \"\"\"\n",
    "    distances = _pdist(x, y)\n",
    "    return np.maximum(0.0, distances.min(axis=0))\n",
    "\n",
    "\n",
    "def _nn_cosine_distance(x, y):\n",
    "    \"\"\" Helper function for nearest neighbor distance metric (cosine).\n",
    "    Parameters\n",
    "    ----------\n",
    "    x : ndarray\n",
    "        A matrix of N row-vectors (sample points).\n",
    "    y : ndarray\n",
    "        A matrix of M row-vectors (query points).\n",
    "    Returns\n",
    "    -------\n",
    "    ndarray\n",
    "        A vector of length M that contains for each entry in `y` the\n",
    "        smallest cosine distance to a sample in `x`.\n",
    "    \"\"\"\n",
    "    distances = _cosine_distance(x, y)\n",
    "    return distances.min(axis=0)\n",
    "\n",
    "\n",
    "class NearestNeighborDistanceMetric(object):\n",
    "    \"\"\"\n",
    "    A nearest neighbor distance metric that, for each target, returns\n",
    "    the closest distance to any sample that has been observed so far.\n",
    "    Parameters\n",
    "    ----------\n",
    "    metric : str\n",
    "        Either \"euclidean\" or \"cosine\".\n",
    "    matching_threshold: float\n",
    "        The matching threshold. Samples with larger distance are considered an\n",
    "        invalid match.\n",
    "    budget : Optional[int]\n",
    "        If not None, fix samples per class to at most this number. Removes\n",
    "        the oldest samples when the budget is reached.\n",
    "    Attributes\n",
    "    ----------\n",
    "    samples : Dict[int -> List[ndarray]]\n",
    "        A dictionary that maps from target identities to the list of samples\n",
    "        that have been observed so far.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, metric, matching_threshold, budget=None):\n",
    "\n",
    "\n",
    "        if metric == \"euclidean\":\n",
    "            self._metric = _nn_euclidean_distance\n",
    "        elif metric == \"cosine\":\n",
    "            self._metric = _nn_cosine_distance\n",
    "        else:\n",
    "            raise ValueError(\n",
    "                \"Invalid metric; must be either 'euclidean' or 'cosine'\")\n",
    "        self.matching_threshold = matching_threshold\n",
    "        self.budget = budget\n",
    "        self.samples = {}\n",
    "\n",
    "    def partial_fit(self, features, targets, active_targets):\n",
    "        \"\"\"Update the distance metric with new data.\n",
    "        Parameters\n",
    "        ----------\n",
    "        features : ndarray\n",
    "            An NxM matrix of N features of dimensionality M.\n",
    "        targets : ndarray\n",
    "            An integer array of associated target identities.\n",
    "        active_targets : List[int]\n",
    "            A list of targets that are currently present in the scene.\n",
    "        \"\"\"\n",
    "        for feature, target in zip(features, targets):\n",
    "            self.samples.setdefault(target, []).append(feature)\n",
    "            if self.budget is not None:\n",
    "                self.samples[target] = self.samples[target][-self.budget:]\n",
    "        self.samples = {k: self.samples[k] for k in active_targets}\n",
    "\n",
    "    def distance(self, features, targets):\n",
    "        \"\"\"Compute distance between features and targets.\n",
    "        Parameters\n",
    "        ----------\n",
    "        features : ndarray\n",
    "            An NxM matrix of N features of dimensionality M.\n",
    "        targets : List[int]\n",
    "            A list of targets to match the given `features` against.\n",
    "        Returns\n",
    "        -------\n",
    "        ndarray\n",
    "            Returns a cost matrix of shape len(targets), len(features), where\n",
    "            element (i, j) contains the closest squared distance between\n",
    "            `targets[i]` and `features[j]`.\n",
    "        \"\"\"\n",
    "        cost_matrix = np.zeros((len(targets), len(features)))\n",
    "        for i, target in enumerate(targets):\n",
    "            cost_matrix[i, :] = self._metric(self.samples[target], features)\n",
    "        return cost_matrix"
   ]
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    "class TrackState:\n",
    "    \"\"\"\n",
    "    Enumeration type for the single target track state. Newly created tracks are\n",
    "    classified as `tentative` until enough evidence has been collected. Then,\n",
    "    the track state is changed to `confirmed`. Tracks that are no longer alive\n",
    "    are classified as `deleted` to mark them for removal from the set of active\n",
    "    tracks.\n",
    "    \"\"\"\n",
    "\n",
    "    Tentative = 1\n",
    "    Confirmed = 2\n",
    "    Deleted = 3\n",
    "\n",
    "\n",
    "class Track:\n",
    "    \"\"\"\n",
    "    A single target track with state space `(x, y, a, h)` and associated\n",
    "    velocities, where `(x, y)` is the center of the bounding box, `a` is the\n",
    "    aspect ratio and `h` is the height.\n",
    "    Parameters\n",
    "    ----------\n",
    "    mean : ndarray\n",
    "        Mean vector of the initial state distribution.\n",
    "    covariance : ndarray\n",
    "        Covariance matrix of the initial state distribution.\n",
    "    track_id : int\n",
    "        A unique track identifier.\n",
    "    n_init : int\n",
    "        Number of consecutive detections before the track is confirmed. The\n",
    "        track state is set to `Deleted` if a miss occurs within the first\n",
    "        `n_init` frames.\n",
    "    max_age : int\n",
    "        The maximum number of consecutive misses before the track state is\n",
    "        set to `Deleted`.\n",
    "    feature : Optional[ndarray]\n",
    "        Feature vector of the detection this track originates from. If not None,\n",
    "        this feature is added to the `features` cache.\n",
    "    Attributes\n",
    "    ----------\n",
    "    mean : ndarray\n",
    "        Mean vector of the initial state distribution.\n",
    "    covariance : ndarray\n",
    "        Covariance matrix of the initial state distribution.\n",
    "    track_id : int\n",
    "        A unique track identifier.\n",
    "    hits : int\n",
    "        Total number of measurement updates.\n",
    "    age : int\n",
    "        Total number of frames since first occurance.\n",
    "    time_since_update : int\n",
    "        Total number of frames since last measurement update.\n",
    "    state : TrackState\n",
    "        The current track state.\n",
    "    features : List[ndarray]\n",
    "        A cache of features. On each measurement update, the associated feature\n",
    "        vector is added to this list.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, mean, covariance, track_id, n_init, max_age,\n",
    "                 feature=None, class_name=None):\n",
    "        self.mean = mean\n",
    "        self.covariance = covariance\n",
    "        self.track_id = track_id\n",
    "        self.hits = 1\n",
    "        self.age = 1\n",
    "        self.time_since_update = 0\n",
    "\n",
    "        self.state = TrackState.Tentative\n",
    "        self.features = []\n",
    "        if feature is not None:\n",
    "            self.features.append(feature)\n",
    "\n",
    "        self._n_init = n_init\n",
    "        self._max_age = max_age\n",
    "        self.class_name = class_name\n",
    "\n",
    "    def to_tlwh(self):\n",
    "        \"\"\"Get current position in bounding box format `(top left x, top left y,\n",
    "        width, height)`.\n",
    "        Returns\n",
    "        -------\n",
    "        ndarray\n",
    "            The bounding box.\n",
    "        \"\"\"\n",
    "        ret = self.mean[:4].copy()\n",
    "        ret[2] *= ret[3]\n",
    "        ret[:2] -= ret[2:] / 2\n",
    "        return ret\n",
    "\n",
    "    def to_tlbr(self):\n",
    "        \"\"\"Get current position in bounding box format `(min x, miny, max x,\n",
    "        max y)`.\n",
    "        Returns\n",
    "        -------\n",
    "        ndarray\n",
    "            The bounding box.\n",
    "        \"\"\"\n",
    "        ret = self.to_tlwh()\n",
    "        ret[2:] = ret[:2] + ret[2:]\n",
    "        return ret\n",
    "    \n",
    "    def get_class(self):\n",
    "        return self.class_name\n",
    "\n",
    "    def predict(self, kf):\n",
    "        \"\"\"Propagate the state distribution to the current time step using a\n",
    "        Kalman filter prediction step.\n",
    "        Parameters\n",
    "        ----------\n",
    "        kf : kalman_filter.KalmanFilter\n",
    "            The Kalman filter.\n",
    "        \"\"\"\n",
    "        self.mean, self.covariance = kf.predict(self.mean, self.covariance)\n",
    "        self.age += 1\n",
    "        self.time_since_update += 1\n",
    "\n",
    "    def update(self, kf, detection):\n",
    "        \"\"\"Perform Kalman filter measurement update step and update the feature\n",
    "        cache.\n",
    "        Parameters\n",
    "        ----------\n",
    "        kf : kalman_filter.KalmanFilter\n",
    "            The Kalman filter.\n",
    "        detection : Detection\n",
    "            The associated detection.\n",
    "        \"\"\"\n",
    "        self.mean, self.covariance = kf.update(\n",
    "            self.mean, self.covariance, detection.to_xyah())\n",
    "        self.features.append(detection.feature)\n",
    "\n",
    "        self.hits += 1\n",
    "        self.time_since_update = 0\n",
    "        if self.state == TrackState.Tentative and self.hits >= self._n_init:\n",
    "            self.state = TrackState.Confirmed\n",
    "\n",
    "    def mark_missed(self):\n",
    "        \"\"\"Mark this track as missed (no association at the current time step).\n",
    "        \"\"\"\n",
    "        if self.state == TrackState.Tentative:\n",
    "            self.state = TrackState.Deleted\n",
    "        elif self.time_since_update > self._max_age:\n",
    "            self.state = TrackState.Deleted\n",
    "\n",
    "    def is_tentative(self):\n",
    "        \"\"\"Returns True if this track is tentative (unconfirmed).\n",
    "        \"\"\"\n",
    "        return self.state == TrackState.Tentative\n",
    "\n",
    "    def is_confirmed(self):\n",
    "        \"\"\"Returns True if this track is confirmed.\"\"\"\n",
    "        return self.state == TrackState.Confirmed\n",
    "\n",
    "    def is_deleted(self):\n",
    "        \"\"\"Returns True if this track is dead and should be deleted.\"\"\"\n",
    "        return self.state == TrackState.Deleted"
   ]
  },
  {
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    "class Tracker:\n",
    "    \"\"\"\n",
    "    This is the multi-target tracker.\n",
    "    Parameters\n",
    "    ----------\n",
    "    metric : nn_matching.NearestNeighborDistanceMetric\n",
    "        A distance metric for measurement-to-track association.\n",
    "    max_age : int\n",
    "        Maximum number of missed misses before a track is deleted.\n",
    "    n_init : int\n",
    "        Number of consecutive detections before the track is confirmed. The\n",
    "        track state is set to `Deleted` if a miss occurs within the first\n",
    "        `n_init` frames.\n",
    "    Attributes\n",
    "    ----------\n",
    "    metric : nn_matching.NearestNeighborDistanceMetric\n",
    "        The distance metric used for measurement to track association.\n",
    "    max_age : int\n",
    "        Maximum number of missed misses before a track is deleted.\n",
    "    n_init : int\n",
    "        Number of frames that a track remains in initialization phase.\n",
    "    kf : kalman_filter.KalmanFilter\n",
    "        A Kalman filter to filter target trajectories in image space.\n",
    "    tracks : List[Track]\n",
    "        The list of active tracks at the current time step.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, metric, max_iou_distance=0.7, max_age=30, n_init=3):\n",
    "        self.metric = metric\n",
    "        self.max_iou_distance = max_iou_distance\n",
    "        self.max_age = max_age\n",
    "        self.n_init = n_init\n",
    "\n",
    "        self.kf = KalmanFilter()\n",
    "        self.tracks = []\n",
    "        self._next_id = 1\n",
    "\n",
    "    def predict(self):\n",
    "        \"\"\"Propagate track state distributions one time step forward.\n",
    "        This function should be called once every time step, before `update`.\n",
    "        \"\"\"\n",
    "        for track in self.tracks:\n",
    "            track.predict(self.kf)\n",
    "\n",
    "    def update(self, detections):\n",
    "        \"\"\"Perform measurement update and track management.\n",
    "        Parameters\n",
    "        ----------\n",
    "        detections : List[deep_sort.detection.Detection]\n",
    "            A list of detections at the current time step.\n",
    "        \"\"\"\n",
    "        # Run matching cascade.\n",
    "        matches, unmatched_tracks, unmatched_detections = \\\n",
    "            self._match(detections)\n",
    "\n",
    "        # Update track set.\n",
    "        for track_idx, detection_idx in matches:\n",
    "            self.tracks[track_idx].update(\n",
    "                self.kf, detections[detection_idx])\n",
    "        for track_idx in unmatched_tracks:\n",
    "            self.tracks[track_idx].mark_missed()\n",
    "        for detection_idx in unmatched_detections:\n",
    "            self._initiate_track(detections[detection_idx])\n",
    "        self.tracks = [t for t in self.tracks if not t.is_deleted()]\n",
    "\n",
    "        # Update distance metric.\n",
    "        active_targets = [t.track_id for t in self.tracks if t.is_confirmed()]\n",
    "        features, targets = [], []\n",
    "        for track in self.tracks:\n",
    "            if not track.is_confirmed():\n",
    "                continue\n",
    "            features += track.features\n",
    "            targets += [track.track_id for _ in track.features]\n",
    "            track.features = []\n",
    "        self.metric.partial_fit(\n",
    "            np.asarray(features), np.asarray(targets), active_targets)\n",
    "\n",
    "    def _match(self, detections):\n",
    "\n",
    "        def gated_metric(tracks, dets, track_indices, detection_indices):\n",
    "            features = np.array([dets[i].feature for i in detection_indices])\n",
    "            targets = np.array([tracks[i].track_id for i in track_indices])\n",
    "            cost_matrix = self.metric.distance(features, targets)\n",
    "            cost_matrix = gate_cost_matrix(\n",
    "                self.kf, cost_matrix, tracks, dets, track_indices,\n",
    "                detection_indices)\n",
    "\n",
    "            return cost_matrix\n",
    "\n",
    "        # Split track set into confirmed and unconfirmed tracks.\n",
    "        confirmed_tracks = [\n",
    "            i for i, t in enumerate(self.tracks) if t.is_confirmed()]\n",
    "        unconfirmed_tracks = [\n",
    "            i for i, t in enumerate(self.tracks) if not t.is_confirmed()]\n",
    "\n",
    "        # Associate confirmed tracks using appearance features.\n",
    "        matches_a, unmatched_tracks_a, unmatched_detections = \\\n",
    "                matching_cascade(\n",
    "                gated_metric, self.metric.matching_threshold, self.max_age,\n",
    "                self.tracks, detections, confirmed_tracks)\n",
    "\n",
    "        # Associate remaining tracks together with unconfirmed tracks using IOU.\n",
    "        iou_track_candidates = unconfirmed_tracks + [\n",
    "            k for k in unmatched_tracks_a if\n",
    "            self.tracks[k].time_since_update == 1]\n",
    "        unmatched_tracks_a = [\n",
    "            k for k in unmatched_tracks_a if\n",
    "            self.tracks[k].time_since_update != 1]\n",
    "        matches_b, unmatched_tracks_b, unmatched_detections = \\\n",
    "                min_cost_matching(\n",
    "                iou_cost, self.max_iou_distance, self.tracks,\n",
    "                detections, iou_track_candidates, unmatched_detections)\n",
    "\n",
    "        matches = matches_a + matches_b\n",
    "        unmatched_tracks = list(set(unmatched_tracks_a + unmatched_tracks_b))\n",
    "        return matches, unmatched_tracks, unmatched_detections\n",
    "\n",
    "    def _initiate_track(self, detection):\n",
    "        mean, covariance = self.kf.initiate(detection.to_xyah())\n",
    "        class_name = detection.get_class()\n",
    "        self.tracks.append(Track(\n",
    "            mean, covariance, self._next_id, self.n_init, self.max_age,\n",
    "            detection.feature, class_name))\n",
    "        self._next_id += 1"
   ]
  },
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    "# Definition of the parameters\n",
    "max_cosine_distance = 0.7\n",
    "max_euclidean_distance = 0.7\n",
    "nn_budget = None\n",
    "model_filename = 'mars-small128.pb'\n",
    "\n",
    "key_list = list(NUM_CLASS.keys()) \n",
    "val_list = list(NUM_CLASS.values()) "
   ]
  },
  {
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   "source": [
    "import time\n",
    "\n",
    "# Function for object tracking on video\n",
    "def object_tracking(video_path, output_path):\n",
    "    encoder = create_box_encoder(model_filename, batch_size=1)\n",
    "    metric = NearestNeighborDistanceMetric(\"cosine\", max_cosine_distance, nn_budget)\n",
    "    tracker = Tracker(metric)\n",
    "    \n",
    "    times, times_2 = [], []\n",
    "    vid = cv2.VideoCapture(video_path) # detect on video\n",
    "\n",
    "    # by default VideoCapture returns float instead of int\n",
    "    width = int(vid.get(cv2.CAP_PROP_FRAME_WIDTH))\n",
    "    height = int(vid.get(cv2.CAP_PROP_FRAME_HEIGHT))\n",
    "    fps = int(vid.get(cv2.CAP_PROP_FPS))\n",
    "    codec = cv2.VideoWriter_fourcc(*'XVID')\n",
    "    out = cv2.VideoWriter(output_path, codec, fps, (width, height)) # output_path must be .mp4\n",
    "    \n",
    "    while True:\n",
    "        _, frame = vid.read()\n",
    "\n",
    "        try:\n",
    "            original_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n",
    "            original_frame = cv2.cvtColor(original_frame, cv2.COLOR_BGR2RGB)\n",
    "        except:\n",
    "            break\n",
    "\n",
    "        # Load picture with old dimensions\n",
    "        image_data, image_w, image_h = image_preprocess(np.copy(original_frame), (WIDTH, HEIGHT))\n",
    "\n",
    "        # Predict Image\n",
    "        t1 = time.time()\n",
    "        yhat = model.predict(image_data)\n",
    "\n",
    "        # Create boxes\n",
    "        boxes = list()\n",
    "        for i in range(len(yhat)):\n",
    "            boxes += decode_netout(yhat[i][0], anchors[i], class_threshold, HEIGHT, WIDTH)\n",
    "\n",
    "        # Correct the sizes of boxes for shape of image\n",
    "        correct_yolo_boxes(boxes, image_h, image_w, HEIGHT, WIDTH)\n",
    "\n",
    "        # Suppress Non Maximal Boxes\n",
    "        do_nms(boxes, 0.3)\n",
    "\n",
    "        # define the labels (Filtered only the ones relevant for this task, which were used in pretraining the YOLOv3 model)\n",
    "        labels = [\"person\", \"bicycle\", \"car\", \"motorbike\", \"aeroplane\", \"bus\", \"train\", \"truck\",\"boat\"]\n",
    "\n",
    "        # get the details of the detected objects\n",
    "        v_boxes, v_labels, v_scores = get_boxes(boxes, labels, class_threshold)\n",
    "\n",
    "\n",
    "        #t1 = time.time()\n",
    "        #pred_bbox = Yolo.predict(image_data)\n",
    "        t2 = time.time()\n",
    "\n",
    "        # Obtain all the detections for the given frame\n",
    "        boxes = []\n",
    "        names = []\n",
    "        scores = []\n",
    "        for box, label, score in zip(v_boxes, v_labels, v_scores):\n",
    "            boxes.append([\n",
    "                 box.xmin, box.ymin, \n",
    "                (box.xmax - box.xmin), (box.ymax - box.ymin) * 2])\n",
    "            names.append(label)\n",
    "            scores.append(score)\n",
    "\n",
    "        boxes = np.array(boxes) \n",
    "        names = np.array(names)\n",
    "        scores = np.array(scores)\n",
    "        features = np.array(encoder(original_frame, boxes))\n",
    "        detections = [Detection(bbox, score, class_name, feature) for bbox, score, class_name, feature in zip(boxes, scores, names, features)]\n",
    "\n",
    "        # Pass detections to the deepsort object and obtain the track information.\n",
    "        tracker.predict()\n",
    "        tracker.update(detections)\n",
    "\n",
    "        # Obtain info from the tracks\n",
    "        tracked_bboxes = []\n",
    "        for track in tracker.tracks:\n",
    "            if not track.is_confirmed() or track.time_since_update > 5:\n",
    "                continue \n",
    "            bbox = track.to_tlbr() # Get the corrected/predicted bounding box\n",
    "            class_name = track.get_class() #Get the class name of particular object\n",
    "            tracking_id = track.track_id # Get the ID for the particular track\n",
    "            index = key_list[val_list.index(class_name)] # Get predicted object index by object name\n",
    "            tracked_bboxes.append(bbox.tolist() + [tracking_id, index]) # Structure data, that we could use it with our draw_bbox function\n",
    "\n",
    "        # draw detection on frame\n",
    "        image = draw_bbox(original_frame, tracked_bboxes, CLASSES=NUM_CLASS, tracking=True)\n",
    "\n",
    "        t3 = time.time()\n",
    "        times.append(t2-t1)\n",
    "        times_2.append(t3-t1)\n",
    "\n",
    "        times = times[-20:]\n",
    "        times_2 = times_2[-20:]\n",
    "\n",
    "        ms = sum(times)/len(times)*1000\n",
    "        fps = 1000 / ms\n",
    "        fps2 = 1000 / (sum(times_2)/len(times_2)*1000)\n",
    "\n",
    "        image = cv2.putText(image, \"Time: {:.1f} FPS\".format(fps), (0, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 0, 255), 2)\n",
    "\n",
    "        # draw original yolo detection\n",
    "        #image = draw_bbox(image, bboxes, CLASSES=CLASSES, show_label=False, rectangle_colors=rectangle_colors, tracking=True)\n",
    "\n",
    "        print(\"Time: {:.2f}ms, Detection FPS: {:.1f}, total FPS: {:.1f}\".format(ms, fps, fps2))\n",
    "        out.write(image)\n",
    "\n",
    "    out.release()\n",
    "    vid.release()"
   ]
  },
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    {
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     "text": [
      "Processing video challenge.mp4\n",
      "1/1 [==============================] - 2s 2s/step\n",
      "Time: 7780.89ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 6608.51ms, Detection FPS: 0.2, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 562ms/step\n",
      "Time: 6022.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 565ms/step\n",
      "Time: 5925.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 5990.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 675ms/step\n",
      "Time: 6235.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 702ms/step\n",
      "Time: 6287.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 588ms/step\n",
      "Time: 6306.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 601ms/step\n",
      "Time: 6245.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 535ms/step\n",
      "Time: 6186.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 544ms/step\n",
      "Time: 6057.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 541ms/step\n",
      "Time: 6210.79ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 1s/step\n",
      "Time: 6443.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 649ms/step\n",
      "Time: 6435.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 649ms/step\n",
      "Time: 6363.37ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 663ms/step\n",
      "Time: 6311.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 566ms/step\n",
      "Time: 6378.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 1s/step\n",
      "Time: 6525.50ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 562ms/step\n",
      "Time: 6450.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 559ms/step\n",
      "Time: 6366.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 562ms/step\n",
      "Time: 6228.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 533ms/step\n",
      "Time: 6200.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 529ms/step\n",
      "Time: 6188.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 525ms/step\n",
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      "1/1 [==============================] - 1s 521ms/step\n",
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      "1/1 [==============================] - 1s 566ms/step\n",
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      "1/1 [==============================] - 1s 737ms/step\n",
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      "1/1 [==============================] - 1s 767ms/step\n",
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      "1/1 [==============================] - 1s 536ms/step\n",
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      "1/1 [==============================] - 1s 574ms/step\n",
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      "1/1 [==============================] - 1s 514ms/step\n",
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      "1/1 [==============================] - 1s 574ms/step\n",
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      "1/1 [==============================] - 1s 730ms/step\n",
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      "1/1 [==============================] - 1s 767ms/step\n",
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      "1/1 [==============================] - 1s 533ms/step\n",
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      "1/1 [==============================] - 1s 525ms/step\n",
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      "1/1 [==============================] - 1s 520ms/step\n",
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      "1/1 [==============================] - 1s 541ms/step\n",
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      "1/1 [==============================] - 1s 529ms/step\n",
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      "1/1 [==============================] - 1s 527ms/step\n",
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      "1/1 [==============================] - 1s 525ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 512ms/step\n",
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      "1/1 [==============================] - 1s 727ms/step\n",
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      "1/1 [==============================] - 1s 777ms/step\n",
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      "1/1 [==============================] - 1s 546ms/step\n",
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      "1/1 [==============================] - 1s 554ms/step\n",
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      "1/1 [==============================] - 1s 915ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 545ms/step\n",
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      "1/1 [==============================] - 1s 539ms/step\n",
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      "1/1 [==============================] - 1s 517ms/step\n",
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      "1/1 [==============================] - 1s 541ms/step\n",
      "Time: 5411.05ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 527ms/step\n",
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      "1/1 [==============================] - 1s 538ms/step\n",
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      "1/1 [==============================] - 1s 523ms/step\n",
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      "1/1 [==============================] - 1s 539ms/step\n",
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      "1/1 [==============================] - 1s 553ms/step\n",
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      "1/1 [==============================] - 1s 535ms/step\n",
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      "1/1 [==============================] - 1s 556ms/step\n",
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      "1/1 [==============================] - 1s 804ms/step\n",
      "Time: 5603.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 775ms/step\n",
      "Time: 5651.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 593ms/step\n",
      "Time: 5630.09ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 561ms/step\n",
      "Time: 5591.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 857ms/step\n",
      "Time: 5773.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 570ms/step\n",
      "Time: 5811.05ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 599ms/step\n",
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      "1/1 [==============================] - 1s 716ms/step\n",
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      "1/1 [==============================] - 1s 796ms/step\n",
      "Time: 5744.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 529ms/step\n",
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      "1/1 [==============================] - 1s 581ms/step\n",
      "Time: 5839.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 866ms/step\n",
      "Time: 5971.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 582ms/step\n",
      "Time: 5979.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 558ms/step\n",
      "Time: 5952.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 542ms/step\n",
      "Time: 5955.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 554ms/step\n",
      "Time: 5983.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 577ms/step\n",
      "Time: 6051.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
      "Time: 6102.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 6129.47ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 556ms/step\n",
      "Time: 6074.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 552ms/step\n",
      "Time: 5875.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 555ms/step\n",
      "Time: 5867.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 522ms/step\n",
      "Time: 5955.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 758ms/step\n",
      "Time: 5989.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 5812.96ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 518ms/step\n",
      "Time: 5802.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 685ms/step\n",
      "Time: 5954.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 894ms/step\n",
      "Time: 5858.23ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 539ms/step\n",
      "Time: 5793.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 536ms/step\n",
      "Time: 5829.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 525ms/step\n",
      "Time: 5723.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 688ms/step\n",
      "Time: 5617.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 541ms/step\n",
      "Time: 5591.82ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 516ms/step\n",
      "Time: 5604.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 509ms/step\n",
      "Time: 5602.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 513ms/step\n",
      "Time: 5560.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 526ms/step\n",
      "Time: 5506.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 657ms/step\n",
      "Time: 5475.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 607ms/step\n",
      "Time: 5471.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 564ms/step\n",
      "Time: 5591.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 1s/step\n",
      "Time: 5905.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 1s/step\n",
      "Time: 6079.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 809ms/step\n",
      "Time: 6178.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 765ms/step\n",
      "Time: 6179.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 885ms/step\n",
      "Time: 6347.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 794ms/step\n",
      "Time: 6480.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 753ms/step\n",
      "Time: 6495.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 882ms/step\n",
      "Time: 6610.09ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 862ms/step\n",
      "Time: 6790.86ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 726ms/step\n",
      "Time: 6816.54ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 511ms/step\n",
      "Time: 6799.40ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 520ms/step\n",
      "Time: 6786.20ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 522ms/step\n",
      "Time: 6812.14ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 527ms/step\n",
      "Time: 6803.21ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 536ms/step\n",
      "Time: 6812.19ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 528ms/step\n",
      "Time: 6804.59ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 528ms/step\n",
      "Time: 6789.60ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 587ms/step\n",
      "Time: 6795.70ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 519ms/step\n",
      "Time: 6787.14ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 544ms/step\n",
      "Time: 6644.40ms, Detection FPS: 0.2, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 527ms/step\n",
      "Time: 6343.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 561ms/step\n",
      "Time: 6139.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 541ms/step\n",
      "Time: 5935.78ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 537ms/step\n",
      "Time: 5789.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 524ms/step\n",
      "Time: 5625.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 554ms/step\n",
      "Time: 5474.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 539ms/step\n",
      "Time: 5350.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 522ms/step\n",
      "Time: 5318.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 784ms/step\n",
      "Time: 5244.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 549ms/step\n",
      "Time: 5185.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 545ms/step\n",
      "Time: 5232.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 918ms/step\n",
      "Time: 5415.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 910ms/step\n",
      "Time: 5443.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 533ms/step\n",
      "Time: 5464.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 543ms/step\n",
      "Time: 5482.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 516ms/step\n",
      "Time: 5493.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 534ms/step\n",
      "Time: 5497.37ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 549ms/step\n",
      "Time: 5503.96ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 543ms/step\n",
      "Time: 5487.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 521ms/step\n",
      "Time: 5487.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 530ms/step\n",
      "Time: 5476.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 532ms/step\n",
      "Time: 5488.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5539.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 557ms/step\n",
      "Time: 5628.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 791ms/step\n",
      "Time: 5794.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 705ms/step\n",
      "Time: 5773.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 542ms/step\n",
      "Time: 5752.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 819ms/step\n",
      "Time: 5793.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 816ms/step\n",
      "Time: 5732.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 531ms/step\n",
      "Time: 5768.16ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 530ms/step\n",
      "Time: 5710.06ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 518ms/step\n",
      "Time: 5541.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 548ms/step\n",
      "Time: 5509.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 526ms/step\n",
      "Time: 5483.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 523ms/step\n",
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      "1/1 [==============================] - 1s 563ms/step\n",
      "Time: 5465.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 531ms/step\n",
      "Time: 5467.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 530ms/step\n",
      "Time: 5465.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 526ms/step\n",
      "Time: 5472.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 534ms/step\n",
      "Time: 5634.12ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 925ms/step\n",
      "Time: 5776.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 534ms/step\n",
      "Time: 5790.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 546ms/step\n",
      "Time: 5733.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 546ms/step\n",
      "Time: 5617.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 534ms/step\n",
      "Time: 5479.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 894ms/step\n",
      "Time: 5674.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 749ms/step\n",
      "Time: 5724.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 537ms/step\n",
      "Time: 5521.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 531ms/step\n",
      "Time: 5615.23ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 931ms/step\n",
      "Time: 5730.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 589ms/step\n",
      "Time: 5745.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 518ms/step\n",
      "Time: 5718.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 570ms/step\n",
      "Time: 5725.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 532ms/step\n",
      "Time: 5733.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 534ms/step\n",
      "Time: 5747.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 552ms/step\n",
      "Time: 5723.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 532ms/step\n",
      "Time: 5741.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 531ms/step\n",
      "Time: 5707.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 522ms/step\n",
      "Time: 5701.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 546ms/step\n",
      "Time: 5540.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 518ms/step\n",
      "Time: 5416.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 531ms/step\n",
      "Time: 5366.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 540ms/step\n",
      "Time: 5366.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 543ms/step\n",
      "Time: 5506.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 753ms/step\n",
      "Time: 5677.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
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      "1/1 [==============================] - 1s 518ms/step\n",
      "Time: 5779.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
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      "1/1 [==============================] - 1s 533ms/step\n",
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      "1/1 [==============================] - 1s 520ms/step\n",
      "Time: 5420.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "Processing video challenge_video.mp4\n",
      "1/1 [==============================] - 1s 533ms/step\n",
      "Time: 5431.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 553ms/step\n",
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      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 4988.33ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4999.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
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      "1/1 [==============================] - 1s 605ms/step\n",
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      "1/1 [==============================] - 1s 597ms/step\n",
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      "1/1 [==============================] - 1s 610ms/step\n",
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      "1/1 [==============================] - 1s 606ms/step\n",
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      "1/1 [==============================] - 1s 590ms/step\n",
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      "1/1 [==============================] - 1s 602ms/step\n",
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      "1/1 [==============================] - 1s 597ms/step\n",
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      "1/1 [==============================] - 1s 612ms/step\n",
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      "1/1 [==============================] - 1s 595ms/step\n",
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      "1/1 [==============================] - 1s 642ms/step\n",
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      "1/1 [==============================] - 1s 591ms/step\n",
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      "1/1 [==============================] - 1s 605ms/step\n",
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      "1/1 [==============================] - 1s 604ms/step\n",
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      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 608ms/step\n",
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      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4956.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 594ms/step\n",
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      "1/1 [==============================] - 1s 595ms/step\n",
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      "1/1 [==============================] - 1s 602ms/step\n",
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      "1/1 [==============================] - 1s 600ms/step\n",
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      "1/1 [==============================] - 1s 634ms/step\n",
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      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4955.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 607ms/step\n",
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      "1/1 [==============================] - 1s 633ms/step\n",
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      "1/1 [==============================] - 1s 603ms/step\n",
      "Time: 4958.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 604ms/step\n",
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      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 4955.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4964.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 4964.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 597ms/step\n",
      "Time: 4970.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4979.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 4988.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 594ms/step\n",
      "Time: 5000.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5001.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 597ms/step\n",
      "Time: 4997.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 597ms/step\n",
      "Time: 5007.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 5008.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5009.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 5012.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5004.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 5014.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 5018.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 5025.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 596ms/step\n",
      "Time: 5034.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 5028.59ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 5037.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5046.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5037.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 5038.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 5037.27ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5044.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5046.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 639ms/step\n",
      "Time: 5045.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
      "Time: 5051.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 5075.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 5079.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 668ms/step\n",
      "Time: 5091.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 5093.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 648ms/step\n",
      "Time: 5103.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5109.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 612ms/step\n",
      "Time: 5105.50ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 609ms/step\n",
      "Time: 5109.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5108.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5110.50ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 609ms/step\n",
      "Time: 5117.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 5115.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 5119.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 600ms/step\n",
      "Time: 5125.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 5121.26ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 5122.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5117.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5109.09ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 5108.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 5111.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 5091.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 5086.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5076.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 5085.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 5077.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 5071.32ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5069.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 5064.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 664ms/step\n",
      "Time: 5069.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 5081.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 5082.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 5080.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5082.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 5084.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 700ms/step\n",
      "Time: 5100.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 5118.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 5120.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 5137.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5131.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 596ms/step\n",
      "Time: 5167.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 722ms/step\n",
      "Time: 5211.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 740ms/step\n",
      "Time: 5226.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 707ms/step\n",
      "Time: 5238.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 703ms/step\n",
      "Time: 5248.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 5261.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 5279.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5284.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 5281.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 664ms/step\n",
      "Time: 5286.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 5280.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5277.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
      "Time: 5283.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5279.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
      "Time: 5285.94ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 607ms/step\n",
      "Time: 5281.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 5262.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 5264.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 5242.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 5254.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5223.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5183.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5174.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 5169.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5148.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 5139.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 5130.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 5121.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 646ms/step\n",
      "Time: 5130.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 5126.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 5124.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5131.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 5127.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 5128.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 5117.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 5108.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 5113.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 5108.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 5128.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5135.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 5135.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 5138.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 5139.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 658ms/step\n",
      "Time: 5135.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5143.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 5147.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5154.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 612ms/step\n",
      "Time: 5159.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 5158.06ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 5154.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 5148.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 5146.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 5156.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 5163.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 5172.54ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 5178.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 5176.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 5175.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
      "Time: 5167.12ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 5162.32ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 5163.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 648ms/step\n",
      "Time: 5160.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 656ms/step\n",
      "Time: 5161.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 5158.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 5158.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 609ms/step\n",
      "Time: 5147.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
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      "1/1 [==============================] - 1s 623ms/step\n",
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      "1/1 [==============================] - 1s 612ms/step\n",
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      "1/1 [==============================] - 1s 638ms/step\n",
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      "1/1 [==============================] - 1s 626ms/step\n",
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      "1/1 [==============================] - 1s 622ms/step\n",
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      "1/1 [==============================] - 1s 630ms/step\n",
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      "1/1 [==============================] - 1s 629ms/step\n",
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      "1/1 [==============================] - 1s 616ms/step\n",
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      "1/1 [==============================] - 1s 651ms/step\n",
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      "1/1 [==============================] - 1s 638ms/step\n",
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      "1/1 [==============================] - 1s 639ms/step\n",
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      "1/1 [==============================] - 1s 618ms/step\n",
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      "1/1 [==============================] - 1s 632ms/step\n",
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      "1/1 [==============================] - 1s 643ms/step\n",
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      "1/1 [==============================] - 1s 612ms/step\n",
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      "1/1 [==============================] - 1s 615ms/step\n",
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      "1/1 [==============================] - 1s 612ms/step\n",
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      "1/1 [==============================] - 1s 632ms/step\n",
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      "1/1 [==============================] - 1s 616ms/step\n",
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      "1/1 [==============================] - 1s 627ms/step\n",
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      "1/1 [==============================] - 1s 664ms/step\n",
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      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 646ms/step\n",
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      "1/1 [==============================] - 1s 623ms/step\n",
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      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 637ms/step\n",
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      "1/1 [==============================] - 1s 630ms/step\n",
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      "1/1 [==============================] - 1s 614ms/step\n",
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      "1/1 [==============================] - 1s 649ms/step\n",
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      "1/1 [==============================] - 1s 636ms/step\n",
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      "1/1 [==============================] - 1s 619ms/step\n",
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      "1/1 [==============================] - 1s 641ms/step\n",
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      "1/1 [==============================] - 1s 645ms/step\n",
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      "1/1 [==============================] - 1s 640ms/step\n",
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      "1/1 [==============================] - 1s 610ms/step\n",
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      "1/1 [==============================] - 1s 616ms/step\n",
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      "1/1 [==============================] - 1s 639ms/step\n",
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      "1/1 [==============================] - 1s 649ms/step\n",
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      "1/1 [==============================] - 1s 614ms/step\n",
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      "1/1 [==============================] - 1s 609ms/step\n",
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      "1/1 [==============================] - 1s 602ms/step\n",
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      "1/1 [==============================] - 1s 620ms/step\n",
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      "1/1 [==============================] - 1s 615ms/step\n",
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      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 635ms/step\n",
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      "1/1 [==============================] - 1s 625ms/step\n",
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      "1/1 [==============================] - 1s 604ms/step\n",
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      "1/1 [==============================] - 1s 621ms/step\n",
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      "1/1 [==============================] - 1s 605ms/step\n",
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      "1/1 [==============================] - 1s 609ms/step\n",
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      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 623ms/step\n",
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      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5137.06ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
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      "1/1 [==============================] - 1s 633ms/step\n",
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      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5116.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 5117.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 604ms/step\n",
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      "1/1 [==============================] - 1s 658ms/step\n",
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      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 5114.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 5118.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 5126.37ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 639ms/step\n",
      "Time: 5130.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
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      "1/1 [==============================] - 1s 608ms/step\n",
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      "1/1 [==============================] - 1s 608ms/step\n",
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      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 5137.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
      "Time: 5131.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
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      "1/1 [==============================] - 1s 641ms/step\n",
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      "1/1 [==============================] - 1s 621ms/step\n",
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      "1/1 [==============================] - 1s 617ms/step\n",
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      "1/1 [==============================] - 1s 657ms/step\n",
      "Time: 5128.82ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
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      "1/1 [==============================] - 1s 615ms/step\n",
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      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 5124.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5128.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
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      "1/1 [==============================] - 1s 613ms/step\n",
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      "1/1 [==============================] - 1s 628ms/step\n",
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      "1/1 [==============================] - 1s 627ms/step\n",
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      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5129.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 594ms/step\n",
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      "1/1 [==============================] - 1s 622ms/step\n",
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      "1/1 [==============================] - 1s 617ms/step\n",
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      "1/1 [==============================] - 1s 614ms/step\n",
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      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 644ms/step\n",
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      "1/1 [==============================] - 1s 711ms/step\n",
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      "1/1 [==============================] - 1s 707ms/step\n",
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      "1/1 [==============================] - 1s 734ms/step\n",
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      "1/1 [==============================] - 1s 806ms/step\n",
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      "1/1 [==============================] - 1s 698ms/step\n",
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      "1/1 [==============================] - 1s 811ms/step\n",
      "Time: 5364.65ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 808ms/step\n",
      "Time: 11091.86ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
      "Time: 21519.83ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 11s 11s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 11s 11s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 11s 11s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 12s 12s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "1/1 [==============================] - 9s 9s/step\n",
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      "1/1 [==============================] - 10s 10s/step\n",
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      "Time: 100105.50ms, Detection FPS: 0.0, total FPS: 0.0\n",
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      "1/1 [==============================] - 1s 919ms/step\n",
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      "1/1 [==============================] - 1s 930ms/step\n",
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      "1/1 [==============================] - 1s 919ms/step\n",
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      "1/1 [==============================] - 1s 915ms/step\n",
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      "1/1 [==============================] - 1s 947ms/step\n",
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      "1/1 [==============================] - 1s 954ms/step\n",
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      "1/1 [==============================] - 1s 631ms/step\n",
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      "1/1 [==============================] - 1s 615ms/step\n",
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      "1/1 [==============================] - 1s 509ms/step\n",
      "Time: 7434.62ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 0s 487ms/step\n",
      "Time: 7367.51ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 814ms/step\n",
      "Time: 7319.44ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 800ms/step\n",
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      "1/1 [==============================] - 1s 859ms/step\n",
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      "1/1 [==============================] - 1s 835ms/step\n",
      "Time: 7219.40ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 834ms/step\n",
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      "1/1 [==============================] - 1s 781ms/step\n",
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      "1/1 [==============================] - 1s 860ms/step\n",
      "Time: 7034.49ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "Processing video harder_challenge_video.mp4\n",
      "1/1 [==============================] - 1s 824ms/step\n",
      "Time: 7761.23ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 841ms/step\n",
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      "1/1 [==============================] - 1s 810ms/step\n",
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      "1/1 [==============================] - 1s 885ms/step\n",
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      "1/1 [==============================] - 1s 770ms/step\n",
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      "1/1 [==============================] - 1s 848ms/step\n",
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      "1/1 [==============================] - 1s 857ms/step\n",
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      "1/1 [==============================] - 1s 556ms/step\n",
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      "1/1 [==============================] - 1s 545ms/step\n",
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      "1/1 [==============================] - 1s 548ms/step\n",
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      "1/1 [==============================] - 1s 533ms/step\n",
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      "1/1 [==============================] - 1s 747ms/step\n",
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      "1/1 [==============================] - 1s 921ms/step\n",
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      "1/1 [==============================] - 1s 970ms/step\n",
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      "1/1 [==============================] - 1s 968ms/step\n",
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      "1/1 [==============================] - 1s 921ms/step\n",
      "Time: 6559.37ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 917ms/step\n",
      "Time: 6718.72ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 877ms/step\n",
      "Time: 6878.69ms, Detection FPS: 0.1, total FPS: 0.1\n",
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      "1/1 [==============================] - 1s 871ms/step\n",
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      "1/1 [==============================] - 1s 912ms/step\n",
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      "1/1 [==============================] - 1s 846ms/step\n",
      "Time: 8125.26ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 893ms/step\n",
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      "1/1 [==============================] - 1s 866ms/step\n",
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      "1/1 [==============================] - 1s 931ms/step\n",
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      "1/1 [==============================] - 1s 893ms/step\n",
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      "1/1 [==============================] - 1s 872ms/step\n",
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      "1/1 [==============================] - 1s 891ms/step\n",
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      "1/1 [==============================] - 1s 836ms/step\n",
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      "1/1 [==============================] - 1s 934ms/step\n",
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      "1/1 [==============================] - 1s 937ms/step\n",
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      "1/1 [==============================] - 1s 903ms/step\n",
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      "1/1 [==============================] - 1s 927ms/step\n",
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      "1/1 [==============================] - 1s 884ms/step\n",
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      "1/1 [==============================] - 1s 888ms/step\n",
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      "1/1 [==============================] - 1s 927ms/step\n",
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      "1/1 [==============================] - 1s 934ms/step\n",
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      "1/1 [==============================] - 1s 900ms/step\n",
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      "1/1 [==============================] - 1s 909ms/step\n",
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      "1/1 [==============================] - 1s 929ms/step\n",
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      "1/1 [==============================] - 1s 958ms/step\n",
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      "1/1 [==============================] - 1s 899ms/step\n",
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      "1/1 [==============================] - 1s 905ms/step\n",
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      "1/1 [==============================] - 1s 873ms/step\n",
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      "1/1 [==============================] - 1s 931ms/step\n",
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      "1/1 [==============================] - 1s 923ms/step\n",
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      "1/1 [==============================] - 1s 911ms/step\n",
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      "1/1 [==============================] - 1s 942ms/step\n",
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      "1/1 [==============================] - 1s 909ms/step\n",
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      "1/1 [==============================] - 1s 876ms/step\n",
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      "1/1 [==============================] - 1s 945ms/step\n",
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      "1/1 [==============================] - 1s 969ms/step\n",
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      "1/1 [==============================] - 1s 918ms/step\n",
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      "1/1 [==============================] - 1s 885ms/step\n",
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      "1/1 [==============================] - 1s 917ms/step\n",
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      "1/1 [==============================] - 1s 929ms/step\n",
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      "1/1 [==============================] - 1s 907ms/step\n",
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      "1/1 [==============================] - 1s 870ms/step\n",
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      "1/1 [==============================] - 1s 924ms/step\n",
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      "1/1 [==============================] - 1s 890ms/step\n",
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      "1/1 [==============================] - 1s 656ms/step\n",
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      "1/1 [==============================] - 1s 909ms/step\n",
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      "1/1 [==============================] - 1s 978ms/step\n",
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      "1/1 [==============================] - 1s 925ms/step\n",
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      "1/1 [==============================] - 1s 878ms/step\n",
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      "1/1 [==============================] - 1s 901ms/step\n",
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      "1/1 [==============================] - 1s 905ms/step\n",
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      "1/1 [==============================] - 1s 901ms/step\n",
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      "1/1 [==============================] - 1s 900ms/step\n",
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      "1/1 [==============================] - 1s 949ms/step\n",
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      "1/1 [==============================] - 1s 863ms/step\n",
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      "1/1 [==============================] - 1s 909ms/step\n",
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      "1/1 [==============================] - 1s 899ms/step\n",
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      "1/1 [==============================] - 1s 874ms/step\n",
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      "1/1 [==============================] - 1s 911ms/step\n",
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      "1/1 [==============================] - 1s 903ms/step\n",
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      "1/1 [==============================] - 1s 863ms/step\n",
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      "1/1 [==============================] - 1s 913ms/step\n",
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      "1/1 [==============================] - 1s 874ms/step\n",
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      "1/1 [==============================] - 1s 924ms/step\n",
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      "1/1 [==============================] - 1s 980ms/step\n",
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      "1/1 [==============================] - 1s 949ms/step\n",
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      "1/1 [==============================] - 1s 911ms/step\n",
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      "1/1 [==============================] - 1s 944ms/step\n",
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      "1/1 [==============================] - 1s 910ms/step\n",
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      "1/1 [==============================] - 1s 880ms/step\n",
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      "1/1 [==============================] - 1s 932ms/step\n",
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      "1/1 [==============================] - 1s 918ms/step\n",
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      "1/1 [==============================] - 1s 558ms/step\n",
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      "1/1 [==============================] - 1s 554ms/step\n",
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      "1/1 [==============================] - 1s 549ms/step\n",
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      "1/1 [==============================] - 1s 586ms/step\n",
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      "1/1 [==============================] - 1s 575ms/step\n",
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      "1/1 [==============================] - 1s 573ms/step\n",
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      "1/1 [==============================] - 1s 537ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 571ms/step\n",
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      "1/1 [==============================] - 1s 544ms/step\n",
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      "1/1 [==============================] - 1s 574ms/step\n",
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      "1/1 [==============================] - 1s 533ms/step\n",
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      "1/1 [==============================] - 1s 587ms/step\n",
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      "1/1 [==============================] - 1s 549ms/step\n",
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      "1/1 [==============================] - 1s 559ms/step\n",
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      "1/1 [==============================] - 1s 586ms/step\n",
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      "1/1 [==============================] - 1s 548ms/step\n",
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      "1/1 [==============================] - 1s 560ms/step\n",
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      "1/1 [==============================] - 1s 613ms/step\n",
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      "1/1 [==============================] - 1s 560ms/step\n",
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      "1/1 [==============================] - 1s 549ms/step\n",
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      "1/1 [==============================] - 1s 576ms/step\n",
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      "1/1 [==============================] - 1s 557ms/step\n",
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      "1/1 [==============================] - 1s 583ms/step\n",
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      "1/1 [==============================] - 1s 566ms/step\n",
      "Time: 6188.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 551ms/step\n",
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      "1/1 [==============================] - 1s 540ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
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      "1/1 [==============================] - 1s 554ms/step\n",
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      "1/1 [==============================] - 1s 554ms/step\n",
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      "1/1 [==============================] - 1s 535ms/step\n",
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      "1/1 [==============================] - 1s 605ms/step\n",
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      "1/1 [==============================] - 1s 567ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 549ms/step\n",
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      "1/1 [==============================] - 1s 546ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 590ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
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      "1/1 [==============================] - 1s 545ms/step\n",
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      "1/1 [==============================] - 1s 531ms/step\n",
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      "1/1 [==============================] - 1s 532ms/step\n",
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      "1/1 [==============================] - 1s 531ms/step\n",
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      "1/1 [==============================] - 1s 527ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 577ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 542ms/step\n",
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      "1/1 [==============================] - 1s 598ms/step\n",
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      "1/1 [==============================] - 1s 547ms/step\n",
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      "1/1 [==============================] - 1s 556ms/step\n",
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      "1/1 [==============================] - 1s 585ms/step\n",
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      "1/1 [==============================] - 1s 526ms/step\n",
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      "1/1 [==============================] - 1s 607ms/step\n",
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      "1/1 [==============================] - 1s 564ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
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      "1/1 [==============================] - 1s 563ms/step\n",
      "Time: 6178.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 564ms/step\n",
      "Time: 6240.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 548ms/step\n",
      "Time: 6290.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 567ms/step\n",
      "Time: 6385.47ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 6441.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 539ms/step\n",
      "Time: 6534.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 567ms/step\n",
      "Time: 6576.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 591ms/step\n",
      "Time: 6665.58ms, Detection FPS: 0.2, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 583ms/step\n",
      "Time: 6714.45ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 540ms/step\n",
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      "1/1 [==============================] - 1s 553ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
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      "1/1 [==============================] - 1s 527ms/step\n",
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      "1/1 [==============================] - 1s 557ms/step\n",
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      "1/1 [==============================] - 1s 545ms/step\n",
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      "1/1 [==============================] - 1s 553ms/step\n",
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      "1/1 [==============================] - 1s 572ms/step\n",
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      "1/1 [==============================] - 1s 569ms/step\n",
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      "1/1 [==============================] - 1s 619ms/step\n",
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      "1/1 [==============================] - 1s 529ms/step\n",
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      "1/1 [==============================] - 1s 522ms/step\n",
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      "1/1 [==============================] - 1s 542ms/step\n",
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      "1/1 [==============================] - 1s 548ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 558ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 534ms/step\n",
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      "1/1 [==============================] - 1s 579ms/step\n",
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      "1/1 [==============================] - 1s 577ms/step\n",
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      "1/1 [==============================] - 1s 567ms/step\n",
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      "1/1 [==============================] - 1s 532ms/step\n",
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      "1/1 [==============================] - 1s 546ms/step\n",
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      "1/1 [==============================] - 1s 533ms/step\n",
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      "1/1 [==============================] - 1s 551ms/step\n",
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      "1/1 [==============================] - 1s 581ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 532ms/step\n",
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      "1/1 [==============================] - 1s 558ms/step\n",
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      "1/1 [==============================] - 1s 543ms/step\n",
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      "1/1 [==============================] - 1s 586ms/step\n",
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      "1/1 [==============================] - 1s 535ms/step\n",
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      "1/1 [==============================] - 1s 550ms/step\n",
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      "1/1 [==============================] - 1s 559ms/step\n",
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      "1/1 [==============================] - 1s 535ms/step\n",
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      "1/1 [==============================] - 1s 582ms/step\n",
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      "1/1 [==============================] - 1s 570ms/step\n",
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      "1/1 [==============================] - 1s 557ms/step\n",
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      "1/1 [==============================] - 1s 592ms/step\n",
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      "1/1 [==============================] - 1s 578ms/step\n",
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      "1/1 [==============================] - 1s 594ms/step\n",
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      "1/1 [==============================] - 1s 548ms/step\n",
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      "1/1 [==============================] - 1s 572ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 579ms/step\n",
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      "1/1 [==============================] - 1s 612ms/step\n",
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      "1/1 [==============================] - 1s 573ms/step\n",
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      "1/1 [==============================] - 1s 574ms/step\n",
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      "1/1 [==============================] - 1s 560ms/step\n",
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      "1/1 [==============================] - 1s 608ms/step\n",
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      "1/1 [==============================] - 1s 576ms/step\n",
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      "1/1 [==============================] - 1s 539ms/step\n",
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      "1/1 [==============================] - 1s 544ms/step\n",
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      "1/1 [==============================] - 1s 545ms/step\n",
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      "1/1 [==============================] - 1s 544ms/step\n",
      "Time: 7571.50ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 546ms/step\n",
      "Time: 7548.78ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 548ms/step\n",
      "Time: 7542.32ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 567ms/step\n",
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      "1/1 [==============================] - 1s 534ms/step\n",
      "Time: 7537.59ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 577ms/step\n",
      "Time: 7569.34ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 549ms/step\n",
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      "1/1 [==============================] - 1s 576ms/step\n",
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      "1/1 [==============================] - 1s 582ms/step\n",
      "Time: 7557.24ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 562ms/step\n",
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      "1/1 [==============================] - 1s 576ms/step\n",
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      "1/1 [==============================] - 1s 589ms/step\n",
      "Time: 7521.19ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 563ms/step\n",
      "Time: 7497.13ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 564ms/step\n",
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      "1/1 [==============================] - 1s 562ms/step\n",
      "Time: 7462.21ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 573ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
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      "1/1 [==============================] - 1s 552ms/step\n",
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      "1/1 [==============================] - 1s 539ms/step\n",
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      "1/1 [==============================] - 1s 574ms/step\n",
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      "1/1 [==============================] - 1s 550ms/step\n",
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      "1/1 [==============================] - 1s 549ms/step\n",
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      "1/1 [==============================] - 1s 578ms/step\n",
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      "1/1 [==============================] - 1s 541ms/step\n",
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      "1/1 [==============================] - 1s 541ms/step\n",
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      "1/1 [==============================] - 1s 563ms/step\n",
      "Time: 7436.05ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 557ms/step\n",
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      "1/1 [==============================] - 1s 576ms/step\n",
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      "1/1 [==============================] - 1s 541ms/step\n",
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      "1/1 [==============================] - 1s 548ms/step\n",
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      "1/1 [==============================] - 1s 557ms/step\n",
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      "1/1 [==============================] - 1s 565ms/step\n",
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      "1/1 [==============================] - 1s 544ms/step\n",
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      "1/1 [==============================] - 1s 590ms/step\n",
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      "1/1 [==============================] - 1s 567ms/step\n",
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      "1/1 [==============================] - 1s 533ms/step\n",
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      "1/1 [==============================] - 1s 540ms/step\n",
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      "1/1 [==============================] - 1s 592ms/step\n",
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      "1/1 [==============================] - 1s 537ms/step\n",
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      "1/1 [==============================] - 1s 568ms/step\n",
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      "1/1 [==============================] - 1s 568ms/step\n",
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      "1/1 [==============================] - 1s 560ms/step\n",
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      "1/1 [==============================] - 1s 554ms/step\n",
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      "1/1 [==============================] - 1s 536ms/step\n",
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      "1/1 [==============================] - 1s 541ms/step\n",
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      "1/1 [==============================] - 1s 538ms/step\n",
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      "1/1 [==============================] - 1s 584ms/step\n",
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      "1/1 [==============================] - 1s 543ms/step\n",
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      "1/1 [==============================] - 1s 542ms/step\n",
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      "1/1 [==============================] - 1s 531ms/step\n",
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      "1/1 [==============================] - 1s 568ms/step\n",
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      "1/1 [==============================] - 1s 553ms/step\n",
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      "1/1 [==============================] - 1s 559ms/step\n",
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      "1/1 [==============================] - 1s 557ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
      "Time: 7329.12ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 585ms/step\n",
      "Time: 7340.58ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 544ms/step\n",
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      "1/1 [==============================] - 1s 535ms/step\n",
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      "1/1 [==============================] - 1s 568ms/step\n",
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      "1/1 [==============================] - 1s 585ms/step\n",
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      "1/1 [==============================] - 1s 546ms/step\n",
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      "1/1 [==============================] - 1s 573ms/step\n",
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      "1/1 [==============================] - 1s 561ms/step\n",
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      "1/1 [==============================] - 1s 568ms/step\n",
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      "1/1 [==============================] - 1s 546ms/step\n",
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      "1/1 [==============================] - 1s 555ms/step\n",
      "Time: 7329.63ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 585ms/step\n",
      "Time: 7304.04ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 562ms/step\n",
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      "1/1 [==============================] - 1s 843ms/step\n",
      "Time: 7225.95ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 0s 480ms/step\n",
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      "1/1 [==============================] - 0s 499ms/step\n",
      "Time: 6964.76ms, Detection FPS: 0.1, total FPS: 0.1\n",
      "1/1 [==============================] - 1s 500ms/step\n",
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      "1/1 [==============================] - 0s 498ms/step\n",
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      "1/1 [==============================] - 0s 494ms/step\n",
      "Time: 6574.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 521ms/step\n",
      "Time: 6447.69ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 547ms/step\n",
      "Time: 6337.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 6241.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 581ms/step\n",
      "Time: 6121.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 600ms/step\n",
      "Time: 6018.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 5900.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 567ms/step\n",
      "Time: 5779.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 600ms/step\n",
      "Time: 5687.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 5629.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 672ms/step\n",
      "Time: 5490.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 578ms/step\n",
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      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 5389.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 692ms/step\n",
      "Time: 5288.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 5129.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 602ms/step\n",
      "Time: 5079.65ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 5088.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 5121.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 583ms/step\n",
      "Time: 5125.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 586ms/step\n",
      "Time: 5120.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 658ms/step\n",
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      "1/1 [==============================] - 1s 646ms/step\n",
      "Time: 5102.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 692ms/step\n",
      "Time: 5089.16ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 520ms/step\n",
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      "1/1 [==============================] - 1s 579ms/step\n",
      "Time: 5100.96ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 597ms/step\n",
      "Time: 5100.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 577ms/step\n",
      "Time: 5094.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 5089.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 639ms/step\n",
      "Time: 5033.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 5032.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 564ms/step\n",
      "Time: 5000.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 595ms/step\n",
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      "1/1 [==============================] - 1s 614ms/step\n",
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      "1/1 [==============================] - 1s 585ms/step\n",
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      "1/1 [==============================] - 1s 600ms/step\n",
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      "1/1 [==============================] - 1s 631ms/step\n",
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      "1/1 [==============================] - 1s 626ms/step\n",
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      "1/1 [==============================] - 1s 550ms/step\n",
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      "1/1 [==============================] - 1s 560ms/step\n",
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      "1/1 [==============================] - 1s 556ms/step\n",
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      "1/1 [==============================] - 1s 554ms/step\n",
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      "1/1 [==============================] - 1s 556ms/step\n",
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      "1/1 [==============================] - 1s 575ms/step\n",
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      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 4746.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 603ms/step\n",
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      "1/1 [==============================] - 1s 593ms/step\n",
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      "1/1 [==============================] - 1s 584ms/step\n",
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      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 4690.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4670.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 4661.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
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      "1/1 [==============================] - 1s 582ms/step\n",
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      "1/1 [==============================] - 1s 612ms/step\n",
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      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 4650.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 568ms/step\n",
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      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 4578.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 595ms/step\n",
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      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4590.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 4598.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 596ms/step\n",
      "Time: 4612.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 575ms/step\n",
      "Time: 4614.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 564ms/step\n",
      "Time: 4619.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 4620.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 595ms/step\n",
      "Time: 4613.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 577ms/step\n",
      "Time: 4614.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 567ms/step\n",
      "Time: 4619.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 602ms/step\n",
      "Time: 4621.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 4635.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 4641.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 4639.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 571ms/step\n",
      "Time: 4631.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 575ms/step\n",
      "Time: 4622.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 4617.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 554ms/step\n",
      "Time: 4606.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 559ms/step\n",
      "Time: 4604.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 558ms/step\n",
      "Time: 4593.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 590ms/step\n",
      "Time: 4589.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 4586.33ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 581ms/step\n",
      "Time: 4585.57ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 581ms/step\n",
      "Time: 4577.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 596ms/step\n",
      "Time: 4578.47ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 580ms/step\n",
      "Time: 4571.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 595ms/step\n",
      "Time: 4559.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 561ms/step\n",
      "Time: 4562.89ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 585ms/step\n",
      "Time: 4559.09ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 577ms/step\n",
      "Time: 4552.47ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 587ms/step\n",
      "Time: 4547.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 584ms/step\n",
      "Time: 4527.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 578ms/step\n",
      "Time: 4523.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
      "Time: 4528.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 4565.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 731ms/step\n",
      "Time: 4672.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 747ms/step\n",
      "Time: 4733.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 4751.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 4765.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 760ms/step\n",
      "Time: 4787.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4823.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 4845.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 743ms/step\n",
      "Time: 4890.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 599ms/step\n",
      "Time: 4914.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4930.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 593ms/step\n",
      "Time: 4940.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 684ms/step\n",
      "Time: 4962.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 4984.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 5006.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 593ms/step\n",
      "Time: 5020.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 5038.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 5052.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 5061.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 5070.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 5057.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
      "Time: 4966.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 714ms/step\n",
      "Time: 4929.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 591ms/step\n",
      "Time: 4931.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 700ms/step\n",
      "Time: 4943.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
      "Time: 4938.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4924.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4923.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 647ms/step\n",
      "Time: 4898.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 4895.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 666ms/step\n",
      "Time: 4898.09ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 792ms/step\n",
      "Time: 4935.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 694ms/step\n",
      "Time: 4930.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4922.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 600ms/step\n",
      "Time: 4906.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 4899.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4888.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4885.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 4876.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
      "Time: 4869.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 596ms/step\n",
      "Time: 4859.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 603ms/step\n",
      "Time: 4858.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 597ms/step\n",
      "Time: 4841.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 594ms/step\n",
      "Time: 4843.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4851.06ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 708ms/step\n",
      "Time: 4870.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 703ms/step\n",
      "Time: 4894.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 717ms/step\n",
      "Time: 4916.32ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 684ms/step\n",
      "Time: 4928.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4940.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4945.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
      "Time: 4910.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 579ms/step\n",
      "Time: 4909.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4899.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 747ms/step\n",
      "Time: 4909.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 583ms/step\n",
      "Time: 4908.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 4905.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 588ms/step\n",
      "Time: 4899.94ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 4895.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4889.12ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 612ms/step\n",
      "Time: 4883.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 4876.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 4899.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4902.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 4877.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 670ms/step\n",
      "Time: 4875.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 668ms/step\n",
      "Time: 4851.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 4824.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 657ms/step\n",
      "Time: 4814.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 702ms/step\n",
      "Time: 4811.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 4795.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4793.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 4782.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 607ms/step\n",
      "Time: 4784.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4779.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 4779.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 584ms/step\n",
      "Time: 4784.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 607ms/step\n",
      "Time: 4783.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 600ms/step\n",
      "Time: 4785.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 592ms/step\n",
      "Time: 4790.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 591ms/step\n",
      "Time: 4791.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4795.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4769.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4756.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 4760.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4735.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4723.23ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4723.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 603ms/step\n",
      "Time: 4710.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 4703.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 596ms/step\n",
      "Time: 4704.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 603ms/step\n",
      "Time: 4703.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
      "Time: 4705.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 4707.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 4704.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4708.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4710.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 607ms/step\n",
      "Time: 4720.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4725.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 600ms/step\n",
      "Time: 4724.78ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4727.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 4727.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4729.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
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      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4734.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
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      "1/1 [==============================] - 1s 657ms/step\n",
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      "1/1 [==============================] - 1s 592ms/step\n",
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      "1/1 [==============================] - 1s 647ms/step\n",
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      "1/1 [==============================] - 1s 621ms/step\n",
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      "1/1 [==============================] - 1s 646ms/step\n",
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      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4745.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
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      "1/1 [==============================] - 1s 625ms/step\n",
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      "1/1 [==============================] - 1s 605ms/step\n",
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      "1/1 [==============================] - 1s 647ms/step\n",
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      "1/1 [==============================] - 1s 646ms/step\n",
      "Time: 4770.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
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      "1/1 [==============================] - 1s 597ms/step\n",
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      "1/1 [==============================] - 1s 658ms/step\n",
      "Time: 4772.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
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      "1/1 [==============================] - 1s 647ms/step\n",
      "Time: 4841.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 655ms/step\n",
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      "1/1 [==============================] - 1s 787ms/step\n",
      "Time: 4904.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 731ms/step\n",
      "Time: 4926.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
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      "1/1 [==============================] - 1s 709ms/step\n",
      "Time: 4984.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
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      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 5018.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 612ms/step\n",
      "Time: 5029.29ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 601ms/step\n",
      "Time: 5022.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 5021.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 5030.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 5026.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 5032.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 5031.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 5030.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 5036.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 5041.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 599ms/step\n",
      "Time: 5038.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 5041.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 4976.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 4953.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 619ms/step\n",
      "Time: 4942.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4921.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 603ms/step\n",
      "Time: 4913.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 692ms/step\n",
      "Time: 4862.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4888.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4861.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4858.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4867.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 857ms/step\n",
      "Time: 4956.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 667ms/step\n",
      "Time: 4965.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 671ms/step\n",
      "Time: 5027.90ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 5095.65ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 741ms/step\n",
      "Time: 5169.89ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 688ms/step\n",
      "Time: 5244.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 873ms/step\n",
      "Time: 5279.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 5328.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 710ms/step\n",
      "Time: 5355.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 748ms/step\n",
      "Time: 5379.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 749ms/step\n",
      "Time: 5407.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 849ms/step\n",
      "Time: 5428.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 716ms/step\n",
      "Time: 5445.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 685ms/step\n",
      "Time: 5465.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 766ms/step\n",
      "Time: 5481.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 691ms/step\n",
      "Time: 5489.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 5463.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 601ms/step\n",
      "Time: 5459.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5458.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 5450.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 5360.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 655ms/step\n",
      "Time: 5349.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 5288.54ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 5215.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 5142.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 652ms/step\n",
      "Time: 5064.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 5050.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 5067.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 556ms/step\n",
      "Time: 5117.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 555ms/step\n",
      "Time: 5147.96ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 567ms/step\n",
      "Time: 5195.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 5228.09ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 696ms/step\n",
      "Time: 5292.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 639ms/step\n",
      "Time: 5342.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 574ms/step\n",
      "Time: 5422.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 580ms/step\n",
      "Time: 5517.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 559ms/step\n",
      "Time: 5579.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 593ms/step\n",
      "Time: 5628.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 573ms/step\n",
      "Time: 5711.27ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 562ms/step\n",
      "Time: 5792.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 573ms/step\n",
      "Time: 5822.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 546ms/step\n",
      "Time: 5818.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 0s 464ms/step\n",
      "Time: 5781.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 0s 467ms/step\n",
      "Time: 5740.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 0s 457ms/step\n",
      "Time: 5691.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 531ms/step\n",
      "Time: 5682.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 5649.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 5570.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5500.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 684ms/step\n",
      "Time: 5509.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 751ms/step\n",
      "Time: 5499.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 764ms/step\n",
      "Time: 5516.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 747ms/step\n",
      "Time: 5499.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 756ms/step\n",
      "Time: 5487.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 762ms/step\n",
      "Time: 5445.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 740ms/step\n",
      "Time: 5406.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 771ms/step\n",
      "Time: 5404.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 768ms/step\n",
      "Time: 5408.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 742ms/step\n",
      "Time: 5408.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 734ms/step\n",
      "Time: 5389.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 737ms/step\n",
      "Time: 5436.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 788ms/step\n",
      "Time: 5494.16ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 739ms/step\n",
      "Time: 5582.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 714ms/step\n",
      "Time: 5658.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 708ms/step\n",
      "Time: 5751.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 5809.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 502ms/step\n",
      "Time: 5790.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 0s 476ms/step\n",
      "Time: 5762.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 5752.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 5677.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 688ms/step\n",
      "Time: 5606.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 654ms/step\n",
      "Time: 5509.49ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 5435.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 5368.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 5304.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
      "Time: 5226.12ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 5153.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 5087.65ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4993.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4924.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4838.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4767.89ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 4705.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 4656.54ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4599.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 4544.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 4560.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 4588.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 4583.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 712ms/step\n",
      "Time: 4589.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4588.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 4585.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4580.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4578.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4573.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 4573.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4574.27ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 4574.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4578.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4580.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 761ms/step\n",
      "Time: 4594.50ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 4597.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 4590.94ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 4595.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 4604.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 4619.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 4624.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4623.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 656ms/step\n",
      "Time: 4624.50ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4624.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 725ms/step\n",
      "Time: 4635.06ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 709ms/step\n",
      "Time: 4649.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 667ms/step\n",
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      "1/1 [==============================] - 1s 625ms/step\n",
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      "1/1 [==============================] - 1s 653ms/step\n",
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      "1/1 [==============================] - 1s 605ms/step\n",
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      "1/1 [==============================] - 1s 633ms/step\n",
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      "1/1 [==============================] - 1s 634ms/step\n",
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      "1/1 [==============================] - 1s 627ms/step\n",
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      "1/1 [==============================] - 1s 633ms/step\n",
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      "1/1 [==============================] - 1s 640ms/step\n",
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      "1/1 [==============================] - 1s 636ms/step\n",
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      "1/1 [==============================] - 1s 626ms/step\n",
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      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4652.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
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      "1/1 [==============================] - 1s 626ms/step\n",
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      "1/1 [==============================] - 1s 693ms/step\n",
      "Time: 4622.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
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      "1/1 [==============================] - 1s 657ms/step\n",
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      "1/1 [==============================] - 1s 649ms/step\n",
      "Time: 4621.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4623.42ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4614.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 4603.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 4590.94ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 593ms/step\n",
      "Time: 4584.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
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      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4592.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4587.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4593.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 4594.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 4597.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 4596.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4598.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4599.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4598.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4598.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 4599.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4606.26ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4610.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 606ms/step\n",
      "Time: 4608.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4590.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 4585.68ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 597ms/step\n",
      "Time: 4589.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 4595.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4602.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 4605.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 4603.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 647ms/step\n",
      "Time: 4606.26ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 4599.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 4603.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 4605.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 4606.16ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 4609.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 653ms/step\n",
      "Time: 4612.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4615.86ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4629.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 647ms/step\n",
      "Time: 4628.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 609ms/step\n",
      "Time: 4620.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 614ms/step\n",
      "Time: 4616.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4621.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 4630.96ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4634.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4632.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 652ms/step\n",
      "Time: 4630.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4627.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4632.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 699ms/step\n",
      "Time: 4636.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4635.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 670ms/step\n",
      "Time: 4647.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 652ms/step\n",
      "Time: 4659.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 4662.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 726ms/step\n",
      "Time: 4673.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 4669.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 660ms/step\n",
      "Time: 4682.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4682.89ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 664ms/step\n",
      "Time: 4669.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4674.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4676.94ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 605ms/step\n",
      "Time: 4676.79ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 646ms/step\n",
      "Time: 4682.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 4677.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4675.59ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 701ms/step\n",
      "Time: 4685.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 4689.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 4698.86ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 693ms/step\n",
      "Time: 4707.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 729ms/step\n",
      "Time: 4722.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4725.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 620ms/step\n",
      "Time: 4718.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4699.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 4695.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 639ms/step\n",
      "Time: 4684.33ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 4685.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4671.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4671.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4668.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 4660.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4659.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4656.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 4645.48ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4651.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 662ms/step\n",
      "Time: 4652.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4645.91ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 4640.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 4625.41ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 4620.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 4608.52ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 658ms/step\n",
      "Time: 4623.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 677ms/step\n",
      "Time: 4627.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4631.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4631.54ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 4632.86ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 613ms/step\n",
      "Time: 4625.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4626.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 4623.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4623.34ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 4639.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4635.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4636.45ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 608ms/step\n",
      "Time: 4638.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4631.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 4629.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 772ms/step\n",
      "Time: 4637.07ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 700ms/step\n",
      "Time: 4643.11ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 656ms/step\n",
      "Time: 4652.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 648ms/step\n",
      "Time: 4643.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4632.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 682ms/step\n",
      "Time: 4612.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 652ms/step\n",
      "Time: 4610.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 669ms/step\n",
      "Time: 4611.01ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 4611.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4612.47ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 639ms/step\n",
      "Time: 4617.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 634ms/step\n",
      "Time: 4616.67ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 675ms/step\n",
      "Time: 4620.05ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4618.81ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 4599.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
      "Time: 4600.73ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 654ms/step\n",
      "Time: 4610.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4608.85ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 654ms/step\n",
      "Time: 4614.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 664ms/step\n",
      "Time: 4612.54ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 611ms/step\n",
      "Time: 4598.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4593.97ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 4584.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4581.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 598ms/step\n",
      "Time: 4606.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 4606.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 656ms/step\n",
      "Time: 4609.35ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 646ms/step\n",
      "Time: 4608.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 670ms/step\n",
      "Time: 4611.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 629ms/step\n",
      "Time: 4605.38ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4603.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 4604.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4598.88ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 640ms/step\n",
      "Time: 4603.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4610.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 649ms/step\n",
      "Time: 4612.13ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4603.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4601.37ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4594.46ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4597.36ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 4597.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 630ms/step\n",
      "Time: 4595.69ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4604.98ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4605.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 654ms/step\n",
      "Time: 4584.15ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 635ms/step\n",
      "Time: 4585.08ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 636ms/step\n",
      "Time: 4576.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 628ms/step\n",
      "Time: 4573.40ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 626ms/step\n",
      "Time: 4573.24ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 642ms/step\n",
      "Time: 4577.64ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 669ms/step\n",
      "Time: 4597.32ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 638ms/step\n",
      "Time: 4597.60ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 683ms/step\n",
      "Time: 4627.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 673ms/step\n",
      "Time: 4637.12ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4642.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 693ms/step\n",
      "Time: 4650.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 681ms/step\n",
      "Time: 4652.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 661ms/step\n",
      "Time: 4652.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 644ms/step\n",
      "Time: 4655.54ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 662ms/step\n",
      "Time: 4655.79ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4655.82ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4654.87ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 752ms/step\n",
      "Time: 4679.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4679.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 627ms/step\n",
      "Time: 4682.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 657ms/step\n",
      "Time: 4715.95ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 746ms/step\n",
      "Time: 4734.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 659ms/step\n",
      "Time: 4739.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 4739.82ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4739.50ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 623ms/step\n",
      "Time: 4717.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 4716.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 4693.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 612ms/step\n",
      "Time: 4688.92ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 669ms/step\n",
      "Time: 4693.18ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 4682.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4680.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 621ms/step\n",
      "Time: 4693.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 633ms/step\n",
      "Time: 4691.65ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 4686.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 632ms/step\n",
      "Time: 4691.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 673ms/step\n",
      "Time: 4692.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 654ms/step\n",
      "Time: 4667.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 663ms/step\n",
      "Time: 4669.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 655ms/step\n",
      "Time: 4669.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4637.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 615ms/step\n",
      "Time: 4624.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 665ms/step\n",
      "Time: 4623.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 616ms/step\n",
      "Time: 4618.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 610ms/step\n",
      "Time: 4619.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 645ms/step\n",
      "Time: 4625.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 664ms/step\n",
      "Time: 4624.82ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 654ms/step\n",
      "Time: 4627.53ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 723ms/step\n",
      "Time: 4630.59ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4619.31ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 658ms/step\n",
      "Time: 4624.04ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 618ms/step\n",
      "Time: 4624.21ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 641ms/step\n",
      "Time: 4614.79ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 631ms/step\n",
      "Time: 4619.17ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 622ms/step\n",
      "Time: 4623.56ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 664ms/step\n",
      "Time: 4624.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 652ms/step\n",
      "Time: 4626.69ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 677ms/step\n",
      "Time: 4624.43ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 669ms/step\n",
      "Time: 4623.69ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 650ms/step\n",
      "Time: 4620.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 656ms/step\n",
      "Time: 4618.10ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 651ms/step\n",
      "Time: 4621.72ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 617ms/step\n",
      "Time: 4618.61ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 637ms/step\n",
      "Time: 4616.28ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 624ms/step\n",
      "Time: 4617.75ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 625ms/step\n",
      "Time: 116642.06ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 575ms/step\n",
      "Time: 116719.17ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 591ms/step\n",
      "Time: 116771.43ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 643ms/step\n",
      "Time: 116875.68ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 737ms/step\n",
      "Time: 117005.51ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 776ms/step\n",
      "Time: 117242.37ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 1s/step\n",
      "Time: 117462.54ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 953ms/step\n",
      "Time: 117604.22ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 868ms/step\n",
      "Time: 117715.77ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 915ms/step\n",
      "Time: 117827.74ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 717ms/step\n",
      "Time: 117892.36ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 819ms/step\n",
      "Time: 117957.01ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 760ms/step\n",
      "Time: 117999.86ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 766ms/step\n",
      "Time: 118046.32ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 826ms/step\n",
      "Time: 118110.59ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 764ms/step\n",
      "Time: 118178.19ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 789ms/step\n",
      "Time: 118231.62ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 766ms/step\n",
      "Time: 118289.08ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 757ms/step\n",
      "Time: 118347.45ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 765ms/step\n",
      "Time: 118409.87ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 808ms/step\n",
      "Time: 6455.66ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 770ms/step\n",
      "Time: 6435.47ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 773ms/step\n",
      "Time: 6434.25ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 785ms/step\n",
      "Time: 6383.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 751ms/step\n",
      "Time: 6304.58ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 782ms/step\n",
      "Time: 6127.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 761ms/step\n",
      "Time: 5983.63ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 776ms/step\n",
      "Time: 5899.96ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 802ms/step\n",
      "Time: 5851.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 777ms/step\n",
      "Time: 5808.12ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 782ms/step\n",
      "Time: 5798.44ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 809ms/step\n",
      "Time: 5798.83ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 802ms/step\n",
      "Time: 5820.39ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 791ms/step\n",
      "Time: 5833.20ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 802ms/step\n",
      "Time: 5834.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 798ms/step\n",
      "Time: 5831.84ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 835ms/step\n",
      "Time: 5843.77ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 806ms/step\n",
      "Time: 5855.86ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 807ms/step\n",
      "Time: 5871.30ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 818ms/step\n",
      "Time: 5878.06ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 817ms/step\n",
      "Time: 5877.71ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 767ms/step\n",
      "Time: 5892.03ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 833ms/step\n",
      "Time: 5903.74ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 864ms/step\n",
      "Time: 5922.82ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 748ms/step\n",
      "Time: 5944.89ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 827ms/step\n",
      "Time: 5954.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 855ms/step\n",
      "Time: 5950.22ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 854ms/step\n",
      "Time: 5968.69ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 809ms/step\n",
      "Time: 5975.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 847ms/step\n",
      "Time: 5985.14ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 886ms/step\n",
      "Time: 6008.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 861ms/step\n",
      "Time: 6013.11ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 834ms/step\n",
      "Time: 6034.65ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 913ms/step\n",
      "Time: 6068.02ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 851ms/step\n",
      "Time: 6078.89ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 863ms/step\n",
      "Time: 6082.80ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 842ms/step\n",
      "Time: 6085.51ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 850ms/step\n",
      "Time: 6103.19ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 836ms/step\n",
      "Time: 6107.62ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 901ms/step\n",
      "Time: 6118.76ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 850ms/step\n",
      "Time: 6129.00ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 827ms/step\n",
      "Time: 6142.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 836ms/step\n",
      "Time: 6154.93ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 863ms/step\n",
      "Time: 6155.99ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 860ms/step\n",
      "Time: 6162.55ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 897ms/step\n",
      "Time: 6164.70ms, Detection FPS: 0.2, total FPS: 0.2\n",
      "1/1 [==============================] - 1s 786ms/step\n",
      "Time: 46711.77ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 540ms/step\n",
      "Time: 53718.90ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 801ms/step\n",
      "Time: 53729.58ms, Detection FPS: 0.0, total FPS: 0.0\n",
      "1/1 [==============================] - 1s 738ms/step\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[46], line 13\u001b[0m\n\u001b[0;32m     11\u001b[0m number_of_videos_object_tracked_using_Kalman_Filter \u001b[38;5;241m=\u001b[39m number_of_videos_object_tracked_using_Kalman_Filter\n\u001b[0;32m     12\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mProcessing video \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mvideo\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m---> 13\u001b[0m \u001b[43mobject_tracking\u001b[49m\u001b[43m(\u001b[49m\u001b[43mVIDEO_PATH\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mvideo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mvideo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     15\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m number_of_videos_object_tracked_using_Kalman_Filter \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m10\u001b[39m :\n\u001b[0;32m     17\u001b[0m     \u001b[38;5;28;01mbreak\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[45], line 44\u001b[0m, in \u001b[0;36mobject_tracking\u001b[1;34m(video_path, output_path)\u001b[0m\n\u001b[0;32m     41\u001b[0m correct_yolo_boxes(boxes, image_h, image_w, HEIGHT, WIDTH)\n\u001b[0;32m     43\u001b[0m \u001b[38;5;66;03m# Suppress Non Maximal Boxes\u001b[39;00m\n\u001b[1;32m---> 44\u001b[0m \u001b[43mdo_nms\u001b[49m\u001b[43m(\u001b[49m\u001b[43mboxes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0.3\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m     46\u001b[0m \u001b[38;5;66;03m# define the labels (Filtered only the ones relevant for this task, which were used in pretraining the YOLOv3 model)\u001b[39;00m\n\u001b[0;32m     47\u001b[0m labels \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mperson\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbicycle\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcar\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmotorbike\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maeroplane\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbus\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtrain\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m,\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mboat\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n",
      "Cell \u001b[1;32mIn[25], line 116\u001b[0m, in \u001b[0;36mdo_nms\u001b[1;34m(boxes, nms_thresh)\u001b[0m\n\u001b[0;32m    114\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[0;32m    115\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m c \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(nb_class):\n\u001b[1;32m--> 116\u001b[0m     sorted_indices \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margsort\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43mbox\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclasses\u001b[49m\u001b[43m[\u001b[49m\u001b[43mc\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mbox\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mboxes\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    117\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(sorted_indices)):\n\u001b[0;32m    118\u001b[0m         index_i \u001b[38;5;241m=\u001b[39m sorted_indices[i]\n",
      "File \u001b[1;32m<__array_function__ internals>:200\u001b[0m, in \u001b[0;36margsort\u001b[1;34m(*args, **kwargs)\u001b[0m\n",
      "File \u001b[1;32mc:\\Users\\moodm\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\numpy\\core\\fromnumeric.py:1146\u001b[0m, in \u001b[0;36margsort\u001b[1;34m(a, axis, kind, order)\u001b[0m\n\u001b[0;32m   1038\u001b[0m \u001b[38;5;129m@array_function_dispatch\u001b[39m(_argsort_dispatcher)\n\u001b[0;32m   1039\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21margsort\u001b[39m(a, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m, kind\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, order\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m   1040\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m   1041\u001b[0m \u001b[38;5;124;03m    Returns the indices that would sort an array.\u001b[39;00m\n\u001b[0;32m   1042\u001b[0m \n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1144\u001b[0m \n\u001b[0;32m   1145\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m-> 1146\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_wrapfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43ma\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43margsort\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43maxis\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkind\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkind\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43morder\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morder\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32mc:\\Users\\moodm\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\numpy\\core\\fromnumeric.py:54\u001b[0m, in \u001b[0;36m_wrapfunc\u001b[1;34m(obj, method, *args, **kwds)\u001b[0m\n\u001b[0;32m     52\u001b[0m bound \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(obj, method, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m     53\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m bound \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m---> 54\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_wrapit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     56\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m     57\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m bound(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n",
      "File \u001b[1;32mc:\\Users\\moodm\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\numpy\\core\\fromnumeric.py:43\u001b[0m, in \u001b[0;36m_wrapit\u001b[1;34m(obj, method, *args, **kwds)\u001b[0m\n\u001b[0;32m     41\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n\u001b[0;32m     42\u001b[0m     wrap \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m---> 43\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mgetattr\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobj\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m)\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     44\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m wrap:\n\u001b[0;32m     45\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(result, mu\u001b[38;5;241m.\u001b[39mndarray):\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# Process all Videos\n",
    "import os\n",
    "\n",
    "VIDEO_PATH = 'dataset/testing/'\n",
    "videos = os.listdir(VIDEO_PATH)\n",
    "\n",
    "number_of_videos_object_tracked_using_Kalman_Filter = 0\n",
    "\n",
    "for video in videos:\n",
    "    \n",
    "    number_of_videos_object_tracked_using_Kalman_Filter = number_of_videos_object_tracked_using_Kalman_Filter\n",
    "    print(f\"Processing video {video}\")\n",
    "    object_tracking(VIDEO_PATH + video, video)\n",
    "    \n",
    "    if number_of_videos_object_tracked_using_Kalman_Filter >= 10 :\n",
    "        \n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60051372",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T13:48:05.147496Z",
     "iopub.status.busy": "2023-09-01T13:48:05.147010Z",
     "iopub.status.idle": "2023-09-01T13:48:14.971935Z",
     "shell.execute_reply": "2023-09-01T13:48:14.969012Z"
    },
    "papermill": {
     "duration": 11.00421,
     "end_time": "2023-09-01T13:48:15.016402",
     "exception": false,
     "start_time": "2023-09-01T13:48:04.012192",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "Image data of dtype object cannot be converted to float",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[54], line 74\u001b[0m\n\u001b[0;32m     70\u001b[0m \u001b[38;5;66;03m#ax.set_size( 20 , 13 )\u001b[39;00m\n\u001b[0;32m     71\u001b[0m \u001b[38;5;66;03m#plt.set_size( 20 , 13 )\u001b[39;00m\n\u001b[0;32m     72\u001b[0m ax[ num \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m4\u001b[39m , num \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m4\u001b[39m ]\u001b[38;5;241m.\u001b[39mset_title( \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mScene \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat( \u001b[38;5;28mstr\u001b[39m( num ) ) )\n\u001b[1;32m---> 74\u001b[0m \u001b[43max\u001b[49m\u001b[43m[\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnum\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m%\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimshow\u001b[49m\u001b[43m(\u001b[49m\u001b[43m \u001b[49m\u001b[43mimg\u001b[49m\u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     76\u001b[0m ax[ num \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m4\u001b[39m , num \u001b[38;5;241m%\u001b[39m \u001b[38;5;241m4\u001b[39m ]\u001b[38;5;241m.\u001b[39mset_axis_off()\n",
      "File \u001b[1;32mc:\\Users\\moodm\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\matplotlib\\__init__.py:1459\u001b[0m, in \u001b[0;36m_preprocess_data.<locals>.inner\u001b[1;34m(ax, data, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1456\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[0;32m   1457\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minner\u001b[39m(ax, \u001b[38;5;241m*\u001b[39margs, data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m   1458\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m data \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m-> 1459\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[43max\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mmap\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43msanitize_sequence\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43margs\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1461\u001b[0m     bound \u001b[38;5;241m=\u001b[39m new_sig\u001b[38;5;241m.\u001b[39mbind(ax, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m   1462\u001b[0m     auto_label \u001b[38;5;241m=\u001b[39m (bound\u001b[38;5;241m.\u001b[39marguments\u001b[38;5;241m.\u001b[39mget(label_namer)\n\u001b[0;32m   1463\u001b[0m                   \u001b[38;5;129;01mor\u001b[39;00m bound\u001b[38;5;241m.\u001b[39mkwargs\u001b[38;5;241m.\u001b[39mget(label_namer))\n",
      "File \u001b[1;32mc:\\Users\\moodm\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\matplotlib\\axes\\_axes.py:5665\u001b[0m, in \u001b[0;36mAxes.imshow\u001b[1;34m(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, interpolation_stage, filternorm, filterrad, resample, url, **kwargs)\u001b[0m\n\u001b[0;32m   5657\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mset_aspect(aspect)\n\u001b[0;32m   5658\u001b[0m im \u001b[38;5;241m=\u001b[39m mimage\u001b[38;5;241m.\u001b[39mAxesImage(\u001b[38;5;28mself\u001b[39m, cmap\u001b[38;5;241m=\u001b[39mcmap, norm\u001b[38;5;241m=\u001b[39mnorm,\n\u001b[0;32m   5659\u001b[0m                       interpolation\u001b[38;5;241m=\u001b[39minterpolation, origin\u001b[38;5;241m=\u001b[39morigin,\n\u001b[0;32m   5660\u001b[0m                       extent\u001b[38;5;241m=\u001b[39mextent, filternorm\u001b[38;5;241m=\u001b[39mfilternorm,\n\u001b[0;32m   5661\u001b[0m                       filterrad\u001b[38;5;241m=\u001b[39mfilterrad, resample\u001b[38;5;241m=\u001b[39mresample,\n\u001b[0;32m   5662\u001b[0m                       interpolation_stage\u001b[38;5;241m=\u001b[39minterpolation_stage,\n\u001b[0;32m   5663\u001b[0m                       \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m-> 5665\u001b[0m \u001b[43mim\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mset_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   5666\u001b[0m im\u001b[38;5;241m.\u001b[39mset_alpha(alpha)\n\u001b[0;32m   5667\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m im\u001b[38;5;241m.\u001b[39mget_clip_path() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m   5668\u001b[0m     \u001b[38;5;66;03m# image does not already have clipping set, clip to axes patch\u001b[39;00m\n",
      "File \u001b[1;32mc:\\Users\\moodm\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\matplotlib\\image.py:701\u001b[0m, in \u001b[0;36m_ImageBase.set_data\u001b[1;34m(self, A)\u001b[0m\n\u001b[0;32m    697\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A \u001b[38;5;241m=\u001b[39m cbook\u001b[38;5;241m.\u001b[39msafe_masked_invalid(A, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m    699\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;241m!=\u001b[39m np\u001b[38;5;241m.\u001b[39muint8 \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[0;32m    700\u001b[0m         \u001b[38;5;129;01mnot\u001b[39;00m np\u001b[38;5;241m.\u001b[39mcan_cast(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A\u001b[38;5;241m.\u001b[39mdtype, \u001b[38;5;28mfloat\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msame_kind\u001b[39m\u001b[38;5;124m\"\u001b[39m)):\n\u001b[1;32m--> 701\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mImage data of dtype \u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m cannot be converted to \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    702\u001b[0m                     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfloat\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A\u001b[38;5;241m.\u001b[39mdtype))\n\u001b[0;32m    704\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m3\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m    705\u001b[0m     \u001b[38;5;66;03m# If just one dimension assume scalar and apply colormap\u001b[39;00m\n\u001b[0;32m    706\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_A[:, :, \u001b[38;5;241m0\u001b[39m]\n",
      "\u001b[1;31mTypeError\u001b[0m: Image data of dtype object cannot be converted to float"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x1300 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    " \n",
    "# Create a VideoCapture object and read from input file\n",
    "# If the input is the camera, pass 0 instead of the video file name\n",
    "cap = cv2.VideoCapture('challenge.mp4')\n",
    " \n",
    "\n",
    "number_of_videos_object_Tracked_using_Kalman_Filters = 0\n",
    "\n",
    "list_of_Object_Tracked_Videos_in_Object_Tracked_Files = []\n",
    "\n",
    "number_of_videos_object_Tracked_show_using_Kalman_Filters = 0\n",
    "\n",
    "\n",
    "while( True ):\n",
    "    # Capture frame-by-frame\n",
    "    ret, frame = cap.read()\n",
    "    \n",
    "    number_of_videos_object_Tracked_using_Kalman_Filters = number_of_videos_object_Tracked_using_Kalman_Filters + 1\n",
    "\n",
    "    \n",
    "    if number_of_videos_object_Tracked_using_Kalman_Filters % 10 == 1 :\n",
    "        \n",
    "        list_of_Object_Tracked_Videos_in_Object_Tracked_Files.append( frame )\n",
    "        \n",
    "        number_of_videos_object_Tracked_show_using_Kalman_Filters = number_of_videos_object_Tracked_show_using_Kalman_Filters + 1\n",
    "        \n",
    "    if number_of_videos_object_Tracked_show_using_Kalman_Filters >= 16 :\n",
    "        \n",
    "        break\n",
    "        \n",
    "    \n",
    " \n",
    "# When everything done, release the video capture object\n",
    "#cap.release()\n",
    " \n",
    "# Closes all the frames\n",
    "#cv2.destroyAllWindows()\n",
    "\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import PIL\n",
    "#%matplotlib inline\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_theme()\n",
    "\n",
    "rows = 4\n",
    "#os.chdir('/home/brian/Desktop/cats/')\n",
    "#files = os.listdir('/home/brian/Desktop/cats/')\n",
    "\n",
    "#define subplots\n",
    "fig, ax = plt.subplots(4, 4, figsize=(20,13))\n",
    "fig.tight_layout()\n",
    "\n",
    "#define data\n",
    "#x = [1, 2, 3]\n",
    "#y = [7, 13, 24]\n",
    "\n",
    "\n",
    "for num, x in enumerate(list_of_Object_Tracked_Videos_in_Object_Tracked_Files ):\n",
    "    \n",
    "    img = list_of_Object_Tracked_Videos_in_Object_Tracked_Files[ num ]#PIL.Image.open(x)\n",
    "    #ax = plt.subplot(rows , 4 , num+1 )\n",
    "    #plt.size( 20 , 13 )\n",
    "    #plt.title(\"Scene {}\".format( str( num )))#x.split('.')[0])\n",
    "    plt.axis('off')\n",
    "    #ax.set_size( 20 , 13 )\n",
    "    #plt.set_size( 20 , 13 )\n",
    "    ax[ num // 4 , num % 4 ].set_title( \"Scene {}\".format( str( num ) ) )\n",
    "    \n",
    "    ax[ num // 4 , num % 4 ].imshow( img )\n",
    "    \n",
    "    ax[ num // 4 , num % 4 ].set_axis_off()\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "25e1ce81",
   "metadata": {
    "papermill": {
     "duration": 1.217306,
     "end_time": "2023-09-01T13:48:17.622183",
     "exception": false,
     "start_time": "2023-09-01T13:48:16.404877",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3b2d86bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T13:48:19.993608Z",
     "iopub.status.busy": "2023-09-01T13:48:19.992214Z",
     "iopub.status.idle": "2023-09-01T13:48:20.002010Z",
     "shell.execute_reply": "2023-09-01T13:48:20.000680Z"
    },
    "papermill": {
     "duration": 1.201756,
     "end_time": "2023-09-01T13:48:20.004601",
     "exception": false,
     "start_time": "2023-09-01T13:48:18.802845",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n!pip install bokeh\\n\\nfrom bokeh.plotting import figure\\nfrom bokeh.io import output_notebook, show, push_notebook\\nimport cv2\\nimport time\\noutput_notebook()\\n\\ncap = cv2.VideoCapture( \\'/kaggle/working/challenge.mp4\\' )\\nret, frame = cap.read()\\n\\nif ret == True:\\n    frame=cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA) # because Bokeh expects a RGBA image\\n    frame=cv2.flip(frame, -1) # because Bokeh flips vertically\\n    width=frame.shape[1]\\n    height=frame.shape[0]\\n    p = figure(x_range=(0,width), y_range=(0,height), output_backend=\"webgl\", width=width, height=height)\\n    myImage = p.image_rgba(image=[frame], x=0, y=0, dw=width, dh=height)\\n    show(p, notebook_handle=True)\\n    while True:\\n        ret, frame = cap.read()\\n        frame=cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)\\n        frame=cv2.flip(frame, -1)\\n        myImage.data_source.data[\\'image\\']=[frame]\\n        push_notebook()\\n        time.sleep(0.3)\\n'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "!pip install bokeh\n",
    "\n",
    "from bokeh.plotting import figure\n",
    "from bokeh.io import output_notebook, show, push_notebook\n",
    "import cv2\n",
    "import time\n",
    "output_notebook()\n",
    "\n",
    "cap = cv2.VideoCapture( '/kaggle/working/challenge.mp4' )\n",
    "ret, frame = cap.read()\n",
    "\n",
    "if ret == True:\n",
    "    frame=cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA) # because Bokeh expects a RGBA image\n",
    "    frame=cv2.flip(frame, -1) # because Bokeh flips vertically\n",
    "    width=frame.shape[1]\n",
    "    height=frame.shape[0]\n",
    "    p = figure(x_range=(0,width), y_range=(0,height), output_backend=\"webgl\", width=width, height=height)\n",
    "    myImage = p.image_rgba(image=[frame], x=0, y=0, dw=width, dh=height)\n",
    "    show(p, notebook_handle=True)\n",
    "    while True:\n",
    "        ret, frame = cap.read()\n",
    "        frame=cv2.cvtColor(frame, cv2.COLOR_BGR2RGBA)\n",
    "        frame=cv2.flip(frame, -1)\n",
    "        myImage.data_source.data['image']=[frame]\n",
    "        push_notebook()\n",
    "        time.sleep(0.3)\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a914c84e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-09-01T13:48:22.555026Z",
     "iopub.status.busy": "2023-09-01T13:48:22.554546Z",
     "iopub.status.idle": "2023-09-01T13:48:22.562765Z",
     "shell.execute_reply": "2023-09-01T13:48:22.561580Z"
    },
    "papermill": {
     "duration": 1.373259,
     "end_time": "2023-09-01T13:48:22.565062",
     "exception": false,
     "start_time": "2023-09-01T13:48:21.191803",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<video width=1024 controls>\n",
       "  <source src='/kaggle/working/challenge.mp4' type=\"video/mp4\">\n",
       "</video>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "HTML(\"\"\"\n",
    "<video width=1024 controls>\n",
    "  <source src='/kaggle/working/challenge.mp4' type=\"video/mp4\">\n",
    "</video>\n",
    "\"\"\")"
   ]
  }
 ],
 "kernelspec": {
  "display_name": "Python 3",
  "language": "python",
  "name": "python3"
 },
 "language_info": {
  "codemirror_mode": {
   "name": "ipython",
   "version": 3
  },
  "file_extension": ".py",
  "mimetype": "text/x-python",
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
  "version": "3.6.4"
 },
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.2"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 38167.328652,
   "end_time": "2023-09-01T13:48:27.071251",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-09-01T03:12:19.742599",
   "version": "2.4.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}