caijun0322_data_augmentation.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import cv2\n",
    "import random\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "import itertools\n",
    "\n",
    "from tqdm import tqdm\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "\n",
    "warnings.filterwarnings('ignore')\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入数据\n",
    "-  label 文件一共有 79572 行\n",
    "- 各种维度混合在一起\n",
    "- 我们的目的是切分开各种维度, 进行训练和模拟\n",
    "- 那么首先取出个标签的图片进行聚类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image_id</th>\n",
       "      <th>class</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Images/collar_design_labels/4d8a38b29930a403e5...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "      <td>nnynn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Images/collar_design_labels/bd0981f231180d2b00...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "      <td>nynnn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Images/collar_design_labels/26937e1724feadfe39...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "      <td>ynnnn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Images/collar_design_labels/cf4140ec542887270f...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "      <td>nynnn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Images/collar_design_labels/50644b2b9de045f2d1...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "      <td>nynnn</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            image_id                 class  \\\n",
       "0  Images/collar_design_labels/4d8a38b29930a403e5...  collar_design_labels   \n",
       "1  Images/collar_design_labels/bd0981f231180d2b00...  collar_design_labels   \n",
       "2  Images/collar_design_labels/26937e1724feadfe39...  collar_design_labels   \n",
       "3  Images/collar_design_labels/cf4140ec542887270f...  collar_design_labels   \n",
       "4  Images/collar_design_labels/50644b2b9de045f2d1...  collar_design_labels   \n",
       "\n",
       "   label  \n",
       "0  nnynn  \n",
       "1  nynnn  \n",
       "2  ynnnn  \n",
       "3  nynnn  \n",
       "4  nynnn  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = pd.read_csv('./Annotations/label.csv', header=None)\n",
    "df_train.columns = ['image_id', 'class', 'label']\n",
    "df_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "classes = ['collar_design_labels', 'neckline_design_labels', 'skirt_length_labels',\n",
    "          'sleeve_length_labels', 'neck_design_labels', 'coat_length_labels', 'lapel_design_labels',\n",
    "          'pant_length_labels']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pant_length_labels: 7460\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image_id</th>\n",
       "      <th>class</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Images/pant_length_labels/07264732b8dfa05ca485...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>ynnnnn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Images/pant_length_labels/ae01c534cddd89261c95...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>nnynnn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Images/pant_length_labels/7d51f1a23c93213e4652...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>nnnnny</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Images/pant_length_labels/5c9f7c834ae1c1daa3f5...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>nynnnn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Images/pant_length_labels/e1eb7a176c228107125d...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>nnnnyn</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            image_id               class  \\\n",
       "0  Images/pant_length_labels/07264732b8dfa05ca485...  pant_length_labels   \n",
       "1  Images/pant_length_labels/ae01c534cddd89261c95...  pant_length_labels   \n",
       "2  Images/pant_length_labels/7d51f1a23c93213e4652...  pant_length_labels   \n",
       "3  Images/pant_length_labels/5c9f7c834ae1c1daa3f5...  pant_length_labels   \n",
       "4  Images/pant_length_labels/e1eb7a176c228107125d...  pant_length_labels   \n",
       "\n",
       "    label  \n",
       "0  ynnnnn  \n",
       "1  nnynnn  \n",
       "2  nnnnny  \n",
       "3  nynnnn  \n",
       "4  nnnnyn  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cur_class = classes[7]\n",
    "df_load = df_train[(df_train['class'] == cur_class)].copy()\n",
    "df_load.reset_index(inplace=True)\n",
    "del df_load['index']\n",
    "\n",
    "print('{0}: {1}'.format(cur_class, len(df_load)))\n",
    "df_load.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n = len(df_load)\n",
    "n_class = len(df_load['label'][0])\n",
    "width = 299 # 定义图片大小\n",
    "\n",
    "X = np.zeros((n, width, width, 3), dtype=np.uint8)\n",
    "y = np.zeros((n, n_class), dtype=np.uint8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "./Images/pant_length_labels/07264732b8dfa05ca4857c71d2f9fb4b.jpg\n"
     ]
    }
   ],
   "source": [
    "print('./{0}'.format(df_load['image_id'][0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n = len(df_load)\n",
    "n_class = len(df_load['label'][0])\n",
    "width = 299 # 定义图片大小\n",
    "\n",
    "X = np.zeros((n, width, width, 3), dtype=np.uint8)\n",
    "y = np.zeros((n, n_class), dtype=np.uint8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 7460/7460 [00:48<00:00, 155.00it/s]\n"
     ]
    }
   ],
   "source": [
    "for i in tqdm(range(n)):\n",
    "    tmp_label = df_load['label'][i]\n",
    "    if len(tmp_label) > n_class:\n",
    "        print(df_load['image_id'][i])\n",
    "    X[i] = cv2.resize(cv2.imread('./{0}'.format(df_load['image_id'][i])), (width, width))\n",
    "    y[i][tmp_label.find('y')] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((7460, 299, 299, 3), (7460, 6))"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.shape, y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#plt.figure(figsize=(12, 7))\n",
    "#for i in range(8):\n",
    "#    random_index = random.randint(0, n-1)\n",
    "#    plt.subplot(2, 4, i+1)\n",
    "#    plt.imshow(X[random_index][:,:,::-1])\n",
    "#    plt.title(y[random_index])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 提取特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.layers import *\n",
    "from keras.models import *\n",
    "from keras.callbacks import *\n",
    "from keras.optimizers import *\n",
    "from keras.applications import *\n",
    "from keras.regularizers import *\n",
    "from keras.applications.inception_v3 import preprocess_input\n",
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "from keras.callbacks import ReduceLROnPlateau\n",
    "from keras.optimizers import RMSprop\n",
    "from keras import applications\n",
    "from keras.models import Model\n",
    "import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "width = 299 # 定义图片大小"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_model = InceptionV3(weights='imagenet', include_top=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def add_new_last_layer(base_model):\n",
    "  \"\"\"\n",
    "  添加最后的层\n",
    "  输入\n",
    "  base_model和分类数量\n",
    "  输出\n",
    "  新的keras的model\n",
    "  \"\"\"\n",
    "  x = base_model.output\n",
    "  x = GlobalAveragePooling2D()(x)\n",
    "  x = Dense(1024, activation='relu')(x) #new FC layer, random init\n",
    "  predictions = Dense(5, activation='softmax')(x) #new softmax layer\n",
    "  model = Model(input=base_model.input, output=predictions)\n",
    "  return model\n",
    "model = add_new_last_layer(base_model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "Layer inception_v3 has multiple inbound nodes, hence the notion of \"layer input\" is ill-defined. Use `get_input_at(node_index)` instead.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-39-8fd72c2e57ad>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDense\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mactivation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'softmax'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'softmax'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 10\u001b[0;31m \u001b[0mmodel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mModel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbase_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m/Users/apple/anaconda/lib/python3.6/site-packages/keras/engine/topology.py\u001b[0m in \u001b[0;36minput\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    938\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_inbound_nodes\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    939\u001b[0m             raise AttributeError('Layer ' + self.name +\n\u001b[0;32m--> 940\u001b[0;31m                                  \u001b[0;34m' has multiple inbound nodes, '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    941\u001b[0m                                  \u001b[0;34m'hence the notion of \"layer input\" '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    942\u001b[0m                                  \u001b[0;34m'is ill-defined. '\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: Layer inception_v3 has multiple inbound nodes, hence the notion of \"layer input\" is ill-defined. Use `get_input_at(node_index)` instead."
     ]
    }
   ],
   "source": [
    "inputs = Input((width, width, 3))\n",
    "\n",
    "x = inputs\n",
    "x = Lambda(preprocess_input, name='preprocessing')(x)\n",
    "x = base_model(x)\n",
    "x = GlobalAveragePooling2D()(x)\n",
    "x = Dropout(0.5)(x)\n",
    "x = Dense(5, activation='softmax', name='softmax')(x)\n",
    "\n",
    "model = Model(inputs, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "i = 0\n",
    "for layer in model.layers[:]:\n",
    "    i = i +1\n",
    "print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "cnn_model = InceptionResNetV2(include_top=False, input_shape=(width, width, 3), weights='imagenet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_4 (InputLayer)            (None, 299, 299, 3)  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_610 (Conv2D)             (None, 149, 149, 32) 864         input_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_610 (BatchN (None, 149, 149, 32) 96          conv2d_610[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_610 (Activation)     (None, 149, 149, 32) 0           batch_normalization_610[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_611 (Conv2D)             (None, 147, 147, 32) 9216        activation_610[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_611 (BatchN (None, 147, 147, 32) 96          conv2d_611[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_611 (Activation)     (None, 147, 147, 32) 0           batch_normalization_611[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_612 (Conv2D)             (None, 147, 147, 64) 18432       activation_611[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_612 (BatchN (None, 147, 147, 64) 192         conv2d_612[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_612 (Activation)     (None, 147, 147, 64) 0           batch_normalization_612[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_13 (MaxPooling2D) (None, 73, 73, 64)   0           activation_612[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_613 (Conv2D)             (None, 73, 73, 80)   5120        max_pooling2d_13[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_613 (BatchN (None, 73, 73, 80)   240         conv2d_613[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_613 (Activation)     (None, 73, 73, 80)   0           batch_normalization_613[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_614 (Conv2D)             (None, 71, 71, 192)  138240      activation_613[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_614 (BatchN (None, 71, 71, 192)  576         conv2d_614[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_614 (Activation)     (None, 71, 71, 192)  0           batch_normalization_614[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_14 (MaxPooling2D) (None, 35, 35, 192)  0           activation_614[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_618 (Conv2D)             (None, 35, 35, 64)   12288       max_pooling2d_14[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_618 (BatchN (None, 35, 35, 64)   192         conv2d_618[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_618 (Activation)     (None, 35, 35, 64)   0           batch_normalization_618[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_616 (Conv2D)             (None, 35, 35, 48)   9216        max_pooling2d_14[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_619 (Conv2D)             (None, 35, 35, 96)   55296       activation_618[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_616 (BatchN (None, 35, 35, 48)   144         conv2d_616[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_619 (BatchN (None, 35, 35, 96)   288         conv2d_619[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_616 (Activation)     (None, 35, 35, 48)   0           batch_normalization_616[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_619 (Activation)     (None, 35, 35, 96)   0           batch_normalization_619[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_4 (AveragePoo (None, 35, 35, 192)  0           max_pooling2d_14[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_615 (Conv2D)             (None, 35, 35, 96)   18432       max_pooling2d_14[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_617 (Conv2D)             (None, 35, 35, 64)   76800       activation_616[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_620 (Conv2D)             (None, 35, 35, 96)   82944       activation_619[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_621 (Conv2D)             (None, 35, 35, 64)   12288       average_pooling2d_4[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_615 (BatchN (None, 35, 35, 96)   288         conv2d_615[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_617 (BatchN (None, 35, 35, 64)   192         conv2d_617[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_620 (BatchN (None, 35, 35, 96)   288         conv2d_620[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_621 (BatchN (None, 35, 35, 64)   192         conv2d_621[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_615 (Activation)     (None, 35, 35, 96)   0           batch_normalization_615[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_617 (Activation)     (None, 35, 35, 64)   0           batch_normalization_617[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_620 (Activation)     (None, 35, 35, 96)   0           batch_normalization_620[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_621 (Activation)     (None, 35, 35, 64)   0           batch_normalization_621[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "mixed_5b (Concatenate)          (None, 35, 35, 320)  0           activation_615[0][0]             \n",
      "                                                                 activation_617[0][0]             \n",
      "                                                                 activation_620[0][0]             \n",
      "                                                                 activation_621[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_625 (Conv2D)             (None, 35, 35, 32)   10240       mixed_5b[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_625 (BatchN (None, 35, 35, 32)   96          conv2d_625[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_625 (Activation)     (None, 35, 35, 32)   0           batch_normalization_625[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_623 (Conv2D)             (None, 35, 35, 32)   10240       mixed_5b[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_626 (Conv2D)             (None, 35, 35, 48)   13824       activation_625[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_623 (BatchN (None, 35, 35, 32)   96          conv2d_623[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_626 (BatchN (None, 35, 35, 48)   144         conv2d_626[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_623 (Activation)     (None, 35, 35, 32)   0           batch_normalization_623[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_626 (Activation)     (None, 35, 35, 48)   0           batch_normalization_626[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_622 (Conv2D)             (None, 35, 35, 32)   10240       mixed_5b[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_624 (Conv2D)             (None, 35, 35, 32)   9216        activation_623[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_627 (Conv2D)             (None, 35, 35, 64)   27648       activation_626[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_622 (BatchN (None, 35, 35, 32)   96          conv2d_622[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_624 (BatchN (None, 35, 35, 32)   96          conv2d_624[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_627 (BatchN (None, 35, 35, 64)   192         conv2d_627[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_622 (Activation)     (None, 35, 35, 32)   0           batch_normalization_622[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_624 (Activation)     (None, 35, 35, 32)   0           batch_normalization_624[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_627 (Activation)     (None, 35, 35, 64)   0           batch_normalization_627[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_1_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_622[0][0]             \n",
      "                                                                 activation_624[0][0]             \n",
      "                                                                 activation_627[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_1_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_1_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_1 (Lambda)              (None, 35, 35, 320)  0           mixed_5b[0][0]                   \n",
      "                                                                 block35_1_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_1_ac (Activation)       (None, 35, 35, 320)  0           block35_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_631 (Conv2D)             (None, 35, 35, 32)   10240       block35_1_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_631 (BatchN (None, 35, 35, 32)   96          conv2d_631[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_631 (Activation)     (None, 35, 35, 32)   0           batch_normalization_631[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_629 (Conv2D)             (None, 35, 35, 32)   10240       block35_1_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_632 (Conv2D)             (None, 35, 35, 48)   13824       activation_631[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_629 (BatchN (None, 35, 35, 32)   96          conv2d_629[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_632 (BatchN (None, 35, 35, 48)   144         conv2d_632[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_629 (Activation)     (None, 35, 35, 32)   0           batch_normalization_629[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_632 (Activation)     (None, 35, 35, 48)   0           batch_normalization_632[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_628 (Conv2D)             (None, 35, 35, 32)   10240       block35_1_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_630 (Conv2D)             (None, 35, 35, 32)   9216        activation_629[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_633 (Conv2D)             (None, 35, 35, 64)   27648       activation_632[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_628 (BatchN (None, 35, 35, 32)   96          conv2d_628[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_630 (BatchN (None, 35, 35, 32)   96          conv2d_630[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_633 (BatchN (None, 35, 35, 64)   192         conv2d_633[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_628 (Activation)     (None, 35, 35, 32)   0           batch_normalization_628[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_630 (Activation)     (None, 35, 35, 32)   0           batch_normalization_630[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_633 (Activation)     (None, 35, 35, 64)   0           batch_normalization_633[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_2_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_628[0][0]             \n",
      "                                                                 activation_630[0][0]             \n",
      "                                                                 activation_633[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_2_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_2_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_2 (Lambda)              (None, 35, 35, 320)  0           block35_1_ac[0][0]               \n",
      "                                                                 block35_2_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_2_ac (Activation)       (None, 35, 35, 320)  0           block35_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_637 (Conv2D)             (None, 35, 35, 32)   10240       block35_2_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_637 (BatchN (None, 35, 35, 32)   96          conv2d_637[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_637 (Activation)     (None, 35, 35, 32)   0           batch_normalization_637[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_635 (Conv2D)             (None, 35, 35, 32)   10240       block35_2_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_638 (Conv2D)             (None, 35, 35, 48)   13824       activation_637[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_635 (BatchN (None, 35, 35, 32)   96          conv2d_635[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_638 (BatchN (None, 35, 35, 48)   144         conv2d_638[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_635 (Activation)     (None, 35, 35, 32)   0           batch_normalization_635[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_638 (Activation)     (None, 35, 35, 48)   0           batch_normalization_638[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_634 (Conv2D)             (None, 35, 35, 32)   10240       block35_2_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_636 (Conv2D)             (None, 35, 35, 32)   9216        activation_635[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_639 (Conv2D)             (None, 35, 35, 64)   27648       activation_638[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_634 (BatchN (None, 35, 35, 32)   96          conv2d_634[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_636 (BatchN (None, 35, 35, 32)   96          conv2d_636[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_639 (BatchN (None, 35, 35, 64)   192         conv2d_639[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_634 (Activation)     (None, 35, 35, 32)   0           batch_normalization_634[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_636 (Activation)     (None, 35, 35, 32)   0           batch_normalization_636[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_639 (Activation)     (None, 35, 35, 64)   0           batch_normalization_639[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_3_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_634[0][0]             \n",
      "                                                                 activation_636[0][0]             \n",
      "                                                                 activation_639[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_3_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_3_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_3 (Lambda)              (None, 35, 35, 320)  0           block35_2_ac[0][0]               \n",
      "                                                                 block35_3_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_3_ac (Activation)       (None, 35, 35, 320)  0           block35_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_643 (Conv2D)             (None, 35, 35, 32)   10240       block35_3_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_643 (BatchN (None, 35, 35, 32)   96          conv2d_643[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_643 (Activation)     (None, 35, 35, 32)   0           batch_normalization_643[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_641 (Conv2D)             (None, 35, 35, 32)   10240       block35_3_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_644 (Conv2D)             (None, 35, 35, 48)   13824       activation_643[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_641 (BatchN (None, 35, 35, 32)   96          conv2d_641[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_644 (BatchN (None, 35, 35, 48)   144         conv2d_644[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_641 (Activation)     (None, 35, 35, 32)   0           batch_normalization_641[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_644 (Activation)     (None, 35, 35, 48)   0           batch_normalization_644[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_640 (Conv2D)             (None, 35, 35, 32)   10240       block35_3_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_642 (Conv2D)             (None, 35, 35, 32)   9216        activation_641[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_645 (Conv2D)             (None, 35, 35, 64)   27648       activation_644[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_640 (BatchN (None, 35, 35, 32)   96          conv2d_640[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_642 (BatchN (None, 35, 35, 32)   96          conv2d_642[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_645 (BatchN (None, 35, 35, 64)   192         conv2d_645[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_640 (Activation)     (None, 35, 35, 32)   0           batch_normalization_640[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_642 (Activation)     (None, 35, 35, 32)   0           batch_normalization_642[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_645 (Activation)     (None, 35, 35, 64)   0           batch_normalization_645[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_4_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_640[0][0]             \n",
      "                                                                 activation_642[0][0]             \n",
      "                                                                 activation_645[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_4_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_4_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_4 (Lambda)              (None, 35, 35, 320)  0           block35_3_ac[0][0]               \n",
      "                                                                 block35_4_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_4_ac (Activation)       (None, 35, 35, 320)  0           block35_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_649 (Conv2D)             (None, 35, 35, 32)   10240       block35_4_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_649 (BatchN (None, 35, 35, 32)   96          conv2d_649[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_649 (Activation)     (None, 35, 35, 32)   0           batch_normalization_649[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_647 (Conv2D)             (None, 35, 35, 32)   10240       block35_4_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_650 (Conv2D)             (None, 35, 35, 48)   13824       activation_649[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_647 (BatchN (None, 35, 35, 32)   96          conv2d_647[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_650 (BatchN (None, 35, 35, 48)   144         conv2d_650[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_647 (Activation)     (None, 35, 35, 32)   0           batch_normalization_647[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_650 (Activation)     (None, 35, 35, 48)   0           batch_normalization_650[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_646 (Conv2D)             (None, 35, 35, 32)   10240       block35_4_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_648 (Conv2D)             (None, 35, 35, 32)   9216        activation_647[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_651 (Conv2D)             (None, 35, 35, 64)   27648       activation_650[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_646 (BatchN (None, 35, 35, 32)   96          conv2d_646[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_648 (BatchN (None, 35, 35, 32)   96          conv2d_648[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_651 (BatchN (None, 35, 35, 64)   192         conv2d_651[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_646 (Activation)     (None, 35, 35, 32)   0           batch_normalization_646[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_648 (Activation)     (None, 35, 35, 32)   0           batch_normalization_648[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_651 (Activation)     (None, 35, 35, 64)   0           batch_normalization_651[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_5_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_646[0][0]             \n",
      "                                                                 activation_648[0][0]             \n",
      "                                                                 activation_651[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_5_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_5_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_5 (Lambda)              (None, 35, 35, 320)  0           block35_4_ac[0][0]               \n",
      "                                                                 block35_5_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_5_ac (Activation)       (None, 35, 35, 320)  0           block35_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_655 (Conv2D)             (None, 35, 35, 32)   10240       block35_5_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_655 (BatchN (None, 35, 35, 32)   96          conv2d_655[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_655 (Activation)     (None, 35, 35, 32)   0           batch_normalization_655[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_653 (Conv2D)             (None, 35, 35, 32)   10240       block35_5_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_656 (Conv2D)             (None, 35, 35, 48)   13824       activation_655[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_653 (BatchN (None, 35, 35, 32)   96          conv2d_653[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_656 (BatchN (None, 35, 35, 48)   144         conv2d_656[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_653 (Activation)     (None, 35, 35, 32)   0           batch_normalization_653[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_656 (Activation)     (None, 35, 35, 48)   0           batch_normalization_656[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_652 (Conv2D)             (None, 35, 35, 32)   10240       block35_5_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_654 (Conv2D)             (None, 35, 35, 32)   9216        activation_653[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_657 (Conv2D)             (None, 35, 35, 64)   27648       activation_656[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_652 (BatchN (None, 35, 35, 32)   96          conv2d_652[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_654 (BatchN (None, 35, 35, 32)   96          conv2d_654[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_657 (BatchN (None, 35, 35, 64)   192         conv2d_657[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_652 (Activation)     (None, 35, 35, 32)   0           batch_normalization_652[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_654 (Activation)     (None, 35, 35, 32)   0           batch_normalization_654[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_657 (Activation)     (None, 35, 35, 64)   0           batch_normalization_657[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_6_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_652[0][0]             \n",
      "                                                                 activation_654[0][0]             \n",
      "                                                                 activation_657[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_6_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_6_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_6 (Lambda)              (None, 35, 35, 320)  0           block35_5_ac[0][0]               \n",
      "                                                                 block35_6_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_6_ac (Activation)       (None, 35, 35, 320)  0           block35_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_661 (Conv2D)             (None, 35, 35, 32)   10240       block35_6_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_661 (BatchN (None, 35, 35, 32)   96          conv2d_661[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_661 (Activation)     (None, 35, 35, 32)   0           batch_normalization_661[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_659 (Conv2D)             (None, 35, 35, 32)   10240       block35_6_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_662 (Conv2D)             (None, 35, 35, 48)   13824       activation_661[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_659 (BatchN (None, 35, 35, 32)   96          conv2d_659[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_662 (BatchN (None, 35, 35, 48)   144         conv2d_662[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_659 (Activation)     (None, 35, 35, 32)   0           batch_normalization_659[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_662 (Activation)     (None, 35, 35, 48)   0           batch_normalization_662[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_658 (Conv2D)             (None, 35, 35, 32)   10240       block35_6_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_660 (Conv2D)             (None, 35, 35, 32)   9216        activation_659[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_663 (Conv2D)             (None, 35, 35, 64)   27648       activation_662[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_658 (BatchN (None, 35, 35, 32)   96          conv2d_658[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_660 (BatchN (None, 35, 35, 32)   96          conv2d_660[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_663 (BatchN (None, 35, 35, 64)   192         conv2d_663[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_658 (Activation)     (None, 35, 35, 32)   0           batch_normalization_658[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_660 (Activation)     (None, 35, 35, 32)   0           batch_normalization_660[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_663 (Activation)     (None, 35, 35, 64)   0           batch_normalization_663[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_7_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_658[0][0]             \n",
      "                                                                 activation_660[0][0]             \n",
      "                                                                 activation_663[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_7_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_7_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_7 (Lambda)              (None, 35, 35, 320)  0           block35_6_ac[0][0]               \n",
      "                                                                 block35_7_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_7_ac (Activation)       (None, 35, 35, 320)  0           block35_7[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_667 (Conv2D)             (None, 35, 35, 32)   10240       block35_7_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_667 (BatchN (None, 35, 35, 32)   96          conv2d_667[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_667 (Activation)     (None, 35, 35, 32)   0           batch_normalization_667[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_665 (Conv2D)             (None, 35, 35, 32)   10240       block35_7_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_668 (Conv2D)             (None, 35, 35, 48)   13824       activation_667[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_665 (BatchN (None, 35, 35, 32)   96          conv2d_665[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_668 (BatchN (None, 35, 35, 48)   144         conv2d_668[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_665 (Activation)     (None, 35, 35, 32)   0           batch_normalization_665[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_668 (Activation)     (None, 35, 35, 48)   0           batch_normalization_668[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_664 (Conv2D)             (None, 35, 35, 32)   10240       block35_7_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_666 (Conv2D)             (None, 35, 35, 32)   9216        activation_665[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_669 (Conv2D)             (None, 35, 35, 64)   27648       activation_668[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_664 (BatchN (None, 35, 35, 32)   96          conv2d_664[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_666 (BatchN (None, 35, 35, 32)   96          conv2d_666[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_669 (BatchN (None, 35, 35, 64)   192         conv2d_669[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_664 (Activation)     (None, 35, 35, 32)   0           batch_normalization_664[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_666 (Activation)     (None, 35, 35, 32)   0           batch_normalization_666[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_669 (Activation)     (None, 35, 35, 64)   0           batch_normalization_669[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_8_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_664[0][0]             \n",
      "                                                                 activation_666[0][0]             \n",
      "                                                                 activation_669[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_8_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_8_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_8 (Lambda)              (None, 35, 35, 320)  0           block35_7_ac[0][0]               \n",
      "                                                                 block35_8_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_8_ac (Activation)       (None, 35, 35, 320)  0           block35_8[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_673 (Conv2D)             (None, 35, 35, 32)   10240       block35_8_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_673 (BatchN (None, 35, 35, 32)   96          conv2d_673[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_673 (Activation)     (None, 35, 35, 32)   0           batch_normalization_673[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_671 (Conv2D)             (None, 35, 35, 32)   10240       block35_8_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_674 (Conv2D)             (None, 35, 35, 48)   13824       activation_673[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_671 (BatchN (None, 35, 35, 32)   96          conv2d_671[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_674 (BatchN (None, 35, 35, 48)   144         conv2d_674[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_671 (Activation)     (None, 35, 35, 32)   0           batch_normalization_671[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_674 (Activation)     (None, 35, 35, 48)   0           batch_normalization_674[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_670 (Conv2D)             (None, 35, 35, 32)   10240       block35_8_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_672 (Conv2D)             (None, 35, 35, 32)   9216        activation_671[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_675 (Conv2D)             (None, 35, 35, 64)   27648       activation_674[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_670 (BatchN (None, 35, 35, 32)   96          conv2d_670[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_672 (BatchN (None, 35, 35, 32)   96          conv2d_672[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_675 (BatchN (None, 35, 35, 64)   192         conv2d_675[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_670 (Activation)     (None, 35, 35, 32)   0           batch_normalization_670[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_672 (Activation)     (None, 35, 35, 32)   0           batch_normalization_672[0][0]    \n",
      "__________________________________________________________________________________________________\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "activation_675 (Activation)     (None, 35, 35, 64)   0           batch_normalization_675[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_9_mixed (Concatenate)   (None, 35, 35, 128)  0           activation_670[0][0]             \n",
      "                                                                 activation_672[0][0]             \n",
      "                                                                 activation_675[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_9_conv (Conv2D)         (None, 35, 35, 320)  41280       block35_9_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_9 (Lambda)              (None, 35, 35, 320)  0           block35_8_ac[0][0]               \n",
      "                                                                 block35_9_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_9_ac (Activation)       (None, 35, 35, 320)  0           block35_9[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_679 (Conv2D)             (None, 35, 35, 32)   10240       block35_9_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_679 (BatchN (None, 35, 35, 32)   96          conv2d_679[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_679 (Activation)     (None, 35, 35, 32)   0           batch_normalization_679[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_677 (Conv2D)             (None, 35, 35, 32)   10240       block35_9_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_680 (Conv2D)             (None, 35, 35, 48)   13824       activation_679[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_677 (BatchN (None, 35, 35, 32)   96          conv2d_677[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_680 (BatchN (None, 35, 35, 48)   144         conv2d_680[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_677 (Activation)     (None, 35, 35, 32)   0           batch_normalization_677[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_680 (Activation)     (None, 35, 35, 48)   0           batch_normalization_680[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_676 (Conv2D)             (None, 35, 35, 32)   10240       block35_9_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_678 (Conv2D)             (None, 35, 35, 32)   9216        activation_677[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_681 (Conv2D)             (None, 35, 35, 64)   27648       activation_680[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_676 (BatchN (None, 35, 35, 32)   96          conv2d_676[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_678 (BatchN (None, 35, 35, 32)   96          conv2d_678[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_681 (BatchN (None, 35, 35, 64)   192         conv2d_681[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_676 (Activation)     (None, 35, 35, 32)   0           batch_normalization_676[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_678 (Activation)     (None, 35, 35, 32)   0           batch_normalization_678[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_681 (Activation)     (None, 35, 35, 64)   0           batch_normalization_681[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block35_10_mixed (Concatenate)  (None, 35, 35, 128)  0           activation_676[0][0]             \n",
      "                                                                 activation_678[0][0]             \n",
      "                                                                 activation_681[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block35_10_conv (Conv2D)        (None, 35, 35, 320)  41280       block35_10_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block35_10 (Lambda)             (None, 35, 35, 320)  0           block35_9_ac[0][0]               \n",
      "                                                                 block35_10_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block35_10_ac (Activation)      (None, 35, 35, 320)  0           block35_10[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_683 (Conv2D)             (None, 35, 35, 256)  81920       block35_10_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_683 (BatchN (None, 35, 35, 256)  768         conv2d_683[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_683 (Activation)     (None, 35, 35, 256)  0           batch_normalization_683[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_684 (Conv2D)             (None, 35, 35, 256)  589824      activation_683[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_684 (BatchN (None, 35, 35, 256)  768         conv2d_684[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_684 (Activation)     (None, 35, 35, 256)  0           batch_normalization_684[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_682 (Conv2D)             (None, 17, 17, 384)  1105920     block35_10_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_685 (Conv2D)             (None, 17, 17, 384)  884736      activation_684[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_682 (BatchN (None, 17, 17, 384)  1152        conv2d_682[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_685 (BatchN (None, 17, 17, 384)  1152        conv2d_685[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_682 (Activation)     (None, 17, 17, 384)  0           batch_normalization_682[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_685 (Activation)     (None, 17, 17, 384)  0           batch_normalization_685[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_15 (MaxPooling2D) (None, 17, 17, 320)  0           block35_10_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "mixed_6a (Concatenate)          (None, 17, 17, 1088) 0           activation_682[0][0]             \n",
      "                                                                 activation_685[0][0]             \n",
      "                                                                 max_pooling2d_15[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_687 (Conv2D)             (None, 17, 17, 128)  139264      mixed_6a[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_687 (BatchN (None, 17, 17, 128)  384         conv2d_687[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_687 (Activation)     (None, 17, 17, 128)  0           batch_normalization_687[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_688 (Conv2D)             (None, 17, 17, 160)  143360      activation_687[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_688 (BatchN (None, 17, 17, 160)  480         conv2d_688[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_688 (Activation)     (None, 17, 17, 160)  0           batch_normalization_688[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_686 (Conv2D)             (None, 17, 17, 192)  208896      mixed_6a[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_689 (Conv2D)             (None, 17, 17, 192)  215040      activation_688[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_686 (BatchN (None, 17, 17, 192)  576         conv2d_686[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_689 (BatchN (None, 17, 17, 192)  576         conv2d_689[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_686 (Activation)     (None, 17, 17, 192)  0           batch_normalization_686[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_689 (Activation)     (None, 17, 17, 192)  0           batch_normalization_689[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_1_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_686[0][0]             \n",
      "                                                                 activation_689[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_1_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_1_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_1 (Lambda)              (None, 17, 17, 1088) 0           mixed_6a[0][0]                   \n",
      "                                                                 block17_1_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_1_ac (Activation)       (None, 17, 17, 1088) 0           block17_1[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_691 (Conv2D)             (None, 17, 17, 128)  139264      block17_1_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_691 (BatchN (None, 17, 17, 128)  384         conv2d_691[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_691 (Activation)     (None, 17, 17, 128)  0           batch_normalization_691[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_692 (Conv2D)             (None, 17, 17, 160)  143360      activation_691[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_692 (BatchN (None, 17, 17, 160)  480         conv2d_692[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_692 (Activation)     (None, 17, 17, 160)  0           batch_normalization_692[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_690 (Conv2D)             (None, 17, 17, 192)  208896      block17_1_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_693 (Conv2D)             (None, 17, 17, 192)  215040      activation_692[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_690 (BatchN (None, 17, 17, 192)  576         conv2d_690[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_693 (BatchN (None, 17, 17, 192)  576         conv2d_693[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_690 (Activation)     (None, 17, 17, 192)  0           batch_normalization_690[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_693 (Activation)     (None, 17, 17, 192)  0           batch_normalization_693[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_2_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_690[0][0]             \n",
      "                                                                 activation_693[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_2_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_2_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_2 (Lambda)              (None, 17, 17, 1088) 0           block17_1_ac[0][0]               \n",
      "                                                                 block17_2_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_2_ac (Activation)       (None, 17, 17, 1088) 0           block17_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_695 (Conv2D)             (None, 17, 17, 128)  139264      block17_2_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_695 (BatchN (None, 17, 17, 128)  384         conv2d_695[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_695 (Activation)     (None, 17, 17, 128)  0           batch_normalization_695[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_696 (Conv2D)             (None, 17, 17, 160)  143360      activation_695[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_696 (BatchN (None, 17, 17, 160)  480         conv2d_696[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_696 (Activation)     (None, 17, 17, 160)  0           batch_normalization_696[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_694 (Conv2D)             (None, 17, 17, 192)  208896      block17_2_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_697 (Conv2D)             (None, 17, 17, 192)  215040      activation_696[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_694 (BatchN (None, 17, 17, 192)  576         conv2d_694[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_697 (BatchN (None, 17, 17, 192)  576         conv2d_697[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_694 (Activation)     (None, 17, 17, 192)  0           batch_normalization_694[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_697 (Activation)     (None, 17, 17, 192)  0           batch_normalization_697[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_3_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_694[0][0]             \n",
      "                                                                 activation_697[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_3_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_3_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_3 (Lambda)              (None, 17, 17, 1088) 0           block17_2_ac[0][0]               \n",
      "                                                                 block17_3_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_3_ac (Activation)       (None, 17, 17, 1088) 0           block17_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_699 (Conv2D)             (None, 17, 17, 128)  139264      block17_3_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_699 (BatchN (None, 17, 17, 128)  384         conv2d_699[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_699 (Activation)     (None, 17, 17, 128)  0           batch_normalization_699[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_700 (Conv2D)             (None, 17, 17, 160)  143360      activation_699[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_700 (BatchN (None, 17, 17, 160)  480         conv2d_700[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_700 (Activation)     (None, 17, 17, 160)  0           batch_normalization_700[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_698 (Conv2D)             (None, 17, 17, 192)  208896      block17_3_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_701 (Conv2D)             (None, 17, 17, 192)  215040      activation_700[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_698 (BatchN (None, 17, 17, 192)  576         conv2d_698[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_701 (BatchN (None, 17, 17, 192)  576         conv2d_701[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_698 (Activation)     (None, 17, 17, 192)  0           batch_normalization_698[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_701 (Activation)     (None, 17, 17, 192)  0           batch_normalization_701[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_4_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_698[0][0]             \n",
      "                                                                 activation_701[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_4_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_4_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_4 (Lambda)              (None, 17, 17, 1088) 0           block17_3_ac[0][0]               \n",
      "                                                                 block17_4_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_4_ac (Activation)       (None, 17, 17, 1088) 0           block17_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_703 (Conv2D)             (None, 17, 17, 128)  139264      block17_4_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_703 (BatchN (None, 17, 17, 128)  384         conv2d_703[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_703 (Activation)     (None, 17, 17, 128)  0           batch_normalization_703[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_704 (Conv2D)             (None, 17, 17, 160)  143360      activation_703[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_704 (BatchN (None, 17, 17, 160)  480         conv2d_704[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_704 (Activation)     (None, 17, 17, 160)  0           batch_normalization_704[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_702 (Conv2D)             (None, 17, 17, 192)  208896      block17_4_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_705 (Conv2D)             (None, 17, 17, 192)  215040      activation_704[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_702 (BatchN (None, 17, 17, 192)  576         conv2d_702[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_705 (BatchN (None, 17, 17, 192)  576         conv2d_705[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_702 (Activation)     (None, 17, 17, 192)  0           batch_normalization_702[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_705 (Activation)     (None, 17, 17, 192)  0           batch_normalization_705[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_5_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_702[0][0]             \n",
      "                                                                 activation_705[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_5_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_5_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_5 (Lambda)              (None, 17, 17, 1088) 0           block17_4_ac[0][0]               \n",
      "                                                                 block17_5_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_5_ac (Activation)       (None, 17, 17, 1088) 0           block17_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_707 (Conv2D)             (None, 17, 17, 128)  139264      block17_5_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_707 (BatchN (None, 17, 17, 128)  384         conv2d_707[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_707 (Activation)     (None, 17, 17, 128)  0           batch_normalization_707[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_708 (Conv2D)             (None, 17, 17, 160)  143360      activation_707[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_708 (BatchN (None, 17, 17, 160)  480         conv2d_708[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_708 (Activation)     (None, 17, 17, 160)  0           batch_normalization_708[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_706 (Conv2D)             (None, 17, 17, 192)  208896      block17_5_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_709 (Conv2D)             (None, 17, 17, 192)  215040      activation_708[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_706 (BatchN (None, 17, 17, 192)  576         conv2d_706[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_709 (BatchN (None, 17, 17, 192)  576         conv2d_709[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_706 (Activation)     (None, 17, 17, 192)  0           batch_normalization_706[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_709 (Activation)     (None, 17, 17, 192)  0           batch_normalization_709[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_6_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_706[0][0]             \n",
      "                                                                 activation_709[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_6_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_6_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_6 (Lambda)              (None, 17, 17, 1088) 0           block17_5_ac[0][0]               \n",
      "                                                                 block17_6_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_6_ac (Activation)       (None, 17, 17, 1088) 0           block17_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_711 (Conv2D)             (None, 17, 17, 128)  139264      block17_6_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_711 (BatchN (None, 17, 17, 128)  384         conv2d_711[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_711 (Activation)     (None, 17, 17, 128)  0           batch_normalization_711[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_712 (Conv2D)             (None, 17, 17, 160)  143360      activation_711[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_712 (BatchN (None, 17, 17, 160)  480         conv2d_712[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_712 (Activation)     (None, 17, 17, 160)  0           batch_normalization_712[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_710 (Conv2D)             (None, 17, 17, 192)  208896      block17_6_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_713 (Conv2D)             (None, 17, 17, 192)  215040      activation_712[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_710 (BatchN (None, 17, 17, 192)  576         conv2d_710[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_713 (BatchN (None, 17, 17, 192)  576         conv2d_713[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_710 (Activation)     (None, 17, 17, 192)  0           batch_normalization_710[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_713 (Activation)     (None, 17, 17, 192)  0           batch_normalization_713[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_7_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_710[0][0]             \n",
      "                                                                 activation_713[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_7_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_7_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_7 (Lambda)              (None, 17, 17, 1088) 0           block17_6_ac[0][0]               \n",
      "                                                                 block17_7_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_7_ac (Activation)       (None, 17, 17, 1088) 0           block17_7[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_715 (Conv2D)             (None, 17, 17, 128)  139264      block17_7_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_715 (BatchN (None, 17, 17, 128)  384         conv2d_715[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_715 (Activation)     (None, 17, 17, 128)  0           batch_normalization_715[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_716 (Conv2D)             (None, 17, 17, 160)  143360      activation_715[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_716 (BatchN (None, 17, 17, 160)  480         conv2d_716[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_716 (Activation)     (None, 17, 17, 160)  0           batch_normalization_716[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_714 (Conv2D)             (None, 17, 17, 192)  208896      block17_7_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_717 (Conv2D)             (None, 17, 17, 192)  215040      activation_716[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_714 (BatchN (None, 17, 17, 192)  576         conv2d_714[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_717 (BatchN (None, 17, 17, 192)  576         conv2d_717[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_714 (Activation)     (None, 17, 17, 192)  0           batch_normalization_714[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_717 (Activation)     (None, 17, 17, 192)  0           batch_normalization_717[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_8_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_714[0][0]             \n",
      "                                                                 activation_717[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_8_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_8_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_8 (Lambda)              (None, 17, 17, 1088) 0           block17_7_ac[0][0]               \n",
      "                                                                 block17_8_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_8_ac (Activation)       (None, 17, 17, 1088) 0           block17_8[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_719 (Conv2D)             (None, 17, 17, 128)  139264      block17_8_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_719 (BatchN (None, 17, 17, 128)  384         conv2d_719[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_719 (Activation)     (None, 17, 17, 128)  0           batch_normalization_719[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_720 (Conv2D)             (None, 17, 17, 160)  143360      activation_719[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_720 (BatchN (None, 17, 17, 160)  480         conv2d_720[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_720 (Activation)     (None, 17, 17, 160)  0           batch_normalization_720[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_718 (Conv2D)             (None, 17, 17, 192)  208896      block17_8_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_721 (Conv2D)             (None, 17, 17, 192)  215040      activation_720[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_718 (BatchN (None, 17, 17, 192)  576         conv2d_718[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_721 (BatchN (None, 17, 17, 192)  576         conv2d_721[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_718 (Activation)     (None, 17, 17, 192)  0           batch_normalization_718[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_721 (Activation)     (None, 17, 17, 192)  0           batch_normalization_721[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_9_mixed (Concatenate)   (None, 17, 17, 384)  0           activation_718[0][0]             \n",
      "                                                                 activation_721[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_9_conv (Conv2D)         (None, 17, 17, 1088) 418880      block17_9_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_9 (Lambda)              (None, 17, 17, 1088) 0           block17_8_ac[0][0]               \n",
      "                                                                 block17_9_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_9_ac (Activation)       (None, 17, 17, 1088) 0           block17_9[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_723 (Conv2D)             (None, 17, 17, 128)  139264      block17_9_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_723 (BatchN (None, 17, 17, 128)  384         conv2d_723[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_723 (Activation)     (None, 17, 17, 128)  0           batch_normalization_723[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_724 (Conv2D)             (None, 17, 17, 160)  143360      activation_723[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_724 (BatchN (None, 17, 17, 160)  480         conv2d_724[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_724 (Activation)     (None, 17, 17, 160)  0           batch_normalization_724[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_722 (Conv2D)             (None, 17, 17, 192)  208896      block17_9_ac[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_725 (Conv2D)             (None, 17, 17, 192)  215040      activation_724[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_722 (BatchN (None, 17, 17, 192)  576         conv2d_722[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_725 (BatchN (None, 17, 17, 192)  576         conv2d_725[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_722 (Activation)     (None, 17, 17, 192)  0           batch_normalization_722[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_725 (Activation)     (None, 17, 17, 192)  0           batch_normalization_725[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_10_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_722[0][0]             \n",
      "                                                                 activation_725[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_10_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_10_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_10 (Lambda)             (None, 17, 17, 1088) 0           block17_9_ac[0][0]               \n",
      "                                                                 block17_10_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_10_ac (Activation)      (None, 17, 17, 1088) 0           block17_10[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_727 (Conv2D)             (None, 17, 17, 128)  139264      block17_10_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_727 (BatchN (None, 17, 17, 128)  384         conv2d_727[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_727 (Activation)     (None, 17, 17, 128)  0           batch_normalization_727[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_728 (Conv2D)             (None, 17, 17, 160)  143360      activation_727[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_728 (BatchN (None, 17, 17, 160)  480         conv2d_728[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_728 (Activation)     (None, 17, 17, 160)  0           batch_normalization_728[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_726 (Conv2D)             (None, 17, 17, 192)  208896      block17_10_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_729 (Conv2D)             (None, 17, 17, 192)  215040      activation_728[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_726 (BatchN (None, 17, 17, 192)  576         conv2d_726[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_729 (BatchN (None, 17, 17, 192)  576         conv2d_729[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_726 (Activation)     (None, 17, 17, 192)  0           batch_normalization_726[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_729 (Activation)     (None, 17, 17, 192)  0           batch_normalization_729[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_11_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_726[0][0]             \n",
      "                                                                 activation_729[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_11_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_11_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_11 (Lambda)             (None, 17, 17, 1088) 0           block17_10_ac[0][0]              \n",
      "                                                                 block17_11_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_11_ac (Activation)      (None, 17, 17, 1088) 0           block17_11[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_731 (Conv2D)             (None, 17, 17, 128)  139264      block17_11_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_731 (BatchN (None, 17, 17, 128)  384         conv2d_731[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_731 (Activation)     (None, 17, 17, 128)  0           batch_normalization_731[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_732 (Conv2D)             (None, 17, 17, 160)  143360      activation_731[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_732 (BatchN (None, 17, 17, 160)  480         conv2d_732[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_732 (Activation)     (None, 17, 17, 160)  0           batch_normalization_732[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_730 (Conv2D)             (None, 17, 17, 192)  208896      block17_11_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_733 (Conv2D)             (None, 17, 17, 192)  215040      activation_732[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_730 (BatchN (None, 17, 17, 192)  576         conv2d_730[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_733 (BatchN (None, 17, 17, 192)  576         conv2d_733[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_730 (Activation)     (None, 17, 17, 192)  0           batch_normalization_730[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_733 (Activation)     (None, 17, 17, 192)  0           batch_normalization_733[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_12_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_730[0][0]             \n",
      "                                                                 activation_733[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_12_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_12_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_12 (Lambda)             (None, 17, 17, 1088) 0           block17_11_ac[0][0]              \n",
      "                                                                 block17_12_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_12_ac (Activation)      (None, 17, 17, 1088) 0           block17_12[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_735 (Conv2D)             (None, 17, 17, 128)  139264      block17_12_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_735 (BatchN (None, 17, 17, 128)  384         conv2d_735[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_735 (Activation)     (None, 17, 17, 128)  0           batch_normalization_735[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_736 (Conv2D)             (None, 17, 17, 160)  143360      activation_735[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_736 (BatchN (None, 17, 17, 160)  480         conv2d_736[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_736 (Activation)     (None, 17, 17, 160)  0           batch_normalization_736[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_734 (Conv2D)             (None, 17, 17, 192)  208896      block17_12_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_737 (Conv2D)             (None, 17, 17, 192)  215040      activation_736[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_734 (BatchN (None, 17, 17, 192)  576         conv2d_734[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_737 (BatchN (None, 17, 17, 192)  576         conv2d_737[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_734 (Activation)     (None, 17, 17, 192)  0           batch_normalization_734[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_737 (Activation)     (None, 17, 17, 192)  0           batch_normalization_737[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_13_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_734[0][0]             \n",
      "                                                                 activation_737[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_13_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_13_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_13 (Lambda)             (None, 17, 17, 1088) 0           block17_12_ac[0][0]              \n",
      "                                                                 block17_13_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_13_ac (Activation)      (None, 17, 17, 1088) 0           block17_13[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_739 (Conv2D)             (None, 17, 17, 128)  139264      block17_13_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_739 (BatchN (None, 17, 17, 128)  384         conv2d_739[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_739 (Activation)     (None, 17, 17, 128)  0           batch_normalization_739[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_740 (Conv2D)             (None, 17, 17, 160)  143360      activation_739[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_740 (BatchN (None, 17, 17, 160)  480         conv2d_740[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_740 (Activation)     (None, 17, 17, 160)  0           batch_normalization_740[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_738 (Conv2D)             (None, 17, 17, 192)  208896      block17_13_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_741 (Conv2D)             (None, 17, 17, 192)  215040      activation_740[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_738 (BatchN (None, 17, 17, 192)  576         conv2d_738[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_741 (BatchN (None, 17, 17, 192)  576         conv2d_741[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_738 (Activation)     (None, 17, 17, 192)  0           batch_normalization_738[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_741 (Activation)     (None, 17, 17, 192)  0           batch_normalization_741[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_14_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_738[0][0]             \n",
      "                                                                 activation_741[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_14_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_14_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_14 (Lambda)             (None, 17, 17, 1088) 0           block17_13_ac[0][0]              \n",
      "                                                                 block17_14_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_14_ac (Activation)      (None, 17, 17, 1088) 0           block17_14[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_743 (Conv2D)             (None, 17, 17, 128)  139264      block17_14_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_743 (BatchN (None, 17, 17, 128)  384         conv2d_743[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_743 (Activation)     (None, 17, 17, 128)  0           batch_normalization_743[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_744 (Conv2D)             (None, 17, 17, 160)  143360      activation_743[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_744 (BatchN (None, 17, 17, 160)  480         conv2d_744[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_744 (Activation)     (None, 17, 17, 160)  0           batch_normalization_744[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_742 (Conv2D)             (None, 17, 17, 192)  208896      block17_14_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_745 (Conv2D)             (None, 17, 17, 192)  215040      activation_744[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_742 (BatchN (None, 17, 17, 192)  576         conv2d_742[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_745 (BatchN (None, 17, 17, 192)  576         conv2d_745[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_742 (Activation)     (None, 17, 17, 192)  0           batch_normalization_742[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_745 (Activation)     (None, 17, 17, 192)  0           batch_normalization_745[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_15_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_742[0][0]             \n",
      "                                                                 activation_745[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_15_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_15_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_15 (Lambda)             (None, 17, 17, 1088) 0           block17_14_ac[0][0]              \n",
      "                                                                 block17_15_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_15_ac (Activation)      (None, 17, 17, 1088) 0           block17_15[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_747 (Conv2D)             (None, 17, 17, 128)  139264      block17_15_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_747 (BatchN (None, 17, 17, 128)  384         conv2d_747[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_747 (Activation)     (None, 17, 17, 128)  0           batch_normalization_747[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_748 (Conv2D)             (None, 17, 17, 160)  143360      activation_747[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_748 (BatchN (None, 17, 17, 160)  480         conv2d_748[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_748 (Activation)     (None, 17, 17, 160)  0           batch_normalization_748[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_746 (Conv2D)             (None, 17, 17, 192)  208896      block17_15_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_749 (Conv2D)             (None, 17, 17, 192)  215040      activation_748[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_746 (BatchN (None, 17, 17, 192)  576         conv2d_746[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_749 (BatchN (None, 17, 17, 192)  576         conv2d_749[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_746 (Activation)     (None, 17, 17, 192)  0           batch_normalization_746[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_749 (Activation)     (None, 17, 17, 192)  0           batch_normalization_749[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_16_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_746[0][0]             \n",
      "                                                                 activation_749[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_16_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_16_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_16 (Lambda)             (None, 17, 17, 1088) 0           block17_15_ac[0][0]              \n",
      "                                                                 block17_16_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_16_ac (Activation)      (None, 17, 17, 1088) 0           block17_16[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_751 (Conv2D)             (None, 17, 17, 128)  139264      block17_16_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_751 (BatchN (None, 17, 17, 128)  384         conv2d_751[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_751 (Activation)     (None, 17, 17, 128)  0           batch_normalization_751[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_752 (Conv2D)             (None, 17, 17, 160)  143360      activation_751[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_752 (BatchN (None, 17, 17, 160)  480         conv2d_752[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_752 (Activation)     (None, 17, 17, 160)  0           batch_normalization_752[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_750 (Conv2D)             (None, 17, 17, 192)  208896      block17_16_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_753 (Conv2D)             (None, 17, 17, 192)  215040      activation_752[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_750 (BatchN (None, 17, 17, 192)  576         conv2d_750[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_753 (BatchN (None, 17, 17, 192)  576         conv2d_753[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_750 (Activation)     (None, 17, 17, 192)  0           batch_normalization_750[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_753 (Activation)     (None, 17, 17, 192)  0           batch_normalization_753[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_17_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_750[0][0]             \n",
      "                                                                 activation_753[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_17_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_17_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_17 (Lambda)             (None, 17, 17, 1088) 0           block17_16_ac[0][0]              \n",
      "                                                                 block17_17_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_17_ac (Activation)      (None, 17, 17, 1088) 0           block17_17[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_755 (Conv2D)             (None, 17, 17, 128)  139264      block17_17_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_755 (BatchN (None, 17, 17, 128)  384         conv2d_755[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_755 (Activation)     (None, 17, 17, 128)  0           batch_normalization_755[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_756 (Conv2D)             (None, 17, 17, 160)  143360      activation_755[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_756 (BatchN (None, 17, 17, 160)  480         conv2d_756[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_756 (Activation)     (None, 17, 17, 160)  0           batch_normalization_756[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_754 (Conv2D)             (None, 17, 17, 192)  208896      block17_17_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_757 (Conv2D)             (None, 17, 17, 192)  215040      activation_756[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_754 (BatchN (None, 17, 17, 192)  576         conv2d_754[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_757 (BatchN (None, 17, 17, 192)  576         conv2d_757[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_754 (Activation)     (None, 17, 17, 192)  0           batch_normalization_754[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_757 (Activation)     (None, 17, 17, 192)  0           batch_normalization_757[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_18_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_754[0][0]             \n",
      "                                                                 activation_757[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_18_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_18_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_18 (Lambda)             (None, 17, 17, 1088) 0           block17_17_ac[0][0]              \n",
      "                                                                 block17_18_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_18_ac (Activation)      (None, 17, 17, 1088) 0           block17_18[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_759 (Conv2D)             (None, 17, 17, 128)  139264      block17_18_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_759 (BatchN (None, 17, 17, 128)  384         conv2d_759[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_759 (Activation)     (None, 17, 17, 128)  0           batch_normalization_759[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_760 (Conv2D)             (None, 17, 17, 160)  143360      activation_759[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_760 (BatchN (None, 17, 17, 160)  480         conv2d_760[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_760 (Activation)     (None, 17, 17, 160)  0           batch_normalization_760[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_758 (Conv2D)             (None, 17, 17, 192)  208896      block17_18_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_761 (Conv2D)             (None, 17, 17, 192)  215040      activation_760[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_758 (BatchN (None, 17, 17, 192)  576         conv2d_758[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_761 (BatchN (None, 17, 17, 192)  576         conv2d_761[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_758 (Activation)     (None, 17, 17, 192)  0           batch_normalization_758[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_761 (Activation)     (None, 17, 17, 192)  0           batch_normalization_761[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_19_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_758[0][0]             \n",
      "                                                                 activation_761[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_19_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_19_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_19 (Lambda)             (None, 17, 17, 1088) 0           block17_18_ac[0][0]              \n",
      "                                                                 block17_19_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_19_ac (Activation)      (None, 17, 17, 1088) 0           block17_19[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_763 (Conv2D)             (None, 17, 17, 128)  139264      block17_19_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_763 (BatchN (None, 17, 17, 128)  384         conv2d_763[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_763 (Activation)     (None, 17, 17, 128)  0           batch_normalization_763[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_764 (Conv2D)             (None, 17, 17, 160)  143360      activation_763[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_764 (BatchN (None, 17, 17, 160)  480         conv2d_764[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_764 (Activation)     (None, 17, 17, 160)  0           batch_normalization_764[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_762 (Conv2D)             (None, 17, 17, 192)  208896      block17_19_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_765 (Conv2D)             (None, 17, 17, 192)  215040      activation_764[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_762 (BatchN (None, 17, 17, 192)  576         conv2d_762[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_765 (BatchN (None, 17, 17, 192)  576         conv2d_765[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_762 (Activation)     (None, 17, 17, 192)  0           batch_normalization_762[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_765 (Activation)     (None, 17, 17, 192)  0           batch_normalization_765[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block17_20_mixed (Concatenate)  (None, 17, 17, 384)  0           activation_762[0][0]             \n",
      "                                                                 activation_765[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block17_20_conv (Conv2D)        (None, 17, 17, 1088) 418880      block17_20_mixed[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "block17_20 (Lambda)             (None, 17, 17, 1088) 0           block17_19_ac[0][0]              \n",
      "                                                                 block17_20_conv[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block17_20_ac (Activation)      (None, 17, 17, 1088) 0           block17_20[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_770 (Conv2D)             (None, 17, 17, 256)  278528      block17_20_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_770 (BatchN (None, 17, 17, 256)  768         conv2d_770[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_770 (Activation)     (None, 17, 17, 256)  0           batch_normalization_770[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_766 (Conv2D)             (None, 17, 17, 256)  278528      block17_20_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_768 (Conv2D)             (None, 17, 17, 256)  278528      block17_20_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_771 (Conv2D)             (None, 17, 17, 288)  663552      activation_770[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_766 (BatchN (None, 17, 17, 256)  768         conv2d_766[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_768 (BatchN (None, 17, 17, 256)  768         conv2d_768[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_771 (BatchN (None, 17, 17, 288)  864         conv2d_771[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_766 (Activation)     (None, 17, 17, 256)  0           batch_normalization_766[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_768 (Activation)     (None, 17, 17, 256)  0           batch_normalization_768[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_771 (Activation)     (None, 17, 17, 288)  0           batch_normalization_771[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_767 (Conv2D)             (None, 8, 8, 384)    884736      activation_766[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_769 (Conv2D)             (None, 8, 8, 288)    663552      activation_768[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_772 (Conv2D)             (None, 8, 8, 320)    829440      activation_771[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_767 (BatchN (None, 8, 8, 384)    1152        conv2d_767[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_769 (BatchN (None, 8, 8, 288)    864         conv2d_769[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_772 (BatchN (None, 8, 8, 320)    960         conv2d_772[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_767 (Activation)     (None, 8, 8, 384)    0           batch_normalization_767[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_769 (Activation)     (None, 8, 8, 288)    0           batch_normalization_769[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_772 (Activation)     (None, 8, 8, 320)    0           batch_normalization_772[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_16 (MaxPooling2D) (None, 8, 8, 1088)   0           block17_20_ac[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "mixed_7a (Concatenate)          (None, 8, 8, 2080)   0           activation_767[0][0]             \n",
      "                                                                 activation_769[0][0]             \n",
      "                                                                 activation_772[0][0]             \n",
      "                                                                 max_pooling2d_16[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_774 (Conv2D)             (None, 8, 8, 192)    399360      mixed_7a[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_774 (BatchN (None, 8, 8, 192)    576         conv2d_774[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_774 (Activation)     (None, 8, 8, 192)    0           batch_normalization_774[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_775 (Conv2D)             (None, 8, 8, 224)    129024      activation_774[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_775 (BatchN (None, 8, 8, 224)    672         conv2d_775[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_775 (Activation)     (None, 8, 8, 224)    0           batch_normalization_775[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_773 (Conv2D)             (None, 8, 8, 192)    399360      mixed_7a[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_776 (Conv2D)             (None, 8, 8, 256)    172032      activation_775[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_773 (BatchN (None, 8, 8, 192)    576         conv2d_773[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_776 (BatchN (None, 8, 8, 256)    768         conv2d_776[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_773 (Activation)     (None, 8, 8, 192)    0           batch_normalization_773[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_776 (Activation)     (None, 8, 8, 256)    0           batch_normalization_776[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_1_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_773[0][0]             \n",
      "                                                                 activation_776[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_1_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_1_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_1 (Lambda)               (None, 8, 8, 2080)   0           mixed_7a[0][0]                   \n",
      "                                                                 block8_1_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_1_ac (Activation)        (None, 8, 8, 2080)   0           block8_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_778 (Conv2D)             (None, 8, 8, 192)    399360      block8_1_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_778 (BatchN (None, 8, 8, 192)    576         conv2d_778[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_778 (Activation)     (None, 8, 8, 192)    0           batch_normalization_778[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_779 (Conv2D)             (None, 8, 8, 224)    129024      activation_778[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_779 (BatchN (None, 8, 8, 224)    672         conv2d_779[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_779 (Activation)     (None, 8, 8, 224)    0           batch_normalization_779[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_777 (Conv2D)             (None, 8, 8, 192)    399360      block8_1_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_780 (Conv2D)             (None, 8, 8, 256)    172032      activation_779[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_777 (BatchN (None, 8, 8, 192)    576         conv2d_777[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_780 (BatchN (None, 8, 8, 256)    768         conv2d_780[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_777 (Activation)     (None, 8, 8, 192)    0           batch_normalization_777[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_780 (Activation)     (None, 8, 8, 256)    0           batch_normalization_780[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_2_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_777[0][0]             \n",
      "                                                                 activation_780[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_2_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_2_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_2 (Lambda)               (None, 8, 8, 2080)   0           block8_1_ac[0][0]                \n",
      "                                                                 block8_2_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_2_ac (Activation)        (None, 8, 8, 2080)   0           block8_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_782 (Conv2D)             (None, 8, 8, 192)    399360      block8_2_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_782 (BatchN (None, 8, 8, 192)    576         conv2d_782[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_782 (Activation)     (None, 8, 8, 192)    0           batch_normalization_782[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_783 (Conv2D)             (None, 8, 8, 224)    129024      activation_782[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_783 (BatchN (None, 8, 8, 224)    672         conv2d_783[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_783 (Activation)     (None, 8, 8, 224)    0           batch_normalization_783[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_781 (Conv2D)             (None, 8, 8, 192)    399360      block8_2_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_784 (Conv2D)             (None, 8, 8, 256)    172032      activation_783[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_781 (BatchN (None, 8, 8, 192)    576         conv2d_781[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_784 (BatchN (None, 8, 8, 256)    768         conv2d_784[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_781 (Activation)     (None, 8, 8, 192)    0           batch_normalization_781[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_784 (Activation)     (None, 8, 8, 256)    0           batch_normalization_784[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_3_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_781[0][0]             \n",
      "                                                                 activation_784[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_3_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_3_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_3 (Lambda)               (None, 8, 8, 2080)   0           block8_2_ac[0][0]                \n",
      "                                                                 block8_3_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_3_ac (Activation)        (None, 8, 8, 2080)   0           block8_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_786 (Conv2D)             (None, 8, 8, 192)    399360      block8_3_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_786 (BatchN (None, 8, 8, 192)    576         conv2d_786[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_786 (Activation)     (None, 8, 8, 192)    0           batch_normalization_786[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_787 (Conv2D)             (None, 8, 8, 224)    129024      activation_786[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_787 (BatchN (None, 8, 8, 224)    672         conv2d_787[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_787 (Activation)     (None, 8, 8, 224)    0           batch_normalization_787[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_785 (Conv2D)             (None, 8, 8, 192)    399360      block8_3_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_788 (Conv2D)             (None, 8, 8, 256)    172032      activation_787[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_785 (BatchN (None, 8, 8, 192)    576         conv2d_785[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_788 (BatchN (None, 8, 8, 256)    768         conv2d_788[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_785 (Activation)     (None, 8, 8, 192)    0           batch_normalization_785[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_788 (Activation)     (None, 8, 8, 256)    0           batch_normalization_788[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_4_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_785[0][0]             \n",
      "                                                                 activation_788[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_4_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_4_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_4 (Lambda)               (None, 8, 8, 2080)   0           block8_3_ac[0][0]                \n",
      "                                                                 block8_4_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_4_ac (Activation)        (None, 8, 8, 2080)   0           block8_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_790 (Conv2D)             (None, 8, 8, 192)    399360      block8_4_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_790 (BatchN (None, 8, 8, 192)    576         conv2d_790[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_790 (Activation)     (None, 8, 8, 192)    0           batch_normalization_790[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_791 (Conv2D)             (None, 8, 8, 224)    129024      activation_790[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_791 (BatchN (None, 8, 8, 224)    672         conv2d_791[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_791 (Activation)     (None, 8, 8, 224)    0           batch_normalization_791[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_789 (Conv2D)             (None, 8, 8, 192)    399360      block8_4_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_792 (Conv2D)             (None, 8, 8, 256)    172032      activation_791[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_789 (BatchN (None, 8, 8, 192)    576         conv2d_789[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_792 (BatchN (None, 8, 8, 256)    768         conv2d_792[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_789 (Activation)     (None, 8, 8, 192)    0           batch_normalization_789[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_792 (Activation)     (None, 8, 8, 256)    0           batch_normalization_792[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_5_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_789[0][0]             \n",
      "                                                                 activation_792[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_5_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_5_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_5 (Lambda)               (None, 8, 8, 2080)   0           block8_4_ac[0][0]                \n",
      "                                                                 block8_5_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_5_ac (Activation)        (None, 8, 8, 2080)   0           block8_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_794 (Conv2D)             (None, 8, 8, 192)    399360      block8_5_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_794 (BatchN (None, 8, 8, 192)    576         conv2d_794[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_794 (Activation)     (None, 8, 8, 192)    0           batch_normalization_794[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_795 (Conv2D)             (None, 8, 8, 224)    129024      activation_794[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_795 (BatchN (None, 8, 8, 224)    672         conv2d_795[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_795 (Activation)     (None, 8, 8, 224)    0           batch_normalization_795[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_793 (Conv2D)             (None, 8, 8, 192)    399360      block8_5_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_796 (Conv2D)             (None, 8, 8, 256)    172032      activation_795[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_793 (BatchN (None, 8, 8, 192)    576         conv2d_793[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_796 (BatchN (None, 8, 8, 256)    768         conv2d_796[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_793 (Activation)     (None, 8, 8, 192)    0           batch_normalization_793[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_796 (Activation)     (None, 8, 8, 256)    0           batch_normalization_796[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_6_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_793[0][0]             \n",
      "                                                                 activation_796[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_6_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_6_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_6 (Lambda)               (None, 8, 8, 2080)   0           block8_5_ac[0][0]                \n",
      "                                                                 block8_6_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_6_ac (Activation)        (None, 8, 8, 2080)   0           block8_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_798 (Conv2D)             (None, 8, 8, 192)    399360      block8_6_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_798 (BatchN (None, 8, 8, 192)    576         conv2d_798[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_798 (Activation)     (None, 8, 8, 192)    0           batch_normalization_798[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_799 (Conv2D)             (None, 8, 8, 224)    129024      activation_798[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_799 (BatchN (None, 8, 8, 224)    672         conv2d_799[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_799 (Activation)     (None, 8, 8, 224)    0           batch_normalization_799[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_797 (Conv2D)             (None, 8, 8, 192)    399360      block8_6_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_800 (Conv2D)             (None, 8, 8, 256)    172032      activation_799[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_797 (BatchN (None, 8, 8, 192)    576         conv2d_797[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_800 (BatchN (None, 8, 8, 256)    768         conv2d_800[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_797 (Activation)     (None, 8, 8, 192)    0           batch_normalization_797[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_800 (Activation)     (None, 8, 8, 256)    0           batch_normalization_800[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_7_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_797[0][0]             \n",
      "                                                                 activation_800[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_7_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_7_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_7 (Lambda)               (None, 8, 8, 2080)   0           block8_6_ac[0][0]                \n",
      "                                                                 block8_7_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_7_ac (Activation)        (None, 8, 8, 2080)   0           block8_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_802 (Conv2D)             (None, 8, 8, 192)    399360      block8_7_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_802 (BatchN (None, 8, 8, 192)    576         conv2d_802[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_802 (Activation)     (None, 8, 8, 192)    0           batch_normalization_802[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_803 (Conv2D)             (None, 8, 8, 224)    129024      activation_802[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_803 (BatchN (None, 8, 8, 224)    672         conv2d_803[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_803 (Activation)     (None, 8, 8, 224)    0           batch_normalization_803[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_801 (Conv2D)             (None, 8, 8, 192)    399360      block8_7_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_804 (Conv2D)             (None, 8, 8, 256)    172032      activation_803[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_801 (BatchN (None, 8, 8, 192)    576         conv2d_801[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_804 (BatchN (None, 8, 8, 256)    768         conv2d_804[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_801 (Activation)     (None, 8, 8, 192)    0           batch_normalization_801[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_804 (Activation)     (None, 8, 8, 256)    0           batch_normalization_804[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_8_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_801[0][0]             \n",
      "                                                                 activation_804[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_8_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_8_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_8 (Lambda)               (None, 8, 8, 2080)   0           block8_7_ac[0][0]                \n",
      "                                                                 block8_8_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_8_ac (Activation)        (None, 8, 8, 2080)   0           block8_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_806 (Conv2D)             (None, 8, 8, 192)    399360      block8_8_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_806 (BatchN (None, 8, 8, 192)    576         conv2d_806[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_806 (Activation)     (None, 8, 8, 192)    0           batch_normalization_806[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_807 (Conv2D)             (None, 8, 8, 224)    129024      activation_806[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_807 (BatchN (None, 8, 8, 224)    672         conv2d_807[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_807 (Activation)     (None, 8, 8, 224)    0           batch_normalization_807[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_805 (Conv2D)             (None, 8, 8, 192)    399360      block8_8_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_808 (Conv2D)             (None, 8, 8, 256)    172032      activation_807[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_805 (BatchN (None, 8, 8, 192)    576         conv2d_805[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_808 (BatchN (None, 8, 8, 256)    768         conv2d_808[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_805 (Activation)     (None, 8, 8, 192)    0           batch_normalization_805[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_808 (Activation)     (None, 8, 8, 256)    0           batch_normalization_808[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_9_mixed (Concatenate)    (None, 8, 8, 448)    0           activation_805[0][0]             \n",
      "                                                                 activation_808[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_9_conv (Conv2D)          (None, 8, 8, 2080)   933920      block8_9_mixed[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_9 (Lambda)               (None, 8, 8, 2080)   0           block8_8_ac[0][0]                \n",
      "                                                                 block8_9_conv[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "block8_9_ac (Activation)        (None, 8, 8, 2080)   0           block8_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_810 (Conv2D)             (None, 8, 8, 192)    399360      block8_9_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_810 (BatchN (None, 8, 8, 192)    576         conv2d_810[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_810 (Activation)     (None, 8, 8, 192)    0           batch_normalization_810[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_811 (Conv2D)             (None, 8, 8, 224)    129024      activation_810[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_811 (BatchN (None, 8, 8, 224)    672         conv2d_811[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_811 (Activation)     (None, 8, 8, 224)    0           batch_normalization_811[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_809 (Conv2D)             (None, 8, 8, 192)    399360      block8_9_ac[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_812 (Conv2D)             (None, 8, 8, 256)    172032      activation_811[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_809 (BatchN (None, 8, 8, 192)    576         conv2d_809[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_812 (BatchN (None, 8, 8, 256)    768         conv2d_812[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "activation_809 (Activation)     (None, 8, 8, 192)    0           batch_normalization_809[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "activation_812 (Activation)     (None, 8, 8, 256)    0           batch_normalization_812[0][0]    \n",
      "__________________________________________________________________________________________________\n",
      "block8_10_mixed (Concatenate)   (None, 8, 8, 448)    0           activation_809[0][0]             \n",
      "                                                                 activation_812[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "block8_10_conv (Conv2D)         (None, 8, 8, 2080)   933920      block8_10_mixed[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "block8_10 (Lambda)              (None, 8, 8, 2080)   0           block8_9_ac[0][0]                \n",
      "                                                                 block8_10_conv[0][0]             \n",
      "__________________________________________________________________________________________________\n",
      "conv_7b (Conv2D)                (None, 8, 8, 1536)   3194880     block8_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "conv_7b_bn (BatchNormalization) (None, 8, 8, 1536)   4608        conv_7b[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv_7b_ac (Activation)         (None, 8, 8, 1536)   0           conv_7b_bn[0][0]                 \n",
      "==================================================================================================\n",
      "Total params: 54,336,736\n",
      "Trainable params: 54,276,192\n",
      "Non-trainable params: 60,544\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "780\n"
     ]
    }
   ],
   "source": [
    "print(cnn_model.summary())\n",
    "i = 0\n",
    "for layer in cnn_model.layers[:]:\n",
    "    i = i +1\n",
    "print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs = Input((width, width, 3))\n",
    "\n",
    "x = inputs\n",
    "x = Lambda(preprocess_input, name='preprocessing')(x)\n",
    "x = cnn_model(x)\n",
    "x = GlobalAveragePooling2D()(x)\n",
    "x = Dropout(0.5)(x)\n",
    "x = Dense(5, activation='softmax', name='softmax')(x)\n",
    "\n",
    "model = Model(inputs, x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_8 (InputLayer)         (None, 299, 299, 3)       0         \n",
      "_________________________________________________________________\n",
      "preprocessing (Lambda)       (None, 299, 299, 3)       0         \n",
      "_________________________________________________________________\n",
      "inception_resnet_v2 (Model)  (None, 8, 8, 1536)        54336736  \n",
      "_________________________________________________________________\n",
      "global_average_pooling2d_2 ( (None, 1536)              0         \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 1536)              0         \n",
      "_________________________________________________________________\n",
      "softmax (Dense)              (None, 5)                 7685      \n",
      "=================================================================\n",
      "Total params: 54,344,421\n",
      "Trainable params: 54,283,877\n",
      "Non-trainable params: 60,544\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 划分训练/测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((6564, 299, 299, 3), (6564, 6))"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train, X_valid, y_train, y_valid = train_test_split(X, y, test_size=0.12, random_state=42)\n",
    "X_train.shape, y_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Compile the model\n",
    "adam = Adam(lr=0.001) \n",
    "\n",
    "model.compile(optimizer=adam, loss='categorical_crossentropy', metrics=['accuracy'])\n",
    "# Set a learning rate annealer\n",
    "# learning_rate_reduction = ReduceLROnPlateau(monitor='val_acc',\n",
    "#                                             patience=3,\n",
    "#                                             verbose=1,\n",
    "#                                             factor=0.1,\n",
    "#                                             min_lr=0.00001)\n",
    "epochs = 16\n",
    "batch_size = 32"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据增强"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "datagen = ImageDataGenerator(\n",
    "        featurewise_center = False, # set input mean to 0 over the dataset\n",
    "        samplewise_center = False, # set each sample mean to 0\n",
    "        featurewise_std_normalization = False, # divide inputs by std of the dataset\n",
    "        samplewise_std_normalization = False, # divide each input by its std\n",
    "        zca_whitening = False, # apply ZCA whitening\n",
    "        rotation_range = 10, # randomly rotate images in the range (degrees, 0 to 180)\n",
    "        zoom_range = 0.05, # randomly zoom image\n",
    "        width_shift_range = 0.075, # randomly shift images horizontally (fraction of total width)\n",
    "        height_shift_range = 0.075, # randomly shift images vertivally (fraction of total heigth)\n",
    "        horizontal_flip = True, # randomly flip images\n",
    "        vertical_flip = False,\n",
    "        shear_range = 0.075,\n",
    "        fill_mode = 'constant',\n",
    "        cval = 0)\n",
    "\n",
    "datagen.fit(X_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- 少量旋转\n",
    "- 少量偏移\n",
    "- 水平翻转\n",
    "- 垂直翻转"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/16\n",
      "Epoch 00001: val_loss improved from inf to 0.93325, saving model to ./models/pant.best.h5\n",
      " - 213s - loss: 0.9445 - acc: 0.6370 - val_loss: 0.9333 - val_acc: 0.6596\n",
      "Epoch 2/16\n",
      "Epoch 00002: val_loss improved from 0.93325 to 0.85811, saving model to ./models/pant.best.h5\n",
      " - 169s - loss: 0.6665 - acc: 0.7563 - val_loss: 0.8581 - val_acc: 0.7344\n",
      "Epoch 3/16\n",
      "Epoch 00003: val_loss improved from 0.85811 to 0.55665, saving model to ./models/pant.best.h5\n",
      " - 169s - loss: 0.5777 - acc: 0.7881 - val_loss: 0.5566 - val_acc: 0.7946\n",
      "Epoch 4/16\n",
      "Epoch 00004: val_loss did not improve\n",
      " - 166s - loss: 0.5318 - acc: 0.8052 - val_loss: 0.6565 - val_acc: 0.7612\n",
      "Epoch 5/16\n",
      "Epoch 00005: val_loss improved from 0.55665 to 0.51301, saving model to ./models/pant.best.h5\n",
      " - 168s - loss: 0.4724 - acc: 0.8264 - val_loss: 0.5130 - val_acc: 0.8203\n",
      "Epoch 6/16\n",
      "Epoch 00006: val_loss improved from 0.51301 to 0.47869, saving model to ./models/pant.best.h5\n",
      " - 168s - loss: 0.4118 - acc: 0.8468 - val_loss: 0.4787 - val_acc: 0.8382\n",
      "Epoch 7/16\n",
      "Epoch 00007: val_loss improved from 0.47869 to 0.43027, saving model to ./models/pant.best.h5\n",
      " - 168s - loss: 0.3946 - acc: 0.8553 - val_loss: 0.4303 - val_acc: 0.8337\n",
      "Epoch 8/16\n",
      "Epoch 00008: val_loss did not improve\n",
      " - 166s - loss: 0.3933 - acc: 0.8573 - val_loss: 0.5221 - val_acc: 0.8259\n",
      "Epoch 9/16\n",
      "Epoch 00009: val_loss did not improve\n",
      " - 166s - loss: 0.3367 - acc: 0.8727 - val_loss: 0.4523 - val_acc: 0.8404\n",
      "Epoch 10/16\n",
      "Epoch 00010: val_loss did not improve\n",
      " - 166s - loss: 0.3131 - acc: 0.8826 - val_loss: 0.5405 - val_acc: 0.8036\n",
      "Epoch 11/16\n",
      "Epoch 00011: val_loss did not improve\n",
      " - 166s - loss: 0.2998 - acc: 0.8928 - val_loss: 0.6695 - val_acc: 0.7857\n",
      "Epoch 12/16\n",
      "Epoch 00012: val_loss did not improve\n",
      " - 166s - loss: 0.2970 - acc: 0.8887 - val_loss: 0.4677 - val_acc: 0.8281\n"
     ]
    }
   ],
   "source": [
    "prefix_cls = cur_class.split('_')[0]\n",
    "\n",
    "checkpointer = ModelCheckpoint(filepath='./models/{0}.best.h5'.format(prefix_cls), verbose=1, \n",
    "                               save_best_only=True, mode='val_acc')\n",
    "\n",
    "try:\n",
    "    # Fit the model\n",
    "    history = model.fit_generator(datagen.flow(X_train, y_train, batch_size=batch_size),\n",
    "                                  epochs=epochs, validation_data=(X_valid, y_valid),\n",
    "                                  verbose=2, steps_per_epoch=X_train.shape[0] // batch_size,\n",
    "                                  callbacks=[EarlyStopping(patience=5), checkpointer])\n",
    "except KeyboardInterrupt:\n",
    "    print('KeyboardInterrupt')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 测试模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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t2tyiRYuIjo6me/fuSSZsq1atonv37lSrVo3ixYvH1X2vX7+e27dvp7m8w1o3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VoVc1jfd999S2zr2LEjAJs2bYq5vZHOk5GRQdOmTcPO8/PPP7Njxw722WcfGjVqVOI5AwcOLFdY\nh/L9PGbOnAkQU7lNeY6tjNJ+11u2bOHxxx/nww8/ZNGiRWRnZ+MDmQP73gJ++ukncnNzGTBgALvs\nUvYH4mOPPZY2bdrw0ksvccMNN+wM9xMmTKBRo0a1fijRSof1ol71YcBi4LFiu28DLgTOcs5d7b3P\nrsD59wIGAiuA9yvX2rrltddscJfLeJRHCZncaI89rPSlffvENU5ERGq8xo0bk5GREXHfq6++yqWX\nXkp6ejqHHnooXbp0oXHjxjjn+Pzzz/nmm2/KNbxi8SEkgZ310gUFBZU6T+BcoefZvHkzAK1bt454\nfLTt0ZT35xH44NA+hr/V5Tm2Mtq0aRNxe25uLscccwxz586lT58+nHjiibRs2ZLU1FTy8/N56KGH\nKvy9AdSvX5+zzjqLBx54YOf9BVOnTmXBggWcfPLJMX/gq6ni0bN+WNF6kve+MHSH936Lc24qFuYH\nAp9W4PwXFq2f8t7H/r+xjlu7Fi67DG5gDGMImQWpb1+YNAnKOQmGiEhdlKjSkpoi9IbB4saMGUOT\nJk2YPHlyiRKJhQsX8s0331Rx6yon8CEk0mgzpW2Pprw/j0Bp0apVq8qcjbU8x6ak2ECAO3bsiLg/\n8CElkmi/77feeou5c+dy3nnnce+994bt++2333jooYeitjdWo0aN4qGHHuK5557j+OOP33lj6dln\nnx3zOWqqeAzd2Kto/WuU/fOL1j3Le2LnXBpwJlAAPFn+ptVdl4/2XL725vCgfuCB8NlnCuoiIlKl\nduzYwbJly+jTp0+JYJqfn8+3336bmIaVQ+/evUlNTeW7774jNze3xP4ZM2bEfK6K/Dz69+8PwKef\nlt3PWZ5jA0F5xYoVJfatX7+epUuXlnmO4hYtWgRYuUpx06ZNK7Ftzz33JC0tjdmzZ+8c+rEsHTt2\nZNiwYXz55ZfMnDmT999/n913352BAweWu701TTzCeuCukmgFY4HtzaPsL80pRc/7yHu/LNYnOedm\nRlqA3SvQhhrn3Xc8B7x8BTdzd3Dj0KHWo968Ir8GERGR2KWmptK+fXt++eWXsDBWWFjInXfeyZIl\nSxLYuthkZGRw9NFHs3bt2hJjqc+cOZN333035nNV5Odx1llnkZaWxuOPPx5242tA6Agv5Tm2Xbt2\ndOjQgS+//JLFixfv3J6fn8+NN95YrpKigMBwl1OnTg3bPn/+fMaMGVPi+EaNGnHWWWexZcsWrr/+\n+hK9/Lm5uWQF5oEJce655+K955xzziEvL69O9KpD8o+zHiiBGZ/QVtQgG9cXsPX0i7icp4IbjzkG\nXn8dItwgIyIiUhUuvvhibrvtNg4++GCOPfZYUlJSmDZtGkuXLuWII44o17CNiXLHHXcwY8YM7rnn\nHqZPn07fvn1ZuXIl77zzDsOHD+eDDz7YWVZSlvL+PNq3b8/YsWO5+OKLOeqooxg2bBi9evVi06ZN\n/Pjjj2zdupUvv/yy3MeCjaxz0003MXz4cI477jjq1avHF198QYMGDejRo0e5h3ocOXIk999/Pw88\n8ABz5syhd+/eLF26lEmTJjF8+HDefvvtEs+55ZZb+O6773j77beZPXs2Rx55JI0bN2bZsmVMnjyZ\nBx98sMSoPYcddhjdunVj0aJFpKWlccopp5SrnTVVPHrWAz3nJcdtCt++sTwndc7tCQwClgMflOe5\n3vv+kRZsSMnaKz+fnwecxRk5waCed/zJ8OabCuoiIlKtLrnkEu6//35atmzJiy++yJtvvkn37t2Z\nNGkSPXuWuzI2ITp16sTEiRM54YQT+P777xk3bhw///wzY8eO5aijjgKIeoNtcRX5eRx//P+3d6fh\nURXp38e/lYTdyJawB4yIgiIwICC7oECQHRGRAcMi2zCjfwUXEMSRcUAFHBcUCUIQAXUiGNmesA7g\nGFAWhREcdpxAkN2EnYR6XpzukJAOhEC6G/L7XFeuputUd9/JIZ2761Td1ZElS5bQoUMHNmzYwKRJ\nk1i4cCEFChRgyJAhOe47YMAA3nzzTYoXL86sWbNYsGABTZs2Zf78+RQuXPiaf05FixYlNjaWDh06\nsHnzZqKioti+fTsjR47knXfe8fiYwoULM3fuXF5//XWKFi3K7Nmz+eSTT9i8eTOdO3f2WILSGJNW\n+aVTp04eS4beikz6sjo5egJjngaigCnW2oEejsfhLDB9xFqb7QWmxph3gWdwNlV67bqCvPScG2rX\nrl3bXeLolnL2LIdadKdUfGxa076HIqm0dCoE+fsFFBER39i2bRvgzE8GOHHiBKdPnyZ//vxXXDwp\nMmLECKZMmcLChQupX7++r8PJM/r06cP8+fOJi4tLm6vvbQcOHCApKYl9+/Zx8uRJDh8+zIMPPpip\ndGadOnXYuHHjRteAcY7diJH1la7bVsaYDM9njAkGGgGngWyvxDDGFAR64Sws/eQq3eXUKVIe7ZAh\nUY+r/CcqLZ+mRF1EROQ6eKpYsnHjRj799FPKlCnjs4QxL9q1axeLFi2iVq1aeernft2ZnLV2lzFm\nCc7o+RDg/XSH/woUAT5211g3xuQDKgMXrLW7snjax4HiwIJrWViaJyUlQdu2BH37bVrTewVf5Ilv\nx0GARoVERESuR8OGDalRowZVq1alQIEC7Ny5M63qyltvvZVW611yz+eff87evXuJiYkhNTWV4cOH\n+zokr7pR/8P+BHwHvGeMeRjYBtTHqcG+HXglXd/yruP7gDuyeD73wlLtWHolR49CRASkK/k0kjHc\nO/UVSpdRoi4iInK9+vbty7Jly4iJieHUqVMUK1aMVq1a8Ze//IV69er5Orw8ISoqii1btlChQgXG\njx+f6zu1+psbkqy7RtcfAF4HIoBHgUTgXZw558ez+1zGmGpAY3KwsDRPOXgQWraE//wnrek5JrKz\n3XOM6eHDuERERG4ho0aNYtSoUb4OI0/LTv34W9kNu3bjmq7SJxv99gJZDvtaa7dd6bgA//sfPPww\n7HD2m7qIYRCT+eL2AWydDFoTJSIiInJr0ESrm82uXU6i7tpAIYVAehPNLHoydSKUL+/j+ERERETk\nhlGyfjPZuhUeeQRcK9MvkI9ufMHXdOaRR6BvXx/HJyIiIiI3lJL1m8XGjdC6NRw5AsCFoIK0T5lH\nHBEUKQJTpmj6i4iIiMitRsn6zSA+Htq0gd+dzWJTC99G67MLWEkzAMaNg/BwXwYoIiIiIrnhRmyK\nJLlpxQqn6osrUbfFitGnwjJWXnQS9caN4U9/8mWAIiIiIpJblKz7s4UL4dFH4dQp535oKJ/0/Bcz\ntzvbGhcsCJ98AgE6iyIiIiK3JKV5/iomBjp3hnPnnPvly7Nz2mqGTKmZ1uX11+Huu30Un4iIiIjk\nOs1Z90czZjilXS5edO6Hh5O6ZDk9e4Zz/rzTVLcuPPec70IUERERkdynkXV/8+GH0Lv3pUT9nntg\n9Wremx/OunVOU758MG0aBOmjloiI3ER2795NSEgIzz77bIb2QYMGERISwoEDB7L9XPfffz9169a9\n0SFmkFW8It6kZN2fvP02DBly6X7NmrB6NTvPVuCVVy41jxwJ1at7PzwREbn1DBw4kJCQEKZNm3bV\nvl27diUkJISFCxd6IbLcl5KSQkhICF26dPF1KCJZUrLuD6yF0aPhxRcvtdWvDytXcjGkFE8/DWfO\nOM01asDLL/smTBERufX06tULgJkzZ16x36+//sqqVasoXbo0rVu3vqExvPbaa8THx1OqVKkb+rzX\nKywsjPj4eEaMGOHrUCQPU7Lua9bCsGHOalG3Zs1g6VIoXpyPP4ZVq5zmwEBn+kv+/L4JVUREbj2N\nGzemcuXKbNmyhZ9++inLfrNmzcJaS48ePQi6wfMwy5QpQ5UqVW74816vfPnyUaVKFUqXLu3rUCQP\nU7LuSxcvwuDBMHHipbaICFi0CIKD+fXXjIPtL74Idep4P0wREbm1XW10PTU1ldmzZ2OMoWfPnmnt\niYmJvPXWW7Rp04Z7772XsmXLUr16dQYOHMiOHTuy/fpZzVm31jJlyhQaNmxIuXLlqF69OsOHDyc5\nOdnj8/z++++89957dOzYkerVq1O2bFmqVq1Kr1692LBhQ4a+M2fOpEyZMgCsXr2akJCQtK8JEyYA\nV56znpiYyLBhw6hVqxblypWjatWq9O7dm82bN2fqO3PmTEJCQvjyyy9ZvXo17du3p1KlSoSHh9Oj\nR49r+lmdO3eOqKgonnjiibTXvuuuu3jsscdYsWJFlo/bv38/L7/8MnXr1qV8+fJUqVKFli1bMjF9\nDnINfa82hcjTOU3/89yxYwd9+/blnnvuITQ0lLVr1wKwadMmhg8fTtOmTalcuTLly5enXr16jB49\nmt9de8548tVXX9GpUyfuuusuypcvzx/+8AcGDBiQ9gH0k08+ISQkxOP3C875LF26NM2bN8/yNXxF\nybqvpKRAZCR8/PGlts6d4euvoXBhrIUBA+DkSedQ1arw6qu+CVVERG5t3bt3J3/+/MydO5fTp09n\nOr5s2TISExNp1qwZlSpVSmtfs2YNH3zwAcWKFaNdu3YMHDiQ2rVrExsbS8uWLdm2bdt1xfXSSy8x\nYsQIkpKSiIyMpHPnzixdupSuXbuSkpKSqf+2bdsYO3YsQUFBtG7dmsGDB9OkSRNWrVpFu3btWOW+\nVA3UqFGDoUOHAlCpUiVeeOGFtK8GDRpcMa49e/bw8MMPEx0dTeXKlRk8eDDNmjUjLi6ONm3asGzZ\nMo+PW7x4Md26daNo0aL07t2bevXqsWTJEjp27Mjx48ez9TM5evQor7zyCqdOnaJZs2YMHjyYiIgI\nfvrpJ5544gnmzJmT6TEbNmygWbNmTJ06lXLlyjFgwAC6dOlCkSJFGD9+fI775tSuXbto1aoVBw4c\noGvXrvTq1YvbbrsNgOjoaGJjY6lSpQo9evSgd+/elCpVikmTJtGuXTtOufeecbHWMmjQIAYOHMgv\nv/xC27ZtGTRoEPXr1+e7775LOxfdunWjSJEifPbZZ1x0F/FI57PPPiM1NZWnnnrqhnyPN5J/XW/K\nK86dgx49YO7cS209e8L06WklXmbMgLg455AxzuZHBQv6IFYREbnlhYSE0KZNG2JjY4mNjeXJJ5/M\ncNw94n55IvPQQw+xdevWtETLbfPmzbRr144xY8Ywe/bsHMX03XffMW3aNO68806WLFlCsWLFABgx\nYgQdOnTg8OHDmV63WrVq/Pzzz5QoUSJD+//+9z9at27NyJEjWbNmDQA1a9bkvvvuY8KECVSqVImX\nXnop27E9//zzHDp0iFdffZVnnnkmrb1379507NiRIUOGsGnTJgoXLpzhcYsXLyYmJobGjRuntY0e\nPZpJkyYxZ84c/pSNLclLlCjBTz/9RNmyZTO0//7770RERPDaa6/RpUsXChQoADgj8X379uXEiRNM\nnTqVTp06ZXhc+pHva+l7PdauXcvQoUMZPnx4pmPDhg1j4sSJBAYGZmiPjo5m2LBhREdHMyRdMY7p\n06cTExPDAw88wD//+U+Cg4PTjqWmpnL48GEAgoOD6dq1KzNmzGDlypU8/PDDaf0uXrzIrFmzKFKk\nCF27dr0h3+ONpJF1bztzBjp1ypioDxjgZOeuRD0xMWMN9WefhYYNvRyniIhQMiTkpvm6XpGRkYAz\nwpjewYMHWbZsGaGhobRp0ybDsVKlSmVKmMEZtW7YsCFr1qwhNTU1R/G4R4iHDRuWlqgDFCpUiJEj\nR3p8TNGiRTMl6uAsFG3bti3btm0jMTExR/G4/frrr6xZs4ZKlSplSq4bNGhAx44dOXr0KIsWLcr0\n2K5du2ZI1OHSB6CNGzdm6/ULFiyYKVEH53t/8sknOXr0aIa1B4sWLWL//v20a9cuU/INUK5cuRz1\nvR5lypRJu6pxubCwsEyJOjg/pyJFirBy5coM7VFRURhjmDBhQoZEHSAwMDBtqhNAnz59AJgxY0aG\nfsuWLSMhIYEuXbpkeg5/oJF1b0pOhvbtL60YBXj+eRg/3hk+x1lvOngwnDjhHIgzY0YAABQaSURB\nVL7zTvjb33wQq4iI5ClNmjQhPDycdevWsX37du52bZE9Z84cUlJS6N69O/ny5cv0uMWLFzNjxgw2\nb97MsWPHMk1POX78OCE5+DDhnvvd0MNoVYMGDQgI8DzeGB8fT1RUFOvXr+fIkSOcd+8m6JKYmOgx\n2c2uLVu2pMXgaUFskyZNmDdvHlu2bMk0SlurVq1M/cuXLw9wxfnYl9u6dSsffPAB69at4+DBg5xz\n73bukv4Dyfr16wEyjCRn5Vr6Xo/q1auTP4tqGRcuXGD69Ol8/fXX/Pe//yU5OTnDtJX031tSUhI7\nduygbNmy3Hfffdl6XffUo/T/Dz799FPAuTLij5Sse8vx49CmDWk7G4EzCf2119ISdYAvv4TY2Etd\npk6FIkW8F6aIiORN7sWjY8aMYebMmYwZMwZrLbNmzcIYk7YINb1JkyYxevRoihcvTtOmTQkLC6Ng\nwYIYY1i4cCFbt27NlCxnV1JSEgChoaGZjuXPnz/DaLtbbGws/fv3p1ChQmnz6wsXLkxAQABr1qxh\n7dq1OY7n8riyqhDjbveUfN9+++2Z2twJf3avQKxbt47HHnuMixcv0rRpUyIiIrjtttsICAhg8+bN\nxMXFZUje3fFm5wPKtfS9HleqrtO7d2/i4uIIDw+nbdu2hIaGpiX2H330UYbz5/4ZX0u8ffr04fvv\nv2fWrFkMGzaMxMREli5dSq1atahZs2YOv6PcpWTdGw4dglatIH1JrLfeghdeyNDt8GH4858v3R84\nEPxwUbKISJ5x9MgRX4fgVU8++STjxo3jyy+/ZNSoUaxdu5a9e/fSpEkT7rzzzgx9L1y4wNtvv02Z\nMmVYsWJFphrp7uoeOeVObA8fPkyFChUyHDt//jwnTpygaNGiGdrHjh1LwYIFWbZsGVWqVMlw7MCB\nA9cdU/q4Dh065PH4b7/9lqHfjTZhwgTOnj3LggULePDBBzMcGz9+PHHuBW8u7jiyM/3nWvq6r2x4\nWugL13alwG39+vXExcXRokULZs+eneHKRWpqKu+++26G/u7zfy1Tmzp06MCoUaP47LPPeP7559MW\nlrqngfkjzVnPbfv3O3XT0yfqkyZlStQBnnkG3H8XKlRw8nkRERFvKVWqFBEREWlzrrNaWApOEn3y\n5Enq16+fKVFPTk5Omy6SUzVq1ACchaaXi4+P91jRY+/evVStWjVTop6amsq69Fe2XdwJ57XMq7//\n/vsB58OIp8d9++23GeK/0fbs2UNoaGimRB08/6weeOABAJYvX37V576WvgEBAQQHB3tcdJqSksLP\nP/981ee43O7duwGIiIjINMXohx9+yHRV5Pbbb6dKlSocPHgw269XoEABevToQUJCAkuWLGHWrFkE\nBwf79S62StZz2+HDzopRgIAAiI4GD6u9Y2Ph888v3Z8yBXLpQ7mIiEiW3NNdPvzwQxYtWkTJkiVp\n27Ztpn6lS5emQIEC/PjjjxnK6Z0/f56XX36ZE+7FVznkrkgzfvz4DKO0Z86c4W9ZLOYKCwtj586d\naaPb4JT2GzduHDt37szUPyAggGLFirF///5sx1WxYkUaN27Mnj17iIqKynBs3bp1fP3115QoUSLT\nYtwbJSwsjCNHjvDLL79kaI+Ojmb16tWZ+j/66KOUL1+eBQsWEJt+nq1L+mT7WvoC1K5dm71792Z6\n3bfffjtHlWMqVqwIwL///e8M7YcOHfJYOQagf//+WGsZOnRopvr7qampGf4vuEVGRhIQEMALL7xA\nQkICjz/+OEX8eM6xpsHktlq1YPFiaNvWqan++OOZuhw/7iwqdXvqKWd6u4iIiLc1b96cihUrplUn\n6devn8fFgIGBgTz99NNMmjQpbe70uXPnWLNmDcnJyTRs2NDjSG92NWzYkD59+jB9+nQaNWpEhw4d\nCAwMZPHixZQsWdLjXPZBgwbx0ksv0bx5c9q1a0dQUBDx8fHs3r2bVq1asWTJkkyPadq0Kd988w09\ne/bk/vvvJygoiEaNGnkcuXabMGEC7dq1Y+TIkSxfvpyaNWuSkJDAN998Q1BQEO+//36uJX+DBg1i\n9erVtGnTho4dOxIcHMymTZv44YcfaN++PfPnz8/Qv0CBAkybNo1u3brRr18/pk+fTu3atTl79izb\nt28nPj4+7cPKtfQFGDJkCKtXr6ZHjx507tyZokWL8v3335OQkECDBg2Ij4+/pu+tbt26PPDAA8TG\nxpKYmEi9evU4dOgQy5Yto2rVqpmu4IAzB33dunV89dVX1KtXj9atWxMSEkJiYiJr1qwhMjIyU+WZ\nSpUq0aJFi7Qa7P48BQY0su4dDRrAnj0eE3WAoUMvDb6XLg3vvOPF2ERERNK5fJdSTwtL3UaNGsXo\n0aPJnz8/M2bMYNGiRdSpU4elS5fekDJ/b775Jm+88QbBwcFER0czb948HnnkEWJiYjxWYunXrx/v\nvvsuoaGhzJkzh5iYGCpWrEhcXBzVq1f3+Bpjx46lc+fOrF+/ngkTJjB27NhMI7uXq1y5MsuXLycy\nMpLt27czadIkVqxYQcuWLVm4cCGtW7e+7u89K61atWLmzJlUqVKFefPmMXv2bAoVKkRsbCwtWrTw\n+Jg6derwr3/9i8jISPbt28fkyZOJiYkhOTmZF9NvlX6NfVu0aEF0dDR33303X331FV988QV33HEH\nS5cuTatycy0CAwOZPXs2vXv35sCBA0RFRfHDDz8QGRnJF1984bGkozGGyZMnM2nSJCpXrkxsbCyT\nJ09m7dq1NGrUiFatWnl8rT/+8Y+AM/UnO5VkfMlYa30dg9cYYzbUrl279uVbDvtSXBxERFy6P3eu\ns5GpiIjkPvcOm9WqVQPgxIkTnD59mvz582PSVeoSkVvL3//+dyZOnMgHH3xA9+7dr+mxBw4cICkp\niX379nHy5EkOHz7Mgw8+mKnkZZ06ddi4ceNGa22d64lVI+s+lJzs7Ifk1q2bEnURERGR3JScnMyM\nGTMoWbKkx82f/I3mrPvQyy/Dr786/y5ZEt5/37fxiIiIiNyq4uLi2LJlC4sXL+bo0aO88cYbFCxY\n0NdhXZWSdR9ZtQo+/PDS/ffeAw/rJkRERETkBpg3bx4xMTGUKlWKoUOH0r9/f1+HlC1K1n3g9Gno\n1+/S/fbtwVWhSkRERERyweTJk5k8ebKvw7hmmrPuA6NGwa5dzr+LFoWPPgKtYxIRERGRyylZ97K1\na+Ef/7h0f8IEyEF1IxERERHJA5Sse9G5c9C3L7h3SH7kEee+iIiIiPg/X5Q8V7LuRWPGgKukL0WK\nQFSUpr+IiPiSu5b6RfcoiojIFbiTdW8m7UrWvWTTJhg37tL9N9+EO+7wWTgiIoKzvTrAqVOnfByJ\niNwMzp07R0pKChcuXPDaa6oajBdcuOBMd0lNde43aQKDB/s2JhERgeDgYM6ePcvBgwcBZ4Q9L+3s\nLSJXZ63FWsu5c+dISkri/PnzXv2Ar2TdC956C3780fl3wYIwdSoE6JqGiIjPlShRglOnTnH69GkS\nEhJISUnBWps2PUZExC0lJYXz589z8uRJkpOTvfa6StZz2c8/w+uvX7o/Zgzcfbfv4hERkUsCAgII\nCwvj2LFjJCcn89tvv3H69GmCgoIIDAz0dXgi4iestVy4cIFTp06RnJycdgXuwoULBAYGki9fvlx7\nbSXruax4cWjVChYsgHr14LnnfB2RiIikFxAQQEhICCEhIZw4cYJ169Zx5swZwsLCNMIuIlm6ePEi\nx48fp0SJEpQpUybXXkfJei4rVw6++QbmzIEaNUADNSIi/is8PJxffvmFnTt3snv3bm6//XaNsItI\nJikpKSQlJZEvXz5CQkIICwvLtddSsu4FxkCPHr6OQkRErqZYsWI0a9YMYwwnTpzg1KlTnD9/3tdh\niYifCQwMpEyZMpQoUYLmzZtTqFChXHstJesiIiLplCtXjscee4yEhASOHTtGqruUl4iIS1BQEKGh\noZQtW5agoNxNp5Wsi4iIXCZfvnyEh4cTHh7u61BEJI9TAUERERERET+lZF1ERERExE8pWRcRERER\n8VMmL22rbIw5WqhQoRLVqlXzdSgiIiIicgvbtm0bZ86cOWatLXk9z5PXkvU9wO3AXh+8fFXX7S8+\neG3JOZ23m5fO3c1L5+7mpPN289K5yx13AEnW2utaqZ6nknVfMsZsALDW1vF1LJJ9Om83L527m5fO\n3c1J5+3mpXPn3zRnXURERETETylZFxERERHxU0rWRURERET8lJJ1ERERERE/pWRdRERERMRPqRqM\niIiIiIif0si6iIiIiIifUrIuIiIiIuKnlKyLiIiIiPgpJesiIiIiIn5KybqIiIiIiJ9Ssi4iIiIi\n4qeUrIuIiIiI+Ckl67nMGFPBGDPNGHPAGHPOGLPXGPMPY0xxX8cmmRljShpjnjbGzDPG7DTGnDHG\n/G6M+dYY088Yo9+Zm4wxpqcxxrq+nvZ1PHJlxpiHXb9/B13vmQeMMXHGmEd9HZt4Zoxpa4xZYoxJ\ncL1n7jbG/NMY08DXseV1xpiuxpj3jTFrjDFJrvfBz67ymIbGmEXGmGOu87nZGPN/xphAb8UtGQX5\nOoBbmTGmMvAdUAqIBX4B6gHPAhHGmEbW2qM+DFEyexz4CEgEVgK/AqWBLsBUoI0x5nGr3cRuCsaY\nMOAD4CRwm4/DkaswxrwFvAAkAN8AR4BQoA7wELDIZ8GJR8aYN4EXgaPA1zjn7C6gI/CYMeYpa+0V\nk0PJVSOBmjjvgQlA1St1NsZ0BL4CzgJfAMeA9sA7QCOcv5HiZdrBNBcZY+KAVsAz1tr307VPBJ4D\nPrbWDvJVfJKZMaYFUARYaK29mK69DPA9EAZ0tdZ+5aMQJZuMMQZYCoQDc4FhQH9r7VSfBiYeGWP6\nA1OAGcAAa+35y47ns9Ze8Elw4pHrfXE/cBioYa09lO5Yc2AFsMdae6ePQszzXOchAdgJNMMZhJpl\nre3poe/trn5FgUbW2vWu9oI457IB8KS19nMvhS8uuqSfS1yj6q2AvcCkyw6PBk4BvYwxRbwcmlyB\ntXaFtXZ++kTd1X4QmOy6+5DXA5OceAZoAfTB+X0TP2WMKQC8gXMlK1OiDqBE3S9Vwskj1qVP1AGs\ntSuBZJwrI+Ij1tqV1tod2bwa3BXnfH3uTtRdz3EWZ4QeYHAuhClXoWQ99zR33S7xkPglA/8GCgMP\nejswyTF3spDi0yjkqowx1YBxwLvW2tW+jkeuqiVOkjAXuOiaA/2SMeZZzXv2azuA80A9Y0xI+gPG\nmKZAMLDMF4FJjrRw3f4/D8dWA6eBhq4P1+JFmrOee+5x3W7P4vgOnJH3u4HlXolIcswYEwQ85brr\n6Y1M/ITrXM3EGaUd4eNwJHvqum7PApuA6ukPGmNW40w/O+ztwCRr1tpjxpiXgInAVmPM1zhz1ysD\nHXCmoQ30YYhybbLMW6y1KcaYPcB9wJ3ANm8GltcpWc89RV23v2dx3N1ezAuxyPUbh5NALLLWxvk6\nGLmiV4E/AI2ttWd8HYxkSynX7QvAVqAJ8CPOeoPxOAMb/0RT0PyOtfYfxpi9wDSgf7pDO4Hoy6fH\niF9T3uKnNA1G5CqMMc8AQ3Gq+fTycThyBcaY+jij6ROstfG+jkeyzf23KAXoYK391lp70lq7BeiM\ns0CumabE+B9jzItADBCNM6JeBKd6z25glqvCj4hcByXrucf9CbRoFsfd7Se8EIvkkDHmz8C7OKN9\nza21x3wckmTBNf3lU5xLuKN8HI5cG/f74CZr7d70B6y1pwH31ax63gxKrswY8xDwJvCNtfZ5a+1u\na+1pa+1GnA9Z+4GhxhhVg7k5KG/xU0rWc89/Xbd3Z3G8ius2qznt4mPGmP8D3gf+g5OoH/RxSHJl\nt+H8vlUDzqbbCMniVGACiHK1/cNnUYon7vfLrJKA467bQl6IRbKvnet25eUHXB+yvsfJM/7gzaAk\nx7LMW1yDIeE4V792ezMo0Zz13OR+82pljAm4rGZ3MM7mAqeBtb4ITq7MtWhqHM682ZbW2iM+Dkmu\n7hzwSRbHauMkDN/i/EHSFBn/shywwL2Xv1+6uBec7vFuWHIV7qogWZVndLdnKsUpfmkF8EcgAphz\n2bGmOBXsVltrz3k7sLxOI+u5xFq7C1gC3AEMuezwX3Hm9c201qr+s58xxozCSdQ3AA8rUb85WGvP\nWGuf9vSFsxsmwAxX2xe+jFUystbuA+YDFXF2eE5jjGkFtMYZdVclJv+yxnU7wBhTPv0BY0wbnEGp\nszg7eYv/i8HZgba7MeYBd6NrU6S/ue5+5IvA8jrtYJqLXBsjfYdT6SAWp9RRfZwa7NuBhtbao76L\nUC5njInEWSiVijMFxtOq+L3W2mgvhiXXyRjzGs5UGO1g6qeMMRVw3i/DcEbaN+Fcdu+EM+reXTsH\n+xdjTADOeoJHcDZAmgccxJmK1g4wwP9Za9/1WZB5nDGmE87vEEAZnA++u7n0QeuItXbYZf1jcD5k\nfQ4cwynDeY+rvVs2N1iSG0jJei4zxoQBr+NcVioJJOK8of3VWnv8So8V70uX1F3JKmvtQ7kfjdwo\nStZvDsaYUJzSmx2AskASTlIx1lr7vS9jE8+MMflwrh53B+7FmSpxDGe++nvW2iU+DC/Py8bftH3W\n2jsue0wj4BWgAVAQpwznNJzzmZo7kcqVKFkXEREREfFTmrMuIiIiIuKnlKyLiIiIiPgpJesiIiIi\nIn5KybqIiIiIiJ9Ssi4iIiIi4qeUrIuIiIiI+Ckl6yIiIiIifkrJuoiIiIiIn1KyLiIiIiLip5Ss\ni4iIiIj4KSXrIiIiIiJ+Ssm6iIiIiIifUrIuIiIiIuKnlKyLiIiIiPgpJesiIiIiIn5KybqIiIiI\niJ9Ssi4iIiIi4qf+PzWTlHixwFGkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f41f541d898>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 373
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the loss and accuracy curves for training and validation\n",
    "fig, ax = plt.subplots(2, 1)\n",
    "ax[0].plot(history.history['loss'], color='b', label=\"Training loss\")\n",
    "ax[0].plot(history.history['val_loss'], color='r', label=\"Validation loss\", axes=ax[0])\n",
    "legend = ax[0].legend(loc='best', shadow=True)\n",
    "\n",
    "ax[1].plot(history.history['acc'], color='b', label=\"Training accuracy\")\n",
    "ax[1].plot(history.history['val_acc'], color='r', label=\"Validation accuracy\")\n",
    "legend = ax[1].legend(loc='best', shadow=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 混淆矩阵"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'X_val' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-49-4e1dbe0a3b88>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     31\u001b[0m \u001b[0;31m# Predict the values from the validation dataset\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 32\u001b[0;31m \u001b[0mY_pred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_val\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     33\u001b[0m \u001b[0;31m# Convert predictions classes to one hot vectors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     34\u001b[0m \u001b[0mY_pred_classes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mY_pred\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'X_val' is not defined"
     ]
    }
   ],
   "source": [
    "## Look at confusion matrix\n",
    "\n",
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.Blues):\n",
    "    \"\"\"\n",
    "    This fuction prints and plots the confusion matrix.\n",
    "    Normalization can be applied by setting 'normalize=True'\n",
    "    \"\"\"\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "    \n",
    "    if normalize:\n",
    "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
    "        \n",
    "    thresh = cm.max() / 2.\n",
    "    for i,j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, cm[i, j],\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "        \n",
    "    plt.tight_layout()\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')\n",
    "    \n",
    "# Predict the values from the validation dataset\n",
    "Y_pred = model.predict(X_val)\n",
    "# Convert predictions classes to one hot vectors\n",
    "Y_pred_classes = np.argmax(Y_pred, axis=1)\n",
    "# Convert validation observations to one hot vectors\n",
    "Y_true = np.argmax(Y_val, axis=1)\n",
    "# Compute the confusion matrix\n",
    "confusion_mtx = confusion_matrix(Y_true, Y_pred_classes)\n",
    "# plt the confusion matrix\n",
    "plot_confusion_matrix(confusion_mtx, classes=range(n_class))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 误差审查"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image_id</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Images/collar_design_labels/60951f5761ea3a01d6...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Images/collar_design_labels/677e1183282769a3fe...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Images/collar_design_labels/3f5a2be205e5d253eb...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Images/collar_design_labels/1712bf3d7b57d779ad...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Images/collar_design_labels/0b2b4254f35ce3a41a...</td>\n",
       "      <td>collar_design_labels</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            image_id                 class\n",
       "0  Images/collar_design_labels/60951f5761ea3a01d6...  collar_design_labels\n",
       "1  Images/collar_design_labels/677e1183282769a3fe...  collar_design_labels\n",
       "2  Images/collar_design_labels/3f5a2be205e5d253eb...  collar_design_labels\n",
       "3  Images/collar_design_labels/1712bf3d7b57d779ad...  collar_design_labels\n",
       "4  Images/collar_design_labels/0b2b4254f35ce3a41a...  collar_design_labels"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test = pd.read_csv('./rank/Tests/question.csv', header=None)\n",
    "df_test.columns = ['image_id', 'class', 'x']\n",
    "del df_test['x']\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pant_length_labels: 949\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image_id</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Images/pant_length_labels/7e25106e7a0f5ac5d26a...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Images/pant_length_labels/3f96c13d864f387e5831...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Images/pant_length_labels/b09780a6311ce0b5c694...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Images/pant_length_labels/501a6f529fe8d80c7886...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Images/pant_length_labels/aaa48326bf7a20ad213f...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            image_id               class\n",
       "0  Images/pant_length_labels/7e25106e7a0f5ac5d26a...  pant_length_labels\n",
       "1  Images/pant_length_labels/3f96c13d864f387e5831...  pant_length_labels\n",
       "2  Images/pant_length_labels/b09780a6311ce0b5c694...  pant_length_labels\n",
       "3  Images/pant_length_labels/501a6f529fe8d80c7886...  pant_length_labels\n",
       "4  Images/pant_length_labels/aaa48326bf7a20ad213f...  pant_length_labels"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_load = df_test[(df_test['class'] == cur_class)].copy()\n",
    "df_load.reset_index(inplace=True)\n",
    "del df_load['index']\n",
    "\n",
    "print('{0}: {1}'.format(cur_class, len(df_load)))\n",
    "df_load.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./rank/Images/pant_length_labels/7e25106e7a0f5ac5d26a42fbe9648eaa.jpg'"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'./rank/{0}'.format(df_load['image_id'][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 949/949 [00:04<00:00, 203.12it/s]\n"
     ]
    }
   ],
   "source": [
    "n = len(df_load)\n",
    "X_test = np.zeros((n, width, width, 3), dtype=np.uint8)\n",
    "\n",
    "for i in tqdm(range(n)):\n",
    "    X_test[i] = cv2.resize(cv2.imread('./rank/{0}'.format(df_load['image_id'][i])), (width, width))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model.load_weights('./models/pant.best.h5')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "test_np = model.predict(X_test, batch_size=256)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(949, 6)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_np.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>image_id</th>\n",
       "      <th>class</th>\n",
       "      <th>result</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Images/pant_length_labels/7e25106e7a0f5ac5d26a...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>0.9487;0.0325;0.0013;0.0006;0.0054;0.0115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Images/pant_length_labels/3f96c13d864f387e5831...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>0.0000;0.0000;0.0001;0.0019;0.0336;0.9643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Images/pant_length_labels/b09780a6311ce0b5c694...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>0.0001;0.0001;0.0004;0.0021;0.0121;0.9851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Images/pant_length_labels/501a6f529fe8d80c7886...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>0.0003;0.9997;0.0000;0.0000;0.0000;0.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Images/pant_length_labels/aaa48326bf7a20ad213f...</td>\n",
       "      <td>pant_length_labels</td>\n",
       "      <td>0.0002;0.0000;0.0010;0.0170;0.7092;0.2725</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            image_id               class  \\\n",
       "0  Images/pant_length_labels/7e25106e7a0f5ac5d26a...  pant_length_labels   \n",
       "1  Images/pant_length_labels/3f96c13d864f387e5831...  pant_length_labels   \n",
       "2  Images/pant_length_labels/b09780a6311ce0b5c694...  pant_length_labels   \n",
       "3  Images/pant_length_labels/501a6f529fe8d80c7886...  pant_length_labels   \n",
       "4  Images/pant_length_labels/aaa48326bf7a20ad213f...  pant_length_labels   \n",
       "\n",
       "                                      result  \n",
       "0  0.9487;0.0325;0.0013;0.0006;0.0054;0.0115  \n",
       "1  0.0000;0.0000;0.0001;0.0019;0.0336;0.9643  \n",
       "2  0.0001;0.0001;0.0004;0.0021;0.0121;0.9851  \n",
       "3  0.0003;0.9997;0.0000;0.0000;0.0000;0.0000  \n",
       "4  0.0002;0.0000;0.0010;0.0170;0.7092;0.2725  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = []\n",
    "\n",
    "for i, row in df_load.iterrows():\n",
    "    tmp_list = test_np[i]\n",
    "    tmp_result = ''\n",
    "    for tmp_ret in tmp_list:\n",
    "        tmp_result += '{:.4f};'.format(tmp_ret)\n",
    "        \n",
    "    result.append(tmp_result[:-1])\n",
    "\n",
    "df_load['result'] = result\n",
    "df_load.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df_load.to_csv('./result/{}_0323b.csv'.format('pant'), header=None, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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