4_5_CM1_RESNET101_70_30_CUSTOM_LR.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "4.5 CM1-RESNET101-70:30-CUSTOM LR.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7JeP6eSnypEd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d18f8475-c017-41b8-98c1-a1f72a24f79e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Collecting msgpack-numpy>=0.4.4.2\n",
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            "Building wheels for collected packages: filterpy\n",
            "  Building wheel for filterpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for filterpy: filename=filterpy-1.4.5-py3-none-any.whl size=110474 sha256=5150460fc5ec3d0b4c2d2434a4fb1c20342eb2ea1215ccd623ccf60bed925188\n",
            "  Stored in directory: /root/.cache/pip/wheels/ce/e0/ee/a2b3c5caab3418c1ccd8c4de573d4cbe13315d7e8b0a55fbc2\n",
            "Successfully built filterpy\n",
            "Installing collected packages: scikit-image, ruamel.yaml.clib, msgpack-numpy, tf-slim, tensorpack, statsmodels, ruamel.yaml, imgaug, filterpy, deeplabcut\n",
            "  Attempting uninstall: scikit-image\n",
            "    Found existing installation: scikit-image 0.18.3\n",
            "    Uninstalling scikit-image-0.18.3:\n",
            "      Successfully uninstalled scikit-image-0.18.3\n",
            "  Attempting uninstall: statsmodels\n",
            "    Found existing installation: statsmodels 0.10.2\n",
            "    Uninstalling statsmodels-0.10.2:\n",
            "      Successfully uninstalled statsmodels-0.10.2\n",
            "  Attempting uninstall: imgaug\n",
            "    Found existing installation: imgaug 0.2.9\n",
            "    Uninstalling imgaug-0.2.9:\n",
            "      Successfully uninstalled imgaug-0.2.9\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.4.0 which is incompatible.\u001b[0m\n",
            "Successfully installed deeplabcut-2.2.0.5 filterpy-1.4.5 imgaug-0.4.0 msgpack-numpy-0.4.7.1 ruamel.yaml-0.17.20 ruamel.yaml.clib-0.2.6 scikit-image-0.18.1 statsmodels-0.13.1 tensorpack-0.11 tf-slim-1.1.0\n"
          ]
        }
      ],
      "source": [
        "#INSTALLING DLC , MUST TO BE REINSTALLED WHEN RESTARTING RUNTIME\n",
        "!pip install deeplabcut "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%tensorflow_version 1.x"
      ],
      "metadata": {
        "id": "Y2ukI3ptzP85",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a2bfafc1-0a05-42c9-d4d4-0e7430a8296a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "TensorFlow 1.x selected.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ[\"DLClight\"]=\"True\""
      ],
      "metadata": {
        "id": "605aP-frzS_9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# DLC LIBRARY MUST BE IMPORTED BEFORE USE\n",
        "import deeplabcut"
      ],
      "metadata": {
        "id": "SagmIauLzVvb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f7c7fc90-cd16-4505-c317-e8213aac7474"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "DLC loaded in light mode; you cannot use any GUI (labeling, relabeling and standalone GUI)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#connecting to google drive, where your project folder is located\n",
        "from google.colab import drive \n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "id": "yDMkNANYzYJw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7c1e8058-4c0c-4a07-92e4-1779028fa68a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#here is where you specify the project folder\n",
        "!ls \"/content/drive/MyDrive\"\n",
        "ProjectFolderName = 'largewithaug-amir-2021-12-20' #change here!\n",
        "\n",
        "VideoType = 'mp4' "
      ],
      "metadata": {
        "id": "cRZYeSxxzYxL",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7a2569aa-fb25-48c0-817f-1e1175c1c1de"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " AYAMFINAL-AMIR-2021-10-07      MULTITEST1-AMIR-2021-11-03\n",
            "'belum di trained'\t        temp\n",
            " CHICKEN5-AMIR-2021-10-09      'temp 2'\n",
            "'Colab Notebooks'\t       'TRAINED BACKUP1'\n",
            "'Copy of learning_stats.csv'   'UNTRAINED BU1 AND 2'\n",
            " DMANIP\t\t\t        VIDDATASET\n",
            " largewithaug-amir-2021-12-20   VIDDATASET2\n",
            "'MESSED UP'\t\t        VIDDATASET3\n",
            " MISC\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "project_path = '/content/drive/MyDrive/'+ ProjectFolderName\n",
        "videofile_path = ['/content/drive/MyDrive/'+ProjectFolderName+'/videos/']\n",
        "path_config_file = '/content/drive/MyDrive/'+ProjectFolderName+'/config.yaml'\n",
        "\n",
        "print('NEW project_path: ' + project_path)\n",
        "print('NEW path_config_file: ' + path_config_file)\n",
        "print('NEW videofile_path: ' + videofile_path[0])"
      ],
      "metadata": {
        "id": "LCy10Yh5za6o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fc036434-d5b5-4ec7-f0ce-d2dde2a4f68f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "NEW project_path: /content/drive/MyDrive/largewithaug-amir-2021-12-20\n",
            "NEW path_config_file: /content/drive/MyDrive/largewithaug-amir-2021-12-20/config.yaml\n",
            "NEW videofile_path: /content/drive/MyDrive/largewithaug-amir-2021-12-20/videos/\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# CHANGE EVERYTIME U START A NEW PROJECT\n",
        "!ls '/content/drive/MyDrive/largewithaug-amir-2021-12-20' \n",
        "#depending on the project folder name, this command will show you the content of the project folder"
      ],
      "metadata": {
        "id": "hFyp-NnL3VYh",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ffad0506-82a0-49b4-c3d3-ad8933cda870"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "config.yaml  labeled-data  videos\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**END OF LIBRARY INSTALLATION / FILE CONFIGURATION**"
      ],
      "metadata": {
        "id": "LDrZcN5arOyM"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**STARTING OF DATASET SPLITTING (base on the TrainingFraction parameters stated within the config.yaml file) AND TRAINING PROCESS**"
      ],
      "metadata": {
        "id": "5OHGbQeYrycn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#CREATE TRAINING DATASET, SPLIT INTO TRAIN AND TEST DATASET, DOWNLOAD THE PRETRAINED MODEL\n",
        "deeplabcut.create_training_dataset(path_config_file, net_type='resnet_101', augmenter_type='imgaug')"
      ],
      "metadata": {
        "id": "Jnz8tq6I3kJ0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f3ee7783-0236-45df-c5b6-cebd7cc0c8d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading a ImageNet-pretrained model from http://download.tensorflow.org/models/resnet_v1_101_2016_08_28.tar.gz....\n",
            "The training dataset is successfully created. Use the function 'train_network' to start training. Happy training!\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[(0.7,\n",
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            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "AFTER CREATING DATASET, THE LEARNING RATE IS CHANGE WITHIN THE pose_cfg.yaml file within the dlc_model train subdirectory"
      ],
      "metadata": {
        "id": "FUXol6oQWiS2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#TRAIN THE PRETRAINED MODEL WITH THE POULTRY DATASET\n",
        "deeplabcut.train_network(path_config_file, shuffle=1, displayiters=100, saveiters=100)"
      ],
      "metadata": {
        "id": "AWfwfTuC3x43",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "f8a567ff-e7e7-4417-8ba0-ccd022951256"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Config:\n",
            "{'all_joints': [[0], [1], [2], [3], [4]],\n",
            " 'all_joints_names': ['center', 'head', 'tail', 'leftleg', 'rightleg'],\n",
            " 'alpha_r': 0.02,\n",
            " 'apply_prob': 0.5,\n",
            " 'batch_size': 1,\n",
            " 'clahe': True,\n",
            " 'claheratio': 0.1,\n",
            " 'crop_pad': 0,\n",
            " 'crop_sampling': 'hybrid',\n",
            " 'crop_size': [400, 400],\n",
            " 'cropratio': 0.4,\n",
            " 'dataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/largewithaug_amir70shuffle1.mat',\n",
            " 'dataset_type': 'imgaug',\n",
            " 'decay_steps': 30000,\n",
            " 'deterministic': False,\n",
            " 'display_iters': 1000,\n",
            " 'edge': False,\n",
            " 'emboss': {'alpha': [0.0, 1.0], 'embossratio': 0.1, 'strength': [0.5, 1.5]},\n",
            " 'fg_fraction': 0.25,\n",
            " 'global_scale': 0.8,\n",
            " 'histeq': True,\n",
            " 'histeqratio': 0.1,\n",
            " 'init_weights': '/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_101.ckpt',\n",
            " 'intermediate_supervision': False,\n",
            " 'intermediate_supervision_layer': 12,\n",
            " 'location_refinement': True,\n",
            " 'locref_huber_loss': True,\n",
            " 'locref_loss_weight': 0.05,\n",
            " 'locref_stdev': 7.2801,\n",
            " 'log_dir': 'log',\n",
            " 'lr_init': 0.0005,\n",
            " 'max_input_size': 1500,\n",
            " 'max_shift': 0.4,\n",
            " 'mean_pixel': [123.68, 116.779, 103.939],\n",
            " 'metadataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/Documentation_data-largewithaug_70shuffle1.pickle',\n",
            " 'min_input_size': 64,\n",
            " 'mirror': False,\n",
            " 'multi_stage': False,\n",
            " 'multi_step': [[0.005, 10000],\n",
            "                [0.02, 214400],\n",
            "                [0.005, 730000],\n",
            "                [0.001, 1030000]],\n",
            " 'net_type': 'resnet_101',\n",
            " 'num_joints': 5,\n",
            " 'optimizer': 'sgd',\n",
            " 'pairwise_huber_loss': False,\n",
            " 'pairwise_predict': False,\n",
            " 'partaffinityfield_predict': False,\n",
            " 'pos_dist_thresh': 17,\n",
            " 'pre_resize': [],\n",
            " 'project_path': '/content/drive/MyDrive/largewithaug-amir-2021-12-20',\n",
            " 'regularize': False,\n",
            " 'rotation': 25,\n",
            " 'rotratio': 0.4,\n",
            " 'save_iters': 50000,\n",
            " 'scale_jitter_lo': 0.5,\n",
            " 'scale_jitter_up': 1.25,\n",
            " 'scoremap_dir': 'test',\n",
            " 'sharpen': False,\n",
            " 'sharpenratio': 0.3,\n",
            " 'shuffle': True,\n",
            " 'snapshot_prefix': '/content/drive/MyDrive/largewithaug-amir-2021-12-20/dlc-models/iteration-0/largewithaugDec20-trainset70shuffle1/train/snapshot',\n",
            " 'stride': 8.0,\n",
            " 'weigh_negatives': False,\n",
            " 'weigh_only_present_joints': False,\n",
            " 'weigh_part_predictions': False,\n",
            " 'weight_decay': 0.0001}\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Selecting single-animal trainer\n",
            "Batch Size is 1\n",
            "Loading ImageNet-pretrained resnet_101\n",
            "Display_iters overwritten as 100\n",
            "Save_iters overwritten as 100\n",
            "Training parameter:\n",
            "{'stride': 8.0, 'weigh_part_predictions': False, 'weigh_negatives': False, 'fg_fraction': 0.25, 'mean_pixel': [123.68, 116.779, 103.939], 'shuffle': True, 'snapshot_prefix': '/content/drive/MyDrive/largewithaug-amir-2021-12-20/dlc-models/iteration-0/largewithaugDec20-trainset70shuffle1/train/snapshot', 'log_dir': 'log', 'global_scale': 0.8, 'location_refinement': True, 'locref_stdev': 7.2801, 'locref_loss_weight': 0.05, 'locref_huber_loss': True, 'optimizer': 'sgd', 'intermediate_supervision': False, 'intermediate_supervision_layer': 12, 'regularize': False, 'weight_decay': 0.0001, 'crop_pad': 0, 'scoremap_dir': 'test', 'batch_size': 1, 'dataset_type': 'imgaug', 'deterministic': False, 'mirror': False, 'pairwise_huber_loss': False, 'weigh_only_present_joints': False, 'partaffinityfield_predict': False, 'pairwise_predict': False, 'all_joints': [[0], [1], [2], [3], [4]], 'all_joints_names': ['center', 'head', 'tail', 'leftleg', 'rightleg'], 'alpha_r': 0.02, 'apply_prob': 0.5, 'clahe': True, 'claheratio': 0.1, 'crop_sampling': 'hybrid', 'crop_size': [400, 400], 'cropratio': 0.4, 'dataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/largewithaug_amir70shuffle1.mat', 'decay_steps': 30000, 'display_iters': 1000, 'edge': False, 'emboss': {'alpha': [0.0, 1.0], 'embossratio': 0.1, 'strength': [0.5, 1.5]}, 'histeq': True, 'histeqratio': 0.1, 'init_weights': '/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_101.ckpt', 'lr_init': 0.0005, 'max_input_size': 1500, 'max_shift': 0.4, 'metadataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/Documentation_data-largewithaug_70shuffle1.pickle', 'min_input_size': 64, 'multi_stage': False, 'multi_step': [[0.005, 10000], [0.02, 214400], [0.005, 730000], [0.001, 1030000]], 'net_type': 'resnet_101', 'num_joints': 5, 'pos_dist_thresh': 17, 'pre_resize': [], 'project_path': '/content/drive/MyDrive/largewithaug-amir-2021-12-20', 'rotation': 25, 'rotratio': 0.4, 'save_iters': 50000, 'scale_jitter_lo': 0.5, 'scale_jitter_up': 1.25, 'sharpen': False, 'sharpenratio': 0.3, 'covering': True, 'elastic_transform': True, 'motion_blur': True, 'motion_blur_params': {'k': 7, 'angle': (-90, 90)}}\n",
            "Starting training....\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
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            "iteration: 299800 loss: 0.0026 lr: 0.005\n",
            "iteration: 299900 loss: 0.0020 lr: 0.005\n",
            "iteration: 300000 loss: 0.0021 lr: 0.005\n",
            "iteration: 300100 loss: 0.0022 lr: 0.005\n",
            "iteration: 300200 loss: 0.0021 lr: 0.005\n",
            "iteration: 300300 loss: 0.0024 lr: 0.005\n",
            "iteration: 300400 loss: 0.0023 lr: 0.005\n",
            "iteration: 300500 loss: 0.0021 lr: 0.005\n",
            "iteration: 300600 loss: 0.0021 lr: 0.005\n",
            "Internal Python error in the inspect module.\n",
            "Below is the traceback from this internal error.\n",
            "\n",
            "\n",
            "Unfortunately, your original traceback can not be constructed.\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py\", line 2882, in run_code\n",
            "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
            "  File \"<ipython-input-10-86db631e8860>\", line 2, in <module>\n",
            "    deeplabcut.train_network(path_config_file, shuffle=1, displayiters=100, saveiters=100)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/training.py\", line 189, in train_network\n",
            "    raise e\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/training.py\", line 185, in train_network\n",
            "    allow_growth=allow_growth,\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/core/train.py\", line 273, in train\n",
            "    [train_op, total_loss, merged_summaries], feed_dict=dict\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py\", line 956, in run\n",
            "    run_metadata_ptr)\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py\", line 1180, in _run\n",
            "    feed_dict_tensor, options, run_metadata)\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py\", line 1359, in _do_run\n",
            "    run_metadata)\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py\", line 1365, in _do_call\n",
            "    return fn(*args)\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py\", line 1350, in _run_fn\n",
            "    target_list, run_metadata)\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/python/client/session.py\", line 1443, in _call_tf_sessionrun\n",
            "    run_metadata)\n",
            "KeyboardInterrupt\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py\", line 1823, in showtraceback\n",
            "    stb = value._render_traceback_()\n",
            "AttributeError: 'KeyboardInterrupt' object has no attribute '_render_traceback_'\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 87, in _path_is_mode_type\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 81, in _path_stat\n",
            "FileNotFoundError: [Errno 2] No such file or directory: '/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/python/ops/__init__.cpython-37m-x86_64-linux-gnu.so'\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/IPython/core/ultratb.py\", line 1132, in get_records\n",
            "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/IPython/core/ultratb.py\", line 313, in wrapped\n",
            "    return f(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.7/dist-packages/IPython/core/ultratb.py\", line 358, in _fixed_getinnerframes\n",
            "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
            "  File \"/usr/lib/python3.7/inspect.py\", line 1502, in getinnerframes\n",
            "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
            "  File \"/usr/lib/python3.7/inspect.py\", line 1460, in getframeinfo\n",
            "    filename = getsourcefile(frame) or getfile(frame)\n",
            "  File \"/usr/lib/python3.7/inspect.py\", line 696, in getsourcefile\n",
            "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
            "  File \"/usr/lib/python3.7/inspect.py\", line 733, in getmodule\n",
            "    if ismodule(module) and hasattr(module, '__file__'):\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow/__init__.py\", line 50, in __getattr__\n",
            "    module = self._load()\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow/__init__.py\", line 44, in _load\n",
            "    module = _importlib.import_module(self.__name__)\n",
            "  File \"/usr/lib/python3.7/importlib/__init__.py\", line 127, in import_module\n",
            "    return _bootstrap._gcd_import(name[level:], package, level)\n",
            "  File \"<frozen importlib._bootstrap>\", line 1006, in _gcd_import\n",
            "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
            "  File \"<frozen importlib._bootstrap>\", line 967, in _find_and_load_unlocked\n",
            "  File \"<frozen importlib._bootstrap>\", line 677, in _load_unlocked\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 728, in exec_module\n",
            "  File \"<frozen importlib._bootstrap>\", line 219, in _call_with_frames_removed\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/__init__.py\", line 90, in <module>\n",
            "    from tensorflow.contrib import tensor_forest\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/__init__.py\", line 21, in <module>\n",
            "    from tensorflow.contrib.tensor_forest.client import *\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/__init__.py\", line 21, in <module>\n",
            "    from tensorflow.contrib.tensor_forest.client import *\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/client/__init__.py\", line 22, in <module>\n",
            "    from tensorflow.contrib.tensor_forest.client import random_forest\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/client/random_forest.py\", line 27, in <module>\n",
            "    from tensorflow.contrib.tensor_forest.python import tensor_forest\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/python/__init__.py\", line 21, in <module>\n",
            "    from tensorflow.contrib.tensor_forest.python import tensor_forest\n",
            "  File \"/tensorflow-1.15.2/python3.7/tensorflow_core/contrib/tensor_forest/python/tensor_forest.py\", line 29, in <module>\n",
            "    from tensorflow.contrib.tensor_forest.python.ops import data_ops\n",
            "  File \"<frozen importlib._bootstrap>\", line 983, in _find_and_load\n",
            "  File \"<frozen importlib._bootstrap>\", line 963, in _find_and_load_unlocked\n",
            "  File \"<frozen importlib._bootstrap>\", line 906, in _find_spec\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 1280, in find_spec\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 1252, in _get_spec\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 1383, in find_spec\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 95, in _path_isfile\n",
            "  File \"<frozen importlib._bootstrap_external>\", line 87, in _path_is_mode_type\n",
            "KeyboardInterrupt\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**EVALUATION**"
      ],
      "metadata": {
        "id": "UZ0NSqWCr8WU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#300,000 ######################CHOSEN\n",
        "%matplotlib notebook\n",
        "deeplabcut.evaluate_network(path_config_file,plotting=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zym8gb3qYATP",
        "outputId": "fc3d00ed-30bb-4388-f2d8-c971ca2c9cf2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Config:\n",
            "{'all_joints': [[0], [1], [2], [3], [4]],\n",
            " 'all_joints_names': ['center', 'head', 'tail', 'leftleg', 'rightleg'],\n",
            " 'batch_size': 1,\n",
            " 'crop_pad': 0,\n",
            " 'dataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/largewithaug_amir70shuffle1.mat',\n",
            " 'dataset_type': 'imgaug',\n",
            " 'deterministic': False,\n",
            " 'fg_fraction': 0.25,\n",
            " 'global_scale': 0.8,\n",
            " 'init_weights': '/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_101.ckpt',\n",
            " 'intermediate_supervision': False,\n",
            " 'intermediate_supervision_layer': 12,\n",
            " 'location_refinement': True,\n",
            " 'locref_huber_loss': True,\n",
            " 'locref_loss_weight': 1.0,\n",
            " 'locref_stdev': 7.2801,\n",
            " 'log_dir': 'log',\n",
            " 'mean_pixel': [123.68, 116.779, 103.939],\n",
            " 'mirror': False,\n",
            " 'net_type': 'resnet_101',\n",
            " 'num_joints': 5,\n",
            " 'optimizer': 'sgd',\n",
            " 'pairwise_huber_loss': True,\n",
            " 'pairwise_predict': False,\n",
            " 'partaffinityfield_predict': False,\n",
            " 'regularize': False,\n",
            " 'scoremap_dir': 'test',\n",
            " 'shuffle': True,\n",
            " 'snapshot_prefix': '/content/drive/MyDrive/largewithaug-amir-2021-12-20/dlc-models/iteration-0/largewithaugDec20-trainset70shuffle1/test/snapshot',\n",
            " 'stride': 8.0,\n",
            " 'weigh_negatives': False,\n",
            " 'weigh_only_present_joints': False,\n",
            " 'weigh_part_predictions': False,\n",
            " 'weight_decay': 0.0001}\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Running  DLC_resnet101_largewithaugDec20shuffle1_300600  with # of training iterations: 300600\n",
            "Running evaluation ...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "256it [01:15,  3.40it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Analysis is done and the results are stored (see evaluation-results) for snapshot:  snapshot-300600\n",
            "Results for 300600  training iterations: 70 1 train error: 2.75 pixels. Test error: 16.24  pixels.\n",
            "With pcutoff of 0.6  train error: 2.74 pixels. Test error: 9.61 pixels\n",
            "Thereby, the errors are given by the average distances between the labels by DLC and the scorer.\n",
            "The network is evaluated and the results are stored in the subdirectory 'evaluation_results'.\n",
            "Please check the results, then choose the best model (snapshot) for prediction. You can update the config.yaml file with the appropriate index for the 'snapshotindex'.\n",
            "Use the function 'analyze_video' to make predictions on new videos.\n",
            "Otherwise, consider adding more labeled-data and retraining the network (see DeepLabCut workflow Fig 2, Nath 2019)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#200K ####CHOSEN\n",
        "%matplotlib notebook\n",
        "deeplabcut.evaluate_network(path_config_file,plotting=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wXmBO1Z-1Nmq",
        "outputId": "99344083-12c0-456b-9690-c07faaaa1c56"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Config:\n",
            "{'all_joints': [[0], [1], [2], [3], [4]],\n",
            " 'all_joints_names': ['center', 'head', 'tail', 'leftleg', 'rightleg'],\n",
            " 'batch_size': 1,\n",
            " 'crop_pad': 0,\n",
            " 'dataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/largewithaug_amir70shuffle1.mat',\n",
            " 'dataset_type': 'imgaug',\n",
            " 'deterministic': False,\n",
            " 'fg_fraction': 0.25,\n",
            " 'global_scale': 0.8,\n",
            " 'init_weights': '/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_101.ckpt',\n",
            " 'intermediate_supervision': False,\n",
            " 'intermediate_supervision_layer': 12,\n",
            " 'location_refinement': True,\n",
            " 'locref_huber_loss': True,\n",
            " 'locref_loss_weight': 1.0,\n",
            " 'locref_stdev': 7.2801,\n",
            " 'log_dir': 'log',\n",
            " 'mean_pixel': [123.68, 116.779, 103.939],\n",
            " 'mirror': False,\n",
            " 'net_type': 'resnet_101',\n",
            " 'num_joints': 5,\n",
            " 'optimizer': 'sgd',\n",
            " 'pairwise_huber_loss': True,\n",
            " 'pairwise_predict': False,\n",
            " 'partaffinityfield_predict': False,\n",
            " 'regularize': False,\n",
            " 'scoremap_dir': 'test',\n",
            " 'shuffle': True,\n",
            " 'snapshot_prefix': '/content/drive/MyDrive/largewithaug-amir-2021-12-20/dlc-models/iteration-0/largewithaugDec20-trainset70shuffle1/test/snapshot',\n",
            " 'stride': 8.0,\n",
            " 'weigh_negatives': False,\n",
            " 'weigh_only_present_joints': False,\n",
            " 'weigh_part_predictions': False,\n",
            " 'weight_decay': 0.0001}\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Running  DLC_resnet101_largewithaugDec20shuffle1_200000  with # of training iterations: 200000\n",
            "Running evaluation ...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "256it [00:31,  8.21it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Analysis is done and the results are stored (see evaluation-results) for snapshot:  snapshot-200000\n",
            "Results for 200000  training iterations: 70 1 train error: 2.92 pixels. Test error: 17.47  pixels.\n",
            "With pcutoff of 0.6  train error: 2.92 pixels. Test error: 9.02 pixels\n",
            "Thereby, the errors are given by the average distances between the labels by DLC and the scorer.\n",
            "The network is evaluated and the results are stored in the subdirectory 'evaluation_results'.\n",
            "Please check the results, then choose the best model (snapshot) for prediction. You can update the config.yaml file with the appropriate index for the 'snapshotindex'.\n",
            "Use the function 'analyze_video' to make predictions on new videos.\n",
            "Otherwise, consider adding more labeled-data and retraining the network (see DeepLabCut workflow Fig 2, Nath 2019)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#100K\n",
        "%matplotlib notebook\n",
        "deeplabcut.evaluate_network(path_config_file,plotting=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MBsImn8T1PhC",
        "outputId": "4e6cf0a1-bcfc-4e19-dc0a-5a4196480650"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Config:\n",
            "{'all_joints': [[0], [1], [2], [3], [4]],\n",
            " 'all_joints_names': ['center', 'head', 'tail', 'leftleg', 'rightleg'],\n",
            " 'batch_size': 1,\n",
            " 'crop_pad': 0,\n",
            " 'dataset': 'training-datasets/iteration-0/UnaugmentedDataSet_largewithaugDec20/largewithaug_amir70shuffle1.mat',\n",
            " 'dataset_type': 'imgaug',\n",
            " 'deterministic': False,\n",
            " 'fg_fraction': 0.25,\n",
            " 'global_scale': 0.8,\n",
            " 'init_weights': '/usr/local/lib/python3.7/dist-packages/deeplabcut/pose_estimation_tensorflow/models/pretrained/resnet_v1_101.ckpt',\n",
            " 'intermediate_supervision': False,\n",
            " 'intermediate_supervision_layer': 12,\n",
            " 'location_refinement': True,\n",
            " 'locref_huber_loss': True,\n",
            " 'locref_loss_weight': 1.0,\n",
            " 'locref_stdev': 7.2801,\n",
            " 'log_dir': 'log',\n",
            " 'mean_pixel': [123.68, 116.779, 103.939],\n",
            " 'mirror': False,\n",
            " 'net_type': 'resnet_101',\n",
            " 'num_joints': 5,\n",
            " 'optimizer': 'sgd',\n",
            " 'pairwise_huber_loss': True,\n",
            " 'pairwise_predict': False,\n",
            " 'partaffinityfield_predict': False,\n",
            " 'regularize': False,\n",
            " 'scoremap_dir': 'test',\n",
            " 'shuffle': True,\n",
            " 'snapshot_prefix': '/content/drive/MyDrive/largewithaug-amir-2021-12-20/dlc-models/iteration-0/largewithaugDec20-trainset70shuffle1/test/snapshot',\n",
            " 'stride': 8.0,\n",
            " 'weigh_negatives': False,\n",
            " 'weigh_only_present_joints': False,\n",
            " 'weigh_part_predictions': False,\n",
            " 'weight_decay': 0.0001}\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Running  DLC_resnet101_largewithaugDec20shuffle1_100000  with # of training iterations: 100000\n",
            "Running evaluation ...\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "256it [00:31,  8.24it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Analysis is done and the results are stored (see evaluation-results) for snapshot:  snapshot-100000\n",
            "Results for 100000  training iterations: 70 1 train error: 3.18 pixels. Test error: 18.49  pixels.\n",
            "With pcutoff of 0.6  train error: 3.0 pixels. Test error: 9.38 pixels\n",
            "Thereby, the errors are given by the average distances between the labels by DLC and the scorer.\n",
            "The network is evaluated and the results are stored in the subdirectory 'evaluation_results'.\n",
            "Please check the results, then choose the best model (snapshot) for prediction. You can update the config.yaml file with the appropriate index for the 'snapshotindex'.\n",
            "Use the function 'analyze_video' to make predictions on new videos.\n",
            "Otherwise, consider adding more labeled-data and retraining the network (see DeepLabCut workflow Fig 2, Nath 2019)\n"
          ]
        }
      ]
    }
  ]
}