pose_estimation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Copy of pose-estimation",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/fubarlabs/aistudygroup/blob/master/pose_estimation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ebIKr1mDwMx8",
        "colab_type": "text"
      },
      "source": [
        "# Pose Estimation for Ai Stdy group\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B1lYlyibwBBE",
        "colab_type": "code",
        "outputId": "6de28e6e-12a8-4ca1-e5e9-4587766a40bc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "print(\"hello world\")"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "hello world\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Goya6Z1h4_tA",
        "colab_type": "code",
        "outputId": "d1b52299-42d2-4bc1-dd42-fc1c73457ee3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        }
      },
      "source": [
        "!git clone https://github.com/ildoonet/tf-pose-estimation/\n",
        "!cd tf-pose-estimation"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'tf-pose-estimation'...\n",
            "remote: Enumerating objects: 1362, done.\u001b[K\n",
            "remote: Total 1362 (delta 0), reused 0 (delta 0), pack-reused 1362\u001b[K\n",
            "Receiving objects: 100% (1362/1362), 94.13 MiB | 28.61 MiB/s, done.\n",
            "Resolving deltas: 100% (729/729), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ibwM7kp25s7u",
        "colab_type": "code",
        "outputId": "15cba13c-9cf5-4fe7-ab31-66403538f632",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        }
      },
      "source": [
        "!pwd\n",
        "!ls\n",
        "%cd tf-pose-estimation"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation\n",
            "CMakeLists.txt\tlaunch\t     requirements.txt\tscripts\n",
            "docker\t\tLICENSE      run_checkpoint.py\tsetup.py\n",
            "Dockerfile\tmodels\t     run_directory.py\ttf_pose\n",
            "etcs\t\tmsg\t     run.py\t\ttf-pose-estimation\n",
            "images\t\tpackage.xml  run_video.py\n",
            "__init__.py\tREADME.md    run_webcam.py\n",
            "/content/tf-pose-estimation/tf-pose-estimation\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tWGPMp2E6NhE",
        "colab_type": "code",
        "outputId": "f8138877-3aa6-4987-93d2-9b2be4530370",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "!pwd\n"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation/tf-pose-estimation\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jW8r99_s7BwI",
        "colab_type": "code",
        "outputId": "59005c8b-46e1-4bcc-a741-7b6093d06e27",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 839
        }
      },
      "source": [
        "!pip3 install -r requirements.txt"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting git+https://github.com/ppwwyyxx/tensorpack.git (from -r requirements.txt (line 13))\n",
            "  Cloning https://github.com/ppwwyyxx/tensorpack.git to /tmp/pip-req-build-b3sase8e\n",
            "  Running command git clone -q https://github.com/ppwwyyxx/tensorpack.git /tmp/pip-req-build-b3sase8e\n",
            "Requirement already satisfied (use --upgrade to upgrade): tensorpack==0.9.8 from git+https://github.com/ppwwyyxx/tensorpack.git in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 13))\n",
            "Requirement already satisfied: argparse in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 1)) (1.4.0)\n",
            "Requirement already satisfied: dill in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 2)) (0.3.1.1)\n",
            "Requirement already satisfied: fire in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 3)) (0.2.1)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 4)) (3.1.1)\n",
            "Requirement already satisfied: numba in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 5)) (0.40.1)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 6)) (5.4.8)\n",
            "Requirement already satisfied: pycocotools in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 7)) (2.0.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 8)) (2.21.0)\n",
            "Requirement already satisfied: scikit-image in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 9)) (0.15.0)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 10)) (1.3.1)\n",
            "Requirement already satisfied: slidingwindow in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 11)) (0.0.13)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.6/dist-packages (from -r requirements.txt (line 12)) (4.28.1)\n",
            "Requirement already satisfied: numpy>=1.14 in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (1.17.3)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (1.12.0)\n",
            "Requirement already satisfied: termcolor>=1.1 in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (1.1.0)\n",
            "Requirement already satisfied: tabulate>=0.7.7 in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (0.8.5)\n",
            "Requirement already satisfied: msgpack>=0.5.2 in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (0.5.6)\n",
            "Requirement already satisfied: msgpack-numpy>=0.4.4.2 in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (0.4.4.3)\n",
            "Requirement already satisfied: pyzmq>=16 in /usr/local/lib/python3.6/dist-packages (from tensorpack==0.9.8->-r requirements.txt (line 13)) (17.0.0)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 4)) (2.4.2)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 4)) (0.10.0)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 4)) (2.6.1)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->-r requirements.txt (line 4)) (1.1.0)\n",
            "Requirement already satisfied: llvmlite>=0.25.0dev0 in /usr/local/lib/python3.6/dist-packages (from numba->-r requirements.txt (line 5)) (0.30.0)\n",
            "Requirement already satisfied: idna<2.9,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->-r requirements.txt (line 8)) (2.8)\n",
            "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->-r requirements.txt (line 8)) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->-r requirements.txt (line 8)) (2019.9.11)\n",
            "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->-r requirements.txt (line 8)) (3.0.4)\n",
            "Requirement already satisfied: pillow>=4.3.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image->-r requirements.txt (line 9)) (4.3.0)\n",
            "Requirement already satisfied: imageio>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from scikit-image->-r requirements.txt (line 9)) (2.4.1)\n",
            "Requirement already satisfied: PyWavelets>=0.4.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image->-r requirements.txt (line 9)) (1.1.1)\n",
            "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.6/dist-packages (from scikit-image->-r requirements.txt (line 9)) (2.4)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from kiwisolver>=1.0.1->matplotlib->-r requirements.txt (line 4)) (41.4.0)\n",
            "Requirement already satisfied: olefile in /usr/local/lib/python3.6/dist-packages (from pillow>=4.3.0->scikit-image->-r requirements.txt (line 9)) (0.46)\n",
            "Requirement already satisfied: decorator>=4.3.0 in /usr/local/lib/python3.6/dist-packages (from networkx>=2.0->scikit-image->-r requirements.txt (line 9)) (4.4.1)\n",
            "Building wheels for collected packages: tensorpack\n",
            "  Building wheel for tensorpack (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for tensorpack: filename=tensorpack-0.9.8-py2.py3-none-any.whl size=291856 sha256=5bddf6227e4b087bac5c373937fff06c68b1228465ce327250cb6cb34214071d\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-1q7ijf5l/wheels/a8/b5/a9/025b3a1294b9ffff93309e6956c65aa80e0fa40821d29eff1e\n",
            "Successfully built tensorpack\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DRxYf1Vj8T-2",
        "colab_type": "code",
        "outputId": "667f6553-027d-4415-af04-9a5573a29ce9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "%cd tf_pose/pafprocess"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation/tf-pose-estimation/tf_pose/pafprocess\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rTIAUFCJ81f4",
        "colab_type": "code",
        "outputId": "9d2e6df0-cb9a-43e3-8392-80cc80960907",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 108
        }
      },
      "source": [
        "!sudo apt-get install swig"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "swig is already the newest version (3.0.12-1).\n",
            "0 upgraded, 0 newly installed, 0 to remove and 28 not upgraded.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IVDCPzdw9BWU",
        "colab_type": "code",
        "outputId": "e70a589d-3109-446c-90c8-1d0978ffd3c0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 201
        }
      },
      "source": [
        "!swig -python -c++ pafprocess.i && python3 setup.py build_ext --inplace\n"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "running build_ext\n",
            "building '_pafprocess' extension\n",
            "swigging pafprocess.i to pafprocess_wrap.cpp\n",
            "swig -python -c++ -o pafprocess_wrap.cpp pafprocess.i\n",
            "creating build\n",
            "creating build/temp.linux-x86_64-3.6\n",
            "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/numpy/core/include -I. -I/usr/include/python3.6m -c pafprocess.cpp -o build/temp.linux-x86_64-3.6/pafprocess.o\n",
            "x86_64-linux-gnu-gcc -pthread -DNDEBUG -g -fwrapv -O2 -Wall -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/local/lib/python3.6/dist-packages/numpy/core/include -I. -I/usr/include/python3.6m -c pafprocess_wrap.cpp -o build/temp.linux-x86_64-3.6/pafprocess_wrap.o\n",
            "x86_64-linux-gnu-g++ -pthread -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-Bsymbolic-functions -Wl,-z,relro -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fstack-protector-strong -Wformat -Werror=format-security -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-3.6/pafprocess.o build/temp.linux-x86_64-3.6/pafprocess_wrap.o -o /content/tf-pose-estimation/tf-pose-estimation/tf_pose/pafprocess/_pafprocess.cpython-36m-x86_64-linux-gnu.so\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OoU7r6jY9Iws",
        "colab_type": "code",
        "outputId": "a1f3973f-52e7-4be5-c659-48915cde922f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        }
      },
      "source": [
        "%cd ../../models/\n",
        "!pwd\n"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation/tf-pose-estimation/models\n",
            "/content/tf-pose-estimation/tf-pose-estimation/models\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g8VpQXP39aXe",
        "colab_type": "code",
        "outputId": "96677cf2-b329-4763-ef59-f3eedfa2879c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "%cd graph/cmu/\n"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation/tf-pose-estimation/models/graph/cmu\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nw7Z0kYi9oxW",
        "colab_type": "code",
        "outputId": "485c55e2-b4f4-45c2-8fe3-ddf36b4f116a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 292
        }
      },
      "source": [
        "!ls\n",
        "!bash download.sh\n"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "download.sh  __init__.py\n",
            "[download] model graph : cmu\n",
            "--2019-11-04 00:03:19--  http://download686.mediafire.com/whw1mc1wc4tg/qlzzr20mpocnpa3/graph_opt.pb\n",
            "Resolving download686.mediafire.com (download686.mediafire.com)... 205.196.120.134\n",
            "Connecting to download686.mediafire.com (download686.mediafire.com)|205.196.120.134|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 209299198 (200M) [application/octet-stream]\n",
            "Saving to: ‘/content/tf-pose-estimation/tf-pose-estimation/models/graph/cmu/graph_opt.pb’\n",
            "\n",
            "/content/tf-pose-es 100%[===================>] 199.60M  1.75MB/s    in 1m 49s  \n",
            "\n",
            "2019-11-04 00:05:08 (1.83 MB/s) - ‘/content/tf-pose-estimation/tf-pose-estimation/models/graph/cmu/graph_opt.pb’ saved [209299198/209299198]\n",
            "\n",
            "[download] end\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O8Nr09KO_BwS",
        "colab_type": "code",
        "outputId": "e6378184-f2e4-4846-daeb-014f92448252",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "%cd /content/tf-pose-estimation/"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N8lMVz26-s2u",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#! python run.py --model=mobilenet_thin --resize=432x368 --image=./images/p1.jpg"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bu0NHmzQB8PW",
        "colab_type": "code",
        "outputId": "882b329d-53da-493e-d4e8-0134ddf3461a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 126
        }
      },
      "source": [
        "!ls"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "CMakeLists.txt\tlaunch\t     requirements.txt\tscripts\n",
            "docker\t\tLICENSE      run_checkpoint.py\tsetup.py\n",
            "Dockerfile\tmodels\t     run_directory.py\ttf_pose\n",
            "etcs\t\tmsg\t     run.py\t\ttf-pose-estimation\n",
            "images\t\tpackage.xml  run_video.py\n",
            "__init__.py\tREADME.md    run_webcam.py\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TwNhOaUaEiT2",
        "colab_type": "code",
        "outputId": "a9e3314d-7a7d-487d-da88-baa5355c7315",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "!cp ../run.py ."
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "cp: cannot stat '../run.py': No such file or directory\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ca_ugF2WEn5e",
        "colab_type": "code",
        "outputId": "11dee450-eb20-4e6c-c19a-c9f4c6b49adc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "! python run.py --model=mobilenet_thin --resize=432x368 --image=./images/p1.jpg"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:\n",
            "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
            "For more information, please see:\n",
            "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
            "  * https://github.com/tensorflow/addons\n",
            "  * https://github.com/tensorflow/io (for I/O related ops)\n",
            "If you depend on functionality not listed there, please file an issue.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/mobilenet/mobilenet.py:369: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.\n",
            "\n",
            "[2019-11-04 00:05:18,273] [TfPoseEstimator] [INFO] loading graph from /content/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)\n",
            "2019-11-04 00:05:18,273 INFO loading graph from /content/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:311: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.\n",
            "\n",
            "2019-11-04 00:05:18,274 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:311: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:312: The name tf.GraphDef is deprecated. Please use tf.compat.v1.GraphDef instead.\n",
            "\n",
            "2019-11-04 00:05:18,274 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:312: The name tf.GraphDef is deprecated. Please use tf.compat.v1.GraphDef instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:330: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
            "\n",
            "2019-11-04 00:05:18,289 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:330: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:332: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.\n",
            "\n",
            "2019-11-04 00:05:18,364 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:332: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.\n",
            "\n",
            "2019-11-04 00:05:18.365912: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1\n",
            "2019-11-04 00:05:18.368738: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.369202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: \n",
            "name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235\n",
            "pciBusID: 0000:00:04.0\n",
            "2019-11-04 00:05:18.369464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0\n",
            "2019-11-04 00:05:18.370702: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0\n",
            "2019-11-04 00:05:18.371926: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0\n",
            "2019-11-04 00:05:18.372291: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0\n",
            "2019-11-04 00:05:18.373789: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0\n",
            "2019-11-04 00:05:18.374979: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0\n",
            "2019-11-04 00:05:18.378359: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7\n",
            "2019-11-04 00:05:18.378504: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.378990: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.379398: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0\n",
            "2019-11-04 00:05:18.384551: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2300000000 Hz\n",
            "2019-11-04 00:05:18.384811: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1e9d2c0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",
            "2019-11-04 00:05:18.384844: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",
            "2019-11-04 00:05:18.431640: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.432200: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x1e9cd80 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:\n",
            "2019-11-04 00:05:18.432231: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Tesla K80, Compute Capability 3.7\n",
            "2019-11-04 00:05:18.432434: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.432836: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1618] Found device 0 with properties: \n",
            "name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235\n",
            "pciBusID: 0000:00:04.0\n",
            "2019-11-04 00:05:18.432932: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0\n",
            "2019-11-04 00:05:18.432974: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0\n",
            "2019-11-04 00:05:18.433029: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10.0\n",
            "2019-11-04 00:05:18.433071: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10.0\n",
            "2019-11-04 00:05:18.433123: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10.0\n",
            "2019-11-04 00:05:18.433164: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10.0\n",
            "2019-11-04 00:05:18.433204: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7\n",
            "2019-11-04 00:05:18.433334: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.433815: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.434225: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1746] Adding visible gpu devices: 0\n",
            "2019-11-04 00:05:18.434296: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0\n",
            "2019-11-04 00:05:18.435683: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1159] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
            "2019-11-04 00:05:18.435717: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1165]      0 \n",
            "2019-11-04 00:05:18.435732: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1178] 0:   N \n",
            "2019-11-04 00:05:18.435891: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.436401: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:983] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero\n",
            "2019-11-04 00:05:18.436805: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
            "2019-11-04 00:05:18.436855: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1304] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3558 MB memory) -> physical GPU (device: 0, name: Tesla K80, pci bus id: 0000:00:04.0, compute capability: 3.7)\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/weights\n",
            "TfPoseEstimator/image\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_2_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_3_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_4_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_5_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_6_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_7_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_8_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_9_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_10_pointwise/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_11_pointwise/Relu\n",
            "TfPoseEstimator/Conv2d_3_pool\n",
            "TfPoseEstimator/feat_concat/axis\n",
            "TfPoseEstimator/feat_concat\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_1_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_2_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_3_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_4_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_5_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_5_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_5_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L1_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_1_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_2_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_3_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage1_L2_4_pointwise/Relu\n",
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            "TfPoseEstimator/Openpose/MConv_Stage5_L1_3_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_3_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_3_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_3_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_4_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_5_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_5_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_5_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L1_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_1_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_2_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_3_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_4_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_5_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_5_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_5_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage5_L2_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_concat/axis\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_concat\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_1_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_2_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_3_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_4_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_5_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_5_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_5_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L1_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_1_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_2_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_3_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_4_pointwise/Relu\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_5_pointwise/weights\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_5_depthwise/depthwise\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_5_pointwise/Conv2D\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/Openpose/MConv_Stage6_L2_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/Openpose/concat_stage7/axis\n",
            "TfPoseEstimator/Openpose/concat_stage7\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:341: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
            "\n",
            "2019-11-04 00:05:18,528 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:341: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:342: The name tf.image.resize_area is deprecated. Please use tf.compat.v1.image.resize_area instead.\n",
            "\n",
            "2019-11-04 00:05:18,529 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:342: The name tf.image.resize_area is deprecated. Please use tf.compat.v1.image.resize_area instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/tensblur/smoother.py:96: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
            "\n",
            "2019-11-04 00:05:18,535 WARNING From /content/tf-pose-estimation/tf_pose/tensblur/smoother.py:96: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:354: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
            "2019-11-04 00:05:18,545 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:354: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:359: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.\n",
            "\n",
            "2019-11-04 00:05:18,545 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:359: The name tf.variables_initializer is deprecated. Please use tf.compat.v1.variables_initializer instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:360: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
            "\n",
            "2019-11-04 00:05:18,546 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:360: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/tf-pose-estimation/tf_pose/estimator.py:362: The name tf.report_uninitialized_variables is deprecated. Please use tf.compat.v1.report_uninitialized_variables instead.\n",
            "\n",
            "2019-11-04 00:05:18,546 WARNING From /content/tf-pose-estimation/tf_pose/estimator.py:362: The name tf.report_uninitialized_variables is deprecated. Please use tf.compat.v1.report_uninitialized_variables instead.\n",
            "\n",
            "2019-11-04 00:05:19.287129: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7\n",
            "2019-11-04 00:05:20.055904: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10.0\n",
            "2019-11-04 00:05:20.486772: W tensorflow/core/common_runtime/bfc_allocator.cc:305] Garbage collection: deallocate free memory regions (i.e., allocations) so that we can re-allocate a larger region to avoid OOM due to memory fragmentation. If you see this message frequently, you are running near the threshold of the available device memory and re-allocation may incur great performance overhead. You may try smaller batch sizes to observe the performance impact. Set TF_ENABLE_GPU_GARBAGE_COLLECTION=false if you'd like to disable this feature.\n",
            "[2019-11-04 00:05:21,327] [TfPoseEstimatorRun] [INFO] inference image: ./images/p1.jpg in 0.0480 seconds.\n",
            "2019-11-04 00:05:21,327 INFO inference image: ./images/p1.jpg in 0.0480 seconds.\n",
            "<Figure size 640x480 with 7 Axes>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OZf1W8ofXIJc",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tuTOCpdBbSKP",
        "colab_type": "code",
        "outputId": "c71bede2-d44e-4d00-a468-b8166fa84acd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "\n",
        "\n",
        "import argparse\n",
        "import logging\n",
        "import sys\n",
        "import time\n",
        "\n",
        "from tf_pose import common\n",
        "import cv2\n",
        "import numpy as np\n",
        "from tf_pose.estimator import TfPoseEstimator\n",
        "from tf_pose.networks import get_graph_path, model_wh\n",
        "\n",
        "logger = logging.getLogger('TfPoseEstimatorRun')\n",
        "logger.handlers.clear()\n",
        "logger.setLevel(logging.DEBUG)\n",
        "ch = logging.StreamHandler()\n",
        "ch.setLevel(logging.DEBUG)\n",
        "formatter = logging.Formatter('[%(asctime)s] [%(name)s] [%(levelname)s] %(message)s')\n",
        "ch.setFormatter(formatter)\n",
        "logger.addHandler(ch)\n",
        "\n",
        "\n",
        "if __name__ == '__main__':\n",
        "\n",
        "    class args:\n",
        "      model = \"\"\n",
        "      resize = \"\"\n",
        "      images = \"\"\n",
        "      resize_out_ratio = 4.0\n",
        "\n",
        "    args.model = \"mobilenet_thin\"\n",
        "    args.resize= \"432x368\"\n",
        "    args.image=\"./images/p1.jpg\"\n",
        "\n",
        "    w, h = model_wh(args.resize)\n",
        "    if w == 0 or h == 0:\n",
        "        e = TfPoseEstimator(get_graph_path(args.model), target_size=(432, 368))\n",
        "    else:\n",
        "        e = TfPoseEstimator(get_graph_path(args.model), target_size=(w, h))\n",
        "\n",
        "    # estimate human poses from a single image !\n",
        "    image = common.read_imgfile(args.image, None, None)\n",
        "    if image is None:\n",
        "        logger.error('Image can not be read, path=%s' % args.image)\n",
        "        sys.exit(-1)\n",
        "\n",
        "    t = time.time()\n",
        "    humans = e.inference(image, resize_to_default=(w > 0 and h > 0), upsample_size=args.resize_out_ratio)\n",
        "    elapsed = time.time() - t\n",
        "\n",
        "    logger.info('inference image: %s in %.4f seconds.' % (args.image, elapsed))\n",
        "\n",
        "    image = TfPoseEstimator.draw_humans(image, humans, imgcopy=False)\n",
        "\n",
        "    try:\n",
        "        import matplotlib.pyplot as plt\n",
        "\n",
        "        fig = plt.figure()\n",
        "        a = fig.add_subplot(2, 2, 1)\n",
        "        a.set_title('Result')\n",
        "        plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n",
        "\n",
        "        bgimg = cv2.cvtColor(image.astype(np.uint8), cv2.COLOR_BGR2RGB)\n",
        "        bgimg = cv2.resize(bgimg, (e.heatMat.shape[1], e.heatMat.shape[0]), interpolation=cv2.INTER_AREA)\n",
        "\n",
        "        # show network output\n",
        "        a = fig.add_subplot(2, 2, 2)\n",
        "        plt.imshow(bgimg, alpha=0.5)\n",
        "        tmp = np.amax(e.heatMat[:, :, :-1], axis=2)\n",
        "        plt.imshow(tmp, cmap=plt.cm.gray, alpha=0.5)\n",
        "        plt.colorbar()\n",
        "\n",
        "        tmp2 = e.pafMat.transpose((2, 0, 1))\n",
        "        tmp2_odd = np.amax(np.absolute(tmp2[::2, :, :]), axis=0)\n",
        "        tmp2_even = np.amax(np.absolute(tmp2[1::2, :, :]), axis=0)\n",
        "\n",
        "        a = fig.add_subplot(2, 2, 3)\n",
        "        a.set_title('Vectormap-x')\n",
        "        # plt.imshow(CocoPose.get_bgimg(inp, target_size=(vectmap.shape[1], vectmap.shape[0])), alpha=0.5)\n",
        "        plt.imshow(tmp2_odd, cmap=plt.cm.gray, alpha=0.5)\n",
        "        plt.colorbar()\n",
        "\n",
        "        a = fig.add_subplot(2, 2, 4)\n",
        "        a.set_title('Vectormap-y')\n",
        "        # plt.imshow(CocoPose.get_bgimg(inp, target_size=(vectmap.shape[1], vectmap.shape[0])), alpha=0.5)\n",
        "        plt.imshow(tmp2_even, cmap=plt.cm.gray, alpha=0.5)\n",
        "        plt.colorbar()\n",
        "        plt.show()\n",
        "    except Exception as e:\n",
        "        logger.warning('matplitlib error, %s' % e)\n",
        "        cv2.imshow('result', image)\n",
        "        cv2.waitKey()\n",
        "\n"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[2019-11-04 00:05:22,898] [TfPoseEstimator] [INFO] loading graph from /content/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)\n",
            "2019-11-04 00:05:22,898 INFO loading graph from /content/tf-pose-estimation/models/graph/mobilenet_thin/graph_opt.pb(default size=432x368)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "TfPoseEstimator/MobilenetV1/Conv2d_0/weights\n",
            "TfPoseEstimator/image\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_0/Relu\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/weights\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_depthwise/depthwise\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/Conv2D\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator/MobilenetV1/Conv2d_1_pointwise/BatchNorm/FusedBatchNorm\n",
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            "init\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_1_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_1_depthwise/depthwise\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_2_pointwise/weights\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_3_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_3_depthwise/depthwise\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_3_pointwise/Conv2D_bn_offset\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_3_pointwise/Relu\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_depthwise/depthwise\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_pointwise/Conv2D\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_4_pointwise/Relu\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_depthwise/depthwise\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_pointwise/Conv2D\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_5_pointwise/Relu\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_depthwise/depthwise\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_pointwise/Conv2D\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_6_pointwise/Relu\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_depthwise/depthwise\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_pointwise/Conv2D\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_7_pointwise/Relu\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_8_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_8_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_8_depthwise/depthwise\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_8_pointwise/Conv2D\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_8_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_8_pointwise/BatchNorm/FusedBatchNorm\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_9_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_9_depthwise/depthwise\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_9_pointwise/Conv2D\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_9_pointwise/Relu\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_10_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_10_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_10_depthwise/depthwise\n",
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            "TfPoseEstimator_1/MobilenetV1/Conv2d_11_depthwise/depthwise_weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_11_pointwise/weights\n",
            "TfPoseEstimator_1/MobilenetV1/Conv2d_11_depthwise/depthwise\n",
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            "TfPoseEstimator_1/Openpose/MConv_Stage1_L1_1_depthwise/depthwise\n",
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            "TfPoseEstimator_1/Openpose/MConv_Stage1_L1_4_depthwise/depthwise\n",
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            "TfPoseEstimator_1/Openpose/MConv_Stage1_L1_5_depthwise/depthwise\n",
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            "TfPoseEstimator_1/Openpose/MConv_Stage1_L2_5_depthwise/depthwise\n",
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            "TfPoseEstimator_1/Openpose/MConv_Stage2_L1_3_depthwise/depthwise\n",
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            "init_2\n",
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            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_3_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_4_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_5_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_5_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_5_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage5_L2_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_concat/axis\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_concat\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_1_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_2_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_3_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_4_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_5_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_5_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_5_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L1_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_1_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_2_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_3_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_4_pointwise/Relu\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_5_depthwise/depthwise_weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_5_pointwise/weights\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_5_depthwise/depthwise\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_5_pointwise/Conv2D\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_5_pointwise/Conv2D_bn_offset\n",
            "TfPoseEstimator_4/Openpose/MConv_Stage6_L2_5_pointwise/BatchNorm/FusedBatchNorm\n",
            "TfPoseEstimator_4/Openpose/concat_stage7/axis\n",
            "TfPoseEstimator_4/Openpose/concat_stage7\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "[2019-11-04 00:05:24,931] [TfPoseEstimatorRun] [INFO] inference image: ./images/p1.jpg in 0.0467 seconds.\n",
            "2019-11-04 00:05:24,931 INFO inference image: ./images/p1.jpg in 0.0467 seconds.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
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eS96PHWwrTYyp4no5GjUQzNCeVebDKQs0VkjiYKvyLlBCWZEpNveKdx3yQRuX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zPpGJOY+Zd6aJ35I1lABHH8PvEtncvk0magZc0V6sAlsfvr9YMgIDKRzaI1tja9xwADfX3s3CN4\nuTJDIyM8+dg0xniIJ0TabMdEjIyOMDY6RhREhLNzFPorUMpZf6vnMV+tIrWQfbv3gHjMTE25ebj2\nkKk5AoiL/AHrlPVzJmntKLpouRM8+14oVBA8Kv1FV4bCPefGfmtN2PJSvX47IbPhnyNEJI9l9v9g\njPlnt/mkmmpEZA+gdaBX7TzzPIklfG2/p9J6OlRLy/22O1TB2tjT0n9aws+nxkgz/3a0hIUBi4uL\nMVOPTN1GBIQRA4P9vPCFL+TMmTMcO3aMSu7pXP6CgD/+/bfy26+v8bxnvYj+kRyL4RC+LJIrFagG\nDeqPR5we3cG9xx/k1fuez1S1wWc/dyfXXr2fr/3v7/DM5z+L2fl5RisV5hfriDSc/bhBPp+nUCgw\nf2qCoaEhPPHBCM2Gh+fl8MQgAfQXC8xPL7A4WydoNHnicB/GCF65iufl6O8bpL9/YKWfY1tBcGYF\nlaGjmEPHgX6tAoZxkSg6QGcO075wqESrFpvOWaNtC4t7j8dMhenYNcrG34vYYnrqwNXnw/OEgcFB\nW7+pWiOMIoJmiDFw5swp7r07QMQnjAKGB0YwJqTRMOQ8ITQhY+Pj9A0MYJrChGngn5xiqFK0UWjG\nUKs3aYSGsLpAX6XI8PAwZ05P2AVIolg1kZQWgpsXWGeslgqP/SQQRyPlxWX4RlqD34Yba7csQfBy\ndgG22cb+WRfSlWz83YAtZ/gu6ubDwEPGmPendt0GvAG42b1/NrX9JrHNfl8IzKxkvwcbAXP86BFE\nhOHREcfM7SsIkprg+Xw68crGJ6sGYE01BiWstNli0S0ixhhybb93JLayJZKEXOp7oWAJLooCfKy/\nQPBoVgMKnrB7fIxdY6Pcde993P9glWuveQ6F0lGiQo2Bof2UmhHzjQhp1BjJhZzZU+NFw7vIX7aL\nBc9w5vQpZpohpXw/O178AuamZ9i1fz9Bo8FAOVl8xC87X4Qhny9SrzddmYYo9ntgvwWCh5cfRETI\n+QajZq5GSATM1uaZPTO/0s+xraAJPxriqMk+iXQteF4r0bTyeBMnBaXNCUuYdxsjitpF3w58KokW\nMs70nwo2cPDSsZwpbQJwSViGnO9RyJeshB+FNIMmnudTrvQRhSHNABqhrVlfyHlEJsIToZj3yYkh\n8gPGc0W8p11MJNAIIyIDtWaToBkwunMHTVdMrVAs0mw0rXCeXvTE62T5shqQPu/GtOxMbpEgnoZf\nuzvuho5C97xHIUEQtlYZbUMQBEw5DaRbseUMH9ul5VeA74vIvW7bf8My+k+JyJuBJ4BfcPtux4Zk\nHsKGZb7pbBco5Avs2XuxXb07xOIr2ptvh2Ez9XerXTp9nkruxhjaDU+xxC9QKva1MPwgTEw8Jgzi\nfQC1Wj02BV133XU0GgE5v4BXvJShwWEaEVTrIYVigTCoMzU1RXPqJM1dFzHj9bEQGZ61bxeveekP\n4RMQBBFzc3OUSiUWXUmEGJK0iMsXh11phZCF+Qa5lHUmLb2kQ1tFBC+flFvOkEDEleJwphpR23yL\njbwV7czbdCgBsETQXJInkrbrd7iMMe2uXxulY8AoEXc4Ri+cDmNOv4sIuVzeOnVDW/Ygl8u7CB5b\n5lmck1UrvPpRaGv9i0/TGAq+T873GazYwn1Gma3Liwl9zfhdeu+03o1K5RrqaZ257fdVb53BOIf0\nkhElCd/u6IBJQWtOdTO2nOEbY/43y3tCXtrheAO8bVXXQBA/h+95hM3APXj2lWZ8pVLr7QijhCG3\nO2PTDF8Xg7Q0rMh7BVTCD2qtEn46CzAdu6+OW90WRRGVSoXqYp1cvkAjCKlVq4yP7yIydQLP8MAD\nD3DxJQc4k5+FcsRAqcLEZJVSERbqNeZnZjlz5gxhGNrSCCn1PRY6jSGMrFlLPIMviTsPEh+Hvqdr\nAa1kytr2UOefl3RaQk30kkjM8eFe++Nw9kWhw0X1yI7nGASJP7v3eF1Z5nHseM3W60RR4nswcVE3\nCALbVjDtbNZeELaIIYgfIZ5PEEfT2dIOgTGYyC4QGrbcKRGyJdZTbHy/XmuZL+S+VuLAtvb6RMJX\nXqF/r9TzKgiCzGnbDRCwWXKROSeHojKxcnk4/rvqqlYqarXFmHnm8wnzbI/Dz+VycZGx2fqsGnUB\n8LykpLA0AMK4eFm9Ube1+j2ParOKMXMYY6j0DQJ1Kv0FQjNHHo8oavKDBx9mZKCfqakZpr1+dl10\nKeHiafoHDeI3MJPz3PnN7zBQKjA/33BSlZXkc6kcADVhaSZxoVxOnNNtxcLLhTyhEOfntOQfZIgR\n85sOjOpcztbaLjEMREsSskzSBERSWbVqfjG6eJtkq9ald0uOjhn/ep3mmjaXOPanIcgaFqkhkTa7\n1bMmEyGWsD0RImc3bzYaBC4XRkyByIS2KBrge4LBxcM3Q+rVauwTSX99Y5LmJ+rwbqFASX/f9i+T\nWiFImbBiNczEdy0Oe10GmYTfJdCHTKs/ppFmTu0P48LCQszw2wuraWllESGMWuvC67jtYaBjY2Mt\nY9Rqtfi4Yl+5hWFqxq/nebYvqNseGjAmJIwCwrBJvdkEYzh8+DCHH3+cpz/jmZR27OPxxx7l0FOn\neOWP/TDB3BSnnjrCgw8eZHBgCN8rUEzZatLNTdKRSCLCYiMxLbU7pILIxAw/63i1EhK66sjvz3LL\n4vvecq60/iUCni2DbC/SOmiyCGgZB61Fn0zMz7XSeCzRpg3jbYt6ulViOzM0qXE0QkbPFWw2az2M\nCIOQfLGAXyiC+CzUrAO4v1KmXCxgwpBadZHFhSqe7+rvpCV6/dvNwIjNSWjRnMRJ7ybF4tv8IvZT\nqwlMHb5q3lppuc5s+N0CSZpyr1ggbYXY+3ZTjZqD0lJxJ5TLZfL5fEsSl2JoaChmknPz03EfUt/z\nCGoNIs8Dz4tr0xgDfs536eEeUWTtUlFkbJGpQonPfOYz3PAzP0e12WRXJc993/oPJk+cYHZhnvGx\nXTSboW1P16jHfWvVt6F/670QEfr7++M5tt+DHBIz/CBVAjdj+u1I7kenII6lWbFt+88aykmiPYi0\nLNxLZmKspC1O2k3/3meDcU1JYkYZ+3ujtuN0pnYR8DzVApTpu//VlxUEzC8uUO7rtzktUUBOhLDZ\nYHZxkSgMaAahi5JJ3QOz1KFtb0H6Hkl819Jfsb1OkCJeKtvN9nEc/sro9hyUbcHwTWTDMW1kTGto\n5ErMaSUThUr3QRBQLLW2+tNz9MHT7N52P0BawtfG1trBKGhaR5Lv++SLhfi42fkZjAlB7DlGoti0\n9NiTTzI9Pc3H/v5WBoeHGRD7vQcH+xnasZ/JyWn6+wdpNkIqxWIcEjo3NwcQ2+f1bxHBz7f6Elpv\nUPJnpVLJmP0ySMwprV2nVNJu5SRnZ7ythoY0g20dzsT/a+Biqz0/iVZLzzM972SU+NoalZWajBUU\nUgw1dYpNxlKasjPRYQ0qsFin7PTkpK0sqpK0c3D7vk8uX8REka2w6SpqWrOjl6LbdF3Ltu9Gm3bl\n7JDt1Nou4Xvpk7ylCZlpeJ7HwEB3hyRvC4YvIlQqFer1OtVqlUKhQD6fb2FuynDTBN1sNuNIFHXu\nakKSrWMfEEVQqybt/5bU1A8h5xcQhGKxtZZOWrswkcRzajc9FYvFOBN2fHy8Zfx0TZ89l17Rsi9n\nkkqfnpe3cdKSMO8GERIZ8mUbYWMA8VtjscN6Ix4/n2sl9sVqPV6gPM9kDH8Z+J4fx7OHYYTnpUsO\nJxbixHzcynR0wRDH0Q02Zj5KCQsmSkvRpLyNzhxIqxSfNufoQrFE02gzeRj1x0piYmyVqInnqbTg\nOw9aGnpdpZWiJ1T6UrRj0lfVYb34e5D6S/9vX7w6Qe37qanSbtWPosguJqoZpCpung1hGDI5OXlu\nB28RtgXDj0zE/Pw8hULB1tQ2VvJV27yaM9JhhgB9fX3xtiAIbDXJSiUOJ9OsXd8XZmZmbAvENuuO\nSdfWdnU92psrA4hbKPL5PKVSiWbQGiHkeR6lUmmJlK31eABymnCiJRq8xK4eRa0lJbRXrS2nLC3X\nSiNt34+iVnXVZuI245aLQMb0O6AZBPie50ruJowZxyyNaWP28c+RmCnSCwIQV3VU6Vojgew/mzwU\ntgg0svR3aRHLndUiPqR1EUrPQ89Lati0D6umnMRfkIaOqWGTKvLbtc+O3SljPX1uu0kqdbuWnBPv\nTon5ulC0U6o2T0krX3YcA9HSMVvO7SDhnz59epmjtwbbguFDYq5QhlYoFBgeHmZubi6W8Nvr7DQa\njVjqT8cdawN0NYnUanVGRkYso6WVKfqxNGedu2k7d0ssvPHivrTFYhFTTcZpNBpxKGd72QddsGq1\nGpXBISd1Wam/Vl+kUCjYTN6GVYPFTxaFWLNJRS+0j58jmW+7q8LzXJawu69ZlE5n+H6qSitJkw5b\njEvNEYmL0cShjSnbjIsVb7Wa2Lh2y6TSjHepL8Vohyw9Ii2ZxxJ7lGLw0vaeHj7JYWlPRJJ4LDVp\nLjNGPE/batETzU9wi0z8nDi6F985Tpc3NS2dZieNxcJqSUtnFLn4fnF1fcIobNUKVkAYhl3vtJXt\n8HCKyGlgAZjY6rmcA8bpjXnCynO9xBiz43xOphshInPAI1s9j01AL9HpanC277UsXYvIF935aUwY\nY27YqMmtF9uC4QOIyF3GmOu3eh5nQ6/ME3prrluFC/UeZd+rN7F8cecMGTJkyHBBIWP4GTJkyLBN\nsJ0Y/i1bPYFzRK/ME3prrluFC/UeZd+rB7FtbPgZMmTIsN1xQUr4IvJFEXlPh+03isgJEVlTOKqI\nfE1Efm39M8yQYfXI6DrDenFBMnxs0/PXydLg3F/BdtUKOpyzqRCLC/V+Zzg/yOg6w/qgCRIX0gso\nAzPAjwM3YOOgDwNN4NlAEXgf8CRwEvifQDl1/o3AvcAs8Kgb471ACNSAeeAv3LE/Atzprncn8COp\ncb7mzvs6UAWuwDZbX8A2b5kHPgdc7raHbpxnufPFzaPp9j0IvCg1/ruBfwQ+CcwB3wWevcJ9uR34\ns9TnTwAfWebY/cC/ums+APy22z4KfAn4gXsfSc31z7GNab4HPHer6WCrXynaOwS8fSPpOrVtxNHk\nhtE18BFg0tGo0vUrUr/7JPBnKbr+qHs/CdyXousx4B/c9e4EDqTm8kHgiNt391rpGtjt5jmW2vZc\n4DSQz2i67X5t9QQ27YvBX2NbJz4KXAb8n44orwE+gG2VOAoMOOL8v915L3BE/pNYDWgf8HS372vA\nr6WuMQpMYSWsHPBa93ksdfyTwLVufx64xxH6QWDIEd8k8DfumO8C33Pnv9I9QGPYzmBPACeAUurB\naAL/xY39+8Bj7YTe9nCcAv4T8MvYRXBgmWP3KIG7e3TQ3bs/wTEv4O3A/5Oa6xfcQ/JDwLe3mga2\nmP78FO0V3O94zQbR9d+kPr8VuNf9vVF0/X9gGfGRFF3XgPe4/Yfd/muBVwFfdGMcwS4oStcHgZe5\nMW4F/jZ1jdc5us4Bv7dOur4d+I3U5w8A/yOj6Q73aqsnsGlfDH4MKx18yX3+OvB54B1YCfvy1LE/\nDDzm/v4r4APLjNn+YPwK8J22Y74JvDF1/Hs6jPGnwP3u859hJaI97vPrgVpqLq9NnfsIMI2TdtyD\n8a3Ufg+rKbyo0/zdMa92D+YE8GOruJ+fxTKLR1Jz3QM8ssJc92w1HWwh/f0wcEfq8zuAd2wQXU+n\nmOPXgd91TGkj6fpepVG3rUoiEX8Dm0Ea/+5ujHfq7+7o+gup8/8zbmFaZg5Ta6Vr4BeBr7u/fezi\n8YKMppe+Lljbm7GtE+cBX0Qux0o4X8CaVSrA3SIyLSLTWAlF06X3YyWzc8FerNSdxhNY6UlxpMN5\n6dTtKlAwSSP241ipBjfOj4rIQyIyg5UWB2lN347HN7agylFgr4j8sojMu9cXUsd/DvtQPOLu0Vkh\nIgeA5wDfBnal5noC2JWaa/q7HqX1Pmw3bMr9cL/ZBPAzKbr+GJZ+N5Kuj7Vt8wFt59Rw14LW73mS\n5HuqiUdRTZ2PiPy+0rWb6xBrp+vPAteIyKVYBj5jjPnOSl9wu9L0hV487d+wppDXAXdg1dCqe11r\ndpaZ7AAAH01JREFUjGknarA/8OXLjNcew3ocuKRt28XYB225c1aDUez8fxxrc/wS8Hxaq1Ht1z+c\n8+wi4Lgx5j+w9tN2vBd4CLhURF5rjPn4ShMQkX7gn4DfMcbMtpbYNUbaO0NnOB+4FasJPg2rRZx0\nv/1G0nU7Y/NoXQTW/LuLyIuA/4rtWf2AMSYSkSnWSNfGmJqIfAr7nD8d+F9nuf62pekLVsJ3+CSW\ncH8d61i6CEu0fw18QER2AojIPhF5hTvnw8CbROSlIuK5fU93+05ipWzF7cBVIvJLIpITkV/E2gQ/\nv8p5VkVkj/t7FOKSm9oR+TR2cX420Nd27vNE5OdcSN7vAHXgW50uIiI/DrwJyyzeAPwPEVlWYhGR\nPPbB+AdjzD+7zSd1ru79lNt+jNRDSnKvtys2837cirWNK12rFLyRdH0ZMJSia8E6XsH6JObW8T0H\ngABH1yLyLqzmmsY507XDrcAbgZ9mBYa/3Wn6Qmf4n8MSygDWnPMarFPrD7Ce92+JyCzwZay0hFMF\n34R1/MxgtQSV4j8I/BcRmRKRPzfGnME6rX4POIOVWl5ljFltFcEjWAYM8HKsLRbgQ+7vg1ipa5Gl\nJqLPYm2Y6jz+OWNMs+0YRGQQ+1DcZIw55iSlDwN/2yHMD7ftw8BDxpj3p3bdlprrG9z1dfvrXZje\nD2HV6qfYvrgTuFJELhWRAgntrRvGmMexdvS+tjE3kq5/FWtiUbr+JNYOD9b5f6/7+zasAAF2kTiX\n3/0OrBZ8EGsCrbFGuk7dk69jW5t/1xjTbmYFMpoGLlynrb6wnvaDWPvlO7tgPh/HOqCaWJvgm7HR\nCl/BhoV9GRh1xwrwl27u3weubxvr3cDfb9I8fwyrtn8P+3Df6+7lmua6HV/dRnurmPeG0egar78m\nuga+Ssr53GH/tqfprLRCD0NE3g1cYYx53VbPJUOGjcJa6FpEno/1ce03xsyd7fjtik0z6YjIDSLy\niIgcEpG3b9Z1MmQ4n8jouvsgIh/FSua/kzH7lbEpEr6I+FhV9iexKuGd2HjWBzf8YhkynCdkdJ2h\n17FZEv4LgEPGmMPGmAY2hf/GTbpWhgznCxldZ9hwiMhHROSUiNy/zH4RkT93WuX3ROS5a73WZsXh\nd0pYeGH6ABF5C/AWgHw+/7zx8fZWkBl6FU899dSiMaY9fDTGDTfcYCYmWgOZ7r777jtMF/X+XAZn\npWvoTNuSau6doXexEm2vg67/DlvD6NZl9v8UcKV7vRAbvbeE7s4FW5Z4ZYy5BddsYO/eveatb33r\nVk0lwwbj3e9+9/RK+ycmJvj2t7/dsi2Xy10wK34n2vY8q0xHUbSVU8uwTqxE22ula2PMv7vM3+Vw\nI3CrsdLCt0RkWET2mDWEiG4Ww7/gEhYybByMMYRhePYDuw9rputMsu8tdEhNOetvuIl0vVyJh1Uz\n/M2y4W9a0kmGCwNRFLW8egQZXWdYER3oelxE7kq93rKV89sUCd8YE4jITdiMOh9bc/2BzbhWht5D\nr0r466HrTMLvLazl91qGrieMMdevczobZjHZNBu+MeZ2bE2ODBmWoIek+hZkdJ1hJWwSXd8G3CQi\nn8A6a9dc4qGrq2W2VbHbwplkSGO9ESe9KuFvJDLa7k6sh7bXStci8nHgJVjzz1HgD3El0o0x/xMr\nYLwSWydpEVsTaU3oaoaf4cKEMaZnJfwMGZbDWunaGPPas+w3wNvWOq80MoafYUuQMfwMFyK6na67\nmuH3mqqrsdbLIf199Fh9V1Ww2wkGNuZ36YXvuZnoNdpuR6ewxfZ97bTdC995vXPsdrruaoaf4cJE\nZsPPcCGiF+g6Y/gbgHZpfdcu2xKzVCoB0Gg0AJieTpL09Jj+ftvm89Qp22Tn5EnbBrTbCWc96IUH\nI4OFSuu5nGUVl156KQDNpu1FMjU1BUC9Xo/PUdoeGhoCEpo+ceLEeZjx1qEX6Dpj+Bm2BL2g3mfI\nsFp0O11nDH8DcdFFFwHw0pe+FICdO3cCMDk5CcDhw4fjY8fGxgAoFosAfPe73wVgbm6u5f1ChDGG\nIAi2ehoZVoFLLrHdEF/ykpcAcOyYzfuZn58HWm36+hzUajUABgYGAJidnQWgWq0C3c8cV4teoOsL\nvadthgwZMmRwyCT8NSIt0eTzeSCx2R85Yuscqe1e7ZtXXHFFfM6hQ4cAeOopmzCnkv7o6CiQSEFp\nm+CFIhEZY2IbcIbuQyfaPnDgAJBI6yrZ6+/4tKc9LT5Ht50+fRpIbPl79uwB4Mknn2w5Ln3NXqbx\nXqDrjOFn2BJ0u3MrQ4a1oNvpOmP4q0Sn+GNt3rJjxw4Azpw5AxDXxq5UKgDs3bs3PkejGzSCYf9+\nWxtpZGQESLSDdEOF9njmXpaGVorjztA9UNv9vn37ADh+/DgAjzzyCJDQtPqrAO66666WY6688sqW\nMZSOVdKHJH691yX9bqfrjOFnOO/oBdU3Q4bVohfoOmP4q4Tv+0Bi0wS4+uqrgcQOv7CwACS2y0Kh\nALRm4qo987rrrgOSeHyNd1bJ/nvf+158TloiypBho6HSabrd6LXXXgsk/qmHHnoISDRUpV+lW0js\n+2rD13P1mVGJPy3FP/HEE0u2Zdh4ZAw/w3lHL0hCGTKsFr1A11lYZobzDs1ITL/OBhG5QUQeEZFD\nIvL2Dvs/ICL3utdBEZlO7QtT+7IOVRk2BWuh6/ONTMI/C9qdMOVyGUgctACXXXYZkJh0NOFEQ9rU\nXJMmAE3Q0JBNdVqpOUg/q8O30/i9ChFZlXNLRHzgL4GfxPbzvFNEbjPGPKjHGGN+N3X8bwLPSQ1R\nNcZct+6JX6BQU6PS2lVXXbVknyYN6nt7yYW0KUbpVI/RwAQ1caoZKF1oTE2YSv+96LxdLV1vBTKG\nn+G8Yw2q7wuAQ8aYwwCu88+NwIPLHP9abBOJDBnOG3rBpLMuhi8ijwNzQAgExpjrRWQU+CRwAHgc\n+AVjzNT6prm5WGlVVietSvYaPjk8PBwfc+eddwKJNKKSvf74KsloqCUk0r5uU4lfSyrs3r0bSKQi\nSJKyNDSul9Hhno+LyF2pz7cYY25xf+8DjqT2HcW2eus07iXApcBXU5tLbuwAuNkY8y/nML/HuQBo\neyWo9K5O1csvvxxoDbFUyfv+++8HYGZmpmUM1QrSAQnqnH3gAdvuVx28Wo5Bi6ultWR9rg4ePAh0\nZ5nhc5Het4OE/xPGmInU57cDXzHG3OxsrW8H/mADrpPhAoExpmXxc9iIZs8ArwH+0RiTNqBeYow5\nJiKXAV8Vke8bYx49h7Ey2s5wzliGrrsKm2HSuRHbnxHgo8DX6NKHotNqrBKLSh9aCEqLnakkrqUP\nIAkp0/KvKu20N4LQxBNYWjpWk7XaJRtNfEnPqb3AWi/ZOWFNZWSPAftTny9y2zrhNbS1gzPGHHPv\nh0Xka1j7/rkw/HZ0PW2vJGGqvV01UP2sNK60pmGVkCRPqZSuUM1Xtdj086BhnSq1a1lwHePRR+2t\nHxwcjM9R7UILDWq58F5CL5RHXm+UjgH+PxG5W0Te4rbtSnVUPwHs6nSiiLxFRO4SkbsWFxfXOY0M\nvQbP81peZ8GdwJUicqmIFLBMfUm0jYg8HRgBvpnaNiIiRff3OPCjLG/7TyOj7Qyrxirp+rxjvRL+\njzlVeSfwJRF5OL3TGGNEpKP46eyztwDs3bv3vIqo+kNoGYOLL7443qdSiUopKtmrJPPww/YravEz\nSAqgqaStq3x7JEPa/qnSjUr6WjpWI3BUGurr64vPUdunvqtUpVpHr0j6xpiWhhnncHwgIjcBdwA+\n8BFjzAMi8h7gLmOMMv/XAJ8wrTfiauCvRCTCCjg3p6N7VkBP0Xa7ZK80p8XOIPFDqXSuz4FuV+k6\nneCnknY7ben1OtGe7tPotcceewxI6F+fF322ICksqBFC+jwonfQCba+WrrcC62L4KVX5lIh8BhtN\ncVJE9hhjnhKRPUDv6WYZNhUiEjOdc4Ux5nbg9rZt72r7/O4O530DeOZq55jRdobVYi10fb6xZoYv\nIn2AZ4yZc3+/HHgPVtV+A3Cze//sRkx0I6BSj0rv11xzDdBaJkGlE7VjakSM2uePHj0KtNo0l5M+\ndLva5VVqgcT+rj4DleRVQlCNIl08TbUClYzUNqr2/16QgsDej26WhHqRtvW31zIeSiNpDVHpULVI\n1URVAlea01j49LjtUO2gUzSN+qXaNVKledVM1ZYPyTOpkr5qFhr33w2N0M927W6na1ifhL8L+Ixj\nkDngY8aYL4rIncCnROTNwBPAL6x/mhkuJIhIV9o3U8hoO8Oq0QN0vXaG75Jgnt1h+xngpeuZ1Gah\nPXtPbZbpdoK6TaVnlYZU+ukkaZxt5dfrpj34Ku1rFq7a8lWzUEkhHTGhxag0qkKlIp1/r9g7u10S\n6mXaVglftdl09IzSidK0SuftkSXnQj/tkWjpc1Qqf85zbLKz+sjUdq/zSGvJjz/+eMux2ixdtYVe\niEjrdrqGLNM2wxah28PXMmRYC7qdrrcVw9eIApXiVcpO2yH1mHbb5EZIFukxVHJvb/SsGbxql083\nRVYJX+OoVZrT916qsdPtzq1eg9KWSpjq+0mn+m9kg239/ZT20s+LPl9Kr1oKXN87te/UyCDNxtWc\nFX0u0lp4N6Pb6XpbMfwM3YFeCF/LkGG16AW6zhh+hi1Bt0tCGTKsBd1O19uK4avaq2ru+apsp9dN\nJ8eo+UWdw9obVB2xKimkQzlVJVfnlybM6PfolZKyxpieMj/1Es4Xba9k0tFra3Kihj+rQ7Y9nBgS\n846aKzWcVJ3P3VhMrR29QNfbiuFn6A70Qs2RDBlWi16g64zhbyJWkrh1m0rw6qzVd01WSTva1NGr\nUpASV6+EYypEpKUHaobeg/5+2uwkzei0YqQ6YrWEiSaDachlJ4eyag5ag6jbq0+m0Qt03d2zy3BB\nIoqilvjwDBkuBPQCXWcMfxPRLuF3ysJT6VztmVpqQcsopKst6rHt9k6VKnpFGuoFSSjDytDfT5un\ndLLhq61ek6qUtjXkslNSodrule67nYGm0Qt03d2zy3BBIoqirnduZciwWvQCXWcMfxPRHp2TXv1V\nStd3teVrwoxG62jpBUiicjQJpVck+k7odudWhpWhtnal6XT8uUr7apfX8giaRKXNTjQyDRKaVglf\nC7i1lxrvdj9Vt9N1xvAzbAm6XfXNkGEt6Ha67u7Z9Tjam0SnkzLa7fEqrauEr5JMuoGFFljTY1WS\nOl/5BBsFY0xP2WYzLIVK7yqJp31N7fSo+44csX3oNbJHtVhI2iu2t/zsdok5jV6g6+6u5ZnhgoSI\nkM/nW17ncM4NIvKIiBxyDcTb979RRE6LyL3u9WupfW8QkR+41xs2+OtkyACsja7PNzIJfxOhEr1K\nNGksFzuvEoI6f1Sqh0Ta12PSLRN7CVEUsZperyLiA38J/CRwFLhTRG7r0Krwk8aYm9rOHQX+ELge\n26f2bnfuFOcBIoKIdL3tebXQKLL2qBpYKuGrJqpRO9r4ZOfOnfExGrnzzW/adsRK4/reDfdvpQbx\nsHq63gpkEn6G8w5jDFEUtbzOghcAh4wxh40xDeATwI3neLlXAF8yxkw6Jv8l4IY1Tz5DhmWwBroG\n1qe9rhaZhL+JUBu+vqezZpcrVauSTHvUAiQSvtYvUYljPXVGtiL6QVXfNoyLyF2pz7e4ZuAA+4Aj\nqX1HgRd2GPrVIvLjwEHgd40xR5Y5d9965p8hkfA1ciwdMbYcbbdHpKVr6ezevRtISijfd999QG/U\n0FEsQ9dnO2fN2utakDH8DOcdy6i+E8aY69cx7OeAjxtj6iLyVuCjwH9ax3gZMqwKazTpxNorgIio\n9trO8DcEZzXpiMhHROSUiNyf2jYqIl9yTrAviciI2y4i8udONfmeiDx3MyadobchIhQKhZbXWXAM\n2J/6fJHbFsMYc8YYo8HgfwM872znZrSdYSOxDF2Pi8hdqddb2k47Vw301Y7u/lFE9nfYf044Fxv+\n37HU5vl24CvGmCuBr7jPAD8FXOlebwE+tNaJbRXUybYZY4ZhGL/OZuOr1+vU63VmZ2fjV7PZpNls\nxhEAvu+vu/62MWbV5pz13qMoilhYWGh5nQV3AleKyKUiUgBeA9zWNqc9qY8/DTzk/r4DeLmIjDjm\n/XK3Dc4Dba/l/nYz9LcfGhpiaGgopsGZmZn4pXS6HHT/8ePH45c+F/v372f//v309fW1mDPXMseN\nPvdsv+MydD1hjLk+9bplxUE643PAAWPMs7A+qI+uYQzgHBi+Mebfgcm2zTemLvpR4GdS2281Ft8C\nhtsexAwZVi3hG2MC4CYso34I+JQx5gEReY+I/LQ77LdE5AERuQ/4LeCN7txJ4I+wi8adwHvctoy2\nM2wo1qC5wvq011VjrTb8XcaYp9zfJ4Bd7u/l1JOnaINTbd4CraGHW431SGPtkoFK3+q0XU0Sic4j\nncihoZrtvWzPdyjYeiXWtdg6jTG3A7e3bXtX6u93AO9Y5tyPAB85x0tdULSdpsmN0DSUprWMt35O\nN+o5G53rPNJO26kpGyWrTltNytJjekFLWqMNP9ZesYz+NcAvpQ8QkT0pmkxrr6vGup22xhgjIqv+\nNZxqcwvA3r17u//XzLCh6IUMyoy2M6wWq6VrY0wgIqq9+sBHVHsF7jLG3IbVXn8aCLAa6RvXOr+1\nMvyTuuo4tfaU235W9WQ7oL05RKeyyOcqsaTD3TRZS8vM6ruWmV0uHK7boKpvlyKj7Q5QTUHDDjVE\nWP1QGka8GqR9N9q288CBA0CSiPWDH/yg5Trn8tysRxtYr4a/Frpej/a6Wqw18eo2QFPU3wB8NrX9\n9S6i4YeAmZQqkiEDsCan7flERtsZ1oQup2vgHCR8Efk48BJseNFRbJr6zcCnROTNwBPAL7jDbwde\nCRwCFoE3bcKcuxYqHaiEr+8qHa0lciCtIqp9UJNeVMJXqUKP7XZ7p4h0LDexBfO44Gl7o2mhvam4\n2ti1bAKcezJfOkrt+PHjQOKn2r/fKlNK62rj72Z0C12vhLMyfGPMa5fZ9dIOxxrgbeudVIYLG1EU\ntXQ72ipktJ1hI9EtdL0SskzbTUC7vbE9Wmet0IgdVRW17LK+6/6NjszYaGjNkQy9A6WjdtpW7TJd\nUmAtNKeawrFj1i2ipRZU0lcNohvpWdELdJ0x/AznHZ7ndb3qmyHDatELdJ0x/E2AZhlqVI1KQems\n2LUULdNx9V1joTUjUWOhuz1aJwzDrld9M3SGRo1pVM7Y2BjQ2qhnLVDtVG35z3zmMwF42tOeBiTR\nOt3cYKQX6Dpj+BnOOzzPi81QGTJcKOgFus4YfobzjjAM1xS3nSFDN6MX6Dpj+JsANdO0m2DSWE8d\nenXaatq+hmeq/bDbTTrQG5m2GZZCaau929ro6Gj891poW52dR48ebRl/x44dwNJub92KbqfrjOFn\nOO/wPC9unJEhw4WCXqDrjOFvAlSyaU+0Sn9eSxKWnqMJWKo+qvNWJf1uzPBLoxdU3wwrQwMEVKLV\nYmewNEx4NZiYmADgiSeeAOCqq64Ckv63p06d6nxiF6AX6Dpj+BnOO3rBuZUhw2rRC3SdMfxNxEZL\n+O2ag0ryGpapNnxNf4futOf3giSUoTOUBjURSkOP0zZ8LYewFglfNYbHH38cgKuvvhqAiy66CICH\nH344PrbbaLsX6Dpj+BnOO3rB1pkhw2rRC3SdMfxNRHtphbRUr9tWI6W0S/gqXem7bk8neHWbFARW\nEko3zDgXiMgNwAexNcP/xhhzc9v+/wv4NWzN8NPArxpjnnD7QuD77tAnjTE/TYZ1QaNolPZGRkbi\nfepTOnny5JrH13OVfrXUQjqTtdtoey10fb6RMfwM5x2rrTkiIj7wl8BPYjtN3SkitxljHkwddg9w\nvTFmUUR+A/gT4Bfdvqox5rqNmX2GDJ2R1dLZ5tA0dJXM0w4dlVTajzkX6LEq4egYWsBqvUXaNhtr\nUH1fABwyxhwGEJFPYHvMxgzfGPOvqeO/BbxuA6aaYRlopNjkpG0JrDZ2SGLnDx48CKyNtrVEgV5H\nc07SdNNt0WiZSSdDhg5YRvUdF5G7Up9vca0CoXM/2ReucIk3A19IfS65sQPgZmPMv6xt5hkyLI/M\npLPNoRK42jk1egGgv78fSKSUtTQ4V/VRm0aoDb9HJfwJY8z16x1bRF4HXA+8OLX5EmPMMRG5DPiq\niHzfGPPoeq+1naE0p9E0112XWMxU2l+Ln6p9fC2mtnfvXoCurkaZSfgZMnTAGiShc+onKyIvA94J\nvNgYU9ftxphj7v2wiHwNeA6QMfwMG4pMws8AJNJKWopXSUDt7qtp0twOjXfudsk+jVXWHLkTuFJE\nLsUy+tcAv5Q+QESeA/wVcIMx5lRq+wiwaIypi8g48KNYh26GDYA2LFFbOyQSvkbraHOTtdjy1Q+g\n9LKW/JXziW6vpXNWDiEiHxGRUyJyf2rbu0XkmIjc616vTO17h4gcEpFHROQVmzXxDL0Lz/OoVCot\nr5VgjAmAm4A7gIeATxljHhCR94iIhlj+KdAPfNrR5G1u+9XAXSJyH/CvWBv+g5DRdoaNxWrpeitw\nLhL+3wF/Adzatv0Dxpj3pTeIyDVY6etaYC/wZRG5yhjT3ctehvOKtai+xpjbsY3E09velfr7Zcuc\n9w3gmcsM+3dktJ1hg3BBmHSMMf8uIgfOcbwbgU84++ljInIIG1L3zTXP8AKAOm3T3XC0HIKGauox\nq0F7GWY1HXU7VBLaamS0vX5oApaWNQa45pprgKTgmZp0VgOl7fS4kIQgdyO6ha5XwnqMvjeJyPec\nWqxpdp3C5/Z1OllE3iIid4nIXWn7X4YLH2EYMjMz0/LqMmS0nWHV6AG6XrPT9kPAHwHGvf8Z8Kur\nGcDFWN8CsHfv3u5tRb8BaE8mgfU1QFlu/E6NVroRxphudm5ltL0KKO099NBD8Tbtc6va63poXMOW\nNTyzm2m8y+kaWCPDN8bERTJE5K+Bz7uP5xQ+l2F7w/f92KTVbchoO8Na0c10rVgTwxeRPcaYp9zH\nnwU0yuE24GMi8n6sY+tK4DvrnuUFgnS5WJV62t/XA01w6fbQtSAI4vK63YaMtteGw4cPx3+rHXtq\namrd4+pzoWWHN+I52Sx0M10rzsrwReTjwEuwqe9HgT8EXiIi12HV3seBtwK4ULlPYWucBMDbsiiG\nDO3wfT/ONN5KZLSdYSPRLXS9Es4lSue1HTZ/eIXj3wu8dz2TutDQSYrfzGbM3SwFgXVudYMklNH2\nxiHtnH7wQVvTbiPt2d1O09A9dL0SskzbDOcdveDcypBhtegFus4Y/hahFySWzYLneV2v+mZYO9LR\naNsJvUDXGcPPcN4RhuGGOPQyZOgm9AJdZww/w3lHL0hCGwURQURW1Og2Micjw9ahF+g6Y/gZzjt6\nwbmVIcNq0Qt0nTH8DOcdvRC+liHDatELdJ0x/AznHUEQdL2tc6NgjOloqun25LgMCc7V5NYLdJ0x\n/Axbgm4PX8uQYS3odrrOGH6G8w7P8xgYGGjZ9tRTTy1zdIZeQFpjudCcz+f6fXqBrjOGn+G8IwxD\nJicnt3oaGTJsKHqBrruK4WtPVu3vmqE7sd4wQs/zGBwcbNk2MTGx7nl1I0QEz/NWLJJ3IUjEvf4d\nVvKprEbC73a67iqGn2H7IFvUM1yI6Ha6lm5YmUVkDnhkq+exCRgHumuJ3xic7XtdYozZsdxOEfmi\nGyONCWPMDRsxuW5CRts9hzXTdi/Qdbcw/LuMMddv9Tw2Gtn3ynCh3qvse/Um1tPTNkOGDBky9BAy\nhp8hQ4YM2wTdwvBv2eoJbBKy75XhQr1X2ffqQXSFDT9DhgwZMmw+ukXCz5AhQ4YMm4yM4WfIkCHD\nNsGWM3wRuUFEHhGRQyLy/7dzxqxVBFEU/g5iKgWNRQgxoIJNOh8iKcQfkCaWVqbwB2j5wF+ghYVg\nqRBBtFEwjYWKYGUQRGM0kKiNSjSd2mlxLXZCFiGQR+CNs3M+WN7du6+4Z+a8y5vdZfq56xkESbck\nbUhabuVGJT2WtJY+D6a8JF1POpck9fJVvj2SJiU9k/Re0jtJF1O+aF05KNXbXfQ12NvA1vatOQ5g\nD/AROAaMAG+AqZw1DVj/GaAHLLdyV4F+ivvAlRTPAI8AAdPAYu76t9E0DvRSvB9YBaZK15VhHIv1\ndhd9nWqt3tu5/+GfAj5ExKeI+A3cA2Yz17RjIuI58O9uSbPAfIrngbOt/O1oeAEckDQ+nEp3TkSs\nR8SrFP8CVoAJCteVgWK93UVfg70N+W/pTACfW+dfUq5kxiJic0/Ub8BYiovTKukIcAJYpEO6hkTX\nxqVT81+rt3M3/E4TzbqwyPdeJe0D7gOXIuJn+1rJuszuKX3+a/Z27ob/FZhsnR9OuZL5vrnsS58b\nKV+MVkl7aX4QdyLiQUoXr2vIdG1cOjH/tXs7d8N/CRyXdFTSCHAOWMhc025ZAOZSPAc8bOXPpyf/\n08CP1jLyv0HNxuA3gZWIuNa6VLSuDHTN28XPv71N3rd0YutJ+CrNGw2Xc9czYO13gXXgD839vQvA\nIeApsAY8AUbTdwXcSDrfAidz17+NptM0S9ol4HU6ZkrXlWksi/R2F32daq3e295awRhjKiH3LR1j\njDFDwg3fGGMqwQ3fGGMqwQ3fGGMqwQ3fGGMqwQ3fGGMqwQ3fGGMq4S95H131hvI/igAAAABJRU5E\nrkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 7 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wO8cHAtLdksM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145
        },
        "outputId": "dc5e3f91-6107-401b-866b-ebc24508ed41"
      },
      "source": [
        "!pwd\n",
        "!ls"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/tf-pose-estimation\n",
            "CMakeLists.txt\tlaunch\t     requirements.txt\tscripts\n",
            "docker\t\tLICENSE      run_checkpoint.py\tsetup.py\n",
            "Dockerfile\tmodels\t     run_directory.py\ttf_pose\n",
            "etcs\t\tmsg\t     run.py\t\ttf-pose-estimation\n",
            "images\t\tpackage.xml  run_video.py\n",
            "__init__.py\tREADME.md    run_webcam.py\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}