binary_classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "metadata": {
    "cell_id": "349e1598-1169-48bc-952d-995cc5542c9f",
    "deepnote_cell_type": "code"
   },
   "source": "!python --version\n!pip install tensorflow\n!pip install opencv-python\n!pip install tensorflow",
   "outputs": [
    {
     "name": "stdout",
     "text": "Python 3.7.3\nCollecting tensorflow\n  Downloading tensorflow-2.1.0-cp37-cp37m-manylinux2010_x86_64.whl (421.8 MB)\n\u001b[K     |████████████████████████████████| 421.8 MB 15 kB/s s eta 0:00:01\n\u001b[?25hRequirement already satisfied: grpcio>=1.8.6 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.26.0)\nRequirement already satisfied: gast==0.2.2 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.2.2)\nRequirement already satisfied: google-pasta>=0.1.6 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.1.8)\nRequirement already satisfied: numpy<2.0,>=1.16.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.18.1)\nRequirement already satisfied: keras-preprocessing>=1.1.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.1.0)\nRequirement already satisfied: tensorboard<2.2.0,>=2.1.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (2.1.0)\nRequirement already satisfied: astor>=0.6.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.8.1)\nRequirement already satisfied: absl-py>=0.7.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.9.0)\nRequirement already satisfied: opt-einsum>=2.3.2 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (3.1.0)\nRequirement already satisfied: wrapt>=1.11.1 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.11.2)\nRequirement already satisfied: protobuf>=3.8.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (3.11.2)\nRequirement already satisfied: six>=1.12.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.14.0)\nRequirement already satisfied: termcolor>=1.1.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.1.0)\nRequirement already satisfied: keras-applications>=1.0.8 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.0.8)\nRequirement already satisfied: wheel>=0.26; python_version >= \"3\" in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.33.6)\nRequirement already satisfied: tensorflow-estimator<2.2.0,>=2.1.0rc0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (2.1.0)\nRequirement already satisfied: scipy==1.4.1; python_version >= \"3\" in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.4.1)\nRequirement already satisfied: markdown>=2.6.8 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (3.1.1)\nRequirement already satisfied: werkzeug>=0.11.15 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (0.16.0)\nRequirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (0.4.1)\nRequirement already satisfied: requests<3,>=2.21.0 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (2.22.0)\nRequirement already satisfied: setuptools>=41.0.0 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (45.1.0)\nRequirement already satisfied: google-auth<2,>=1.6.3 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (1.11.0)\nRequirement already satisfied: h5py in /opt/venv/lib/python3.7/site-packages (from keras-applications>=1.0.8->tensorflow) (2.10.0)\nRequirement already satisfied: requests-oauthlib>=0.7.0 in /opt/venv/lib/python3.7/site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow) (1.3.0)\nRequirement already satisfied: certifi>=2017.4.17 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (2019.11.28)\nRequirement already satisfied: idna<2.9,>=2.5 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (2.8)\nRequirement already satisfied: chardet<3.1.0,>=3.0.2 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (3.0.4)\nRequirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (1.25.8)\nRequirement already satisfied: cachetools<5.0,>=2.0.0 in /opt/venv/lib/python3.7/site-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (4.0.0)\nRequirement already satisfied: rsa<4.1,>=3.1.4 in /opt/venv/lib/python3.7/site-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (4.0)\nRequirement already satisfied: pyasn1-modules>=0.2.1 in /opt/venv/lib/python3.7/site-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (0.2.8)\nRequirement already satisfied: oauthlib>=3.0.0 in /opt/venv/lib/python3.7/site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow) (3.1.0)\nRequirement already satisfied: pyasn1>=0.1.3 in /opt/venv/lib/python3.7/site-packages (from rsa<4.1,>=3.1.4->google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (0.4.8)\nInstalling collected packages: tensorflow\n\u001b[31mERROR: Could not install packages due to an EnvironmentError: [Errno 13] Permission denied: '/opt/venv/lib/python3.7/site-packages/tensorflow_core/libtensorflow_framework.so.2'\nConsider using the `--user` option or check the permissions.\n\u001b[0m\n\u001b[33mWARNING: You are using pip version 20.0.1; however, version 20.0.2 is available.\nYou should consider upgrading via the '/opt/venv/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\nRequirement already satisfied: opencv-python in /opt/venv/lib/python3.7/site-packages (4.2.0.32)\nRequirement already satisfied: numpy>=1.14.5 in /opt/venv/lib/python3.7/site-packages (from opencv-python) (1.18.1)\n\u001b[33mWARNING: You are using pip version 20.0.1; however, version 20.0.2 is available.\nYou should consider upgrading via the '/opt/venv/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\nCollecting tensorflow\n  Using cached tensorflow-2.1.0-cp37-cp37m-manylinux2010_x86_64.whl (421.8 MB)\nRequirement already satisfied: grpcio>=1.8.6 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.26.0)\nRequirement already satisfied: tensorboard<2.2.0,>=2.1.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (2.1.0)\nRequirement already satisfied: wheel>=0.26; python_version >= \"3\" in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.33.6)\nRequirement already satisfied: opt-einsum>=2.3.2 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (3.1.0)\nRequirement already satisfied: wrapt>=1.11.1 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.11.2)\nRequirement already satisfied: google-pasta>=0.1.6 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.1.8)\nRequirement already satisfied: gast==0.2.2 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.2.2)\nRequirement already satisfied: astor>=0.6.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.8.1)\nRequirement already satisfied: termcolor>=1.1.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.1.0)\nRequirement already satisfied: scipy==1.4.1; python_version >= \"3\" in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.4.1)\nRequirement already satisfied: six>=1.12.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.14.0)\nRequirement already satisfied: protobuf>=3.8.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (3.11.2)\nRequirement already satisfied: absl-py>=0.7.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (0.9.0)\nRequirement already satisfied: numpy<2.0,>=1.16.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.18.1)\nRequirement already satisfied: keras-applications>=1.0.8 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.0.8)\nRequirement already satisfied: tensorflow-estimator<2.2.0,>=2.1.0rc0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (2.1.0)\nRequirement already satisfied: keras-preprocessing>=1.1.0 in /opt/venv/lib/python3.7/site-packages (from tensorflow) (1.1.0)\nRequirement already satisfied: markdown>=2.6.8 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (3.1.1)\nRequirement already satisfied: werkzeug>=0.11.15 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (0.16.0)\nRequirement already satisfied: requests<3,>=2.21.0 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (2.22.0)\nRequirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (0.4.1)\nRequirement already satisfied: google-auth<2,>=1.6.3 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (1.11.0)\nRequirement already satisfied: setuptools>=41.0.0 in /opt/venv/lib/python3.7/site-packages (from tensorboard<2.2.0,>=2.1.0->tensorflow) (45.1.0)\nRequirement already satisfied: h5py in /opt/venv/lib/python3.7/site-packages (from keras-applications>=1.0.8->tensorflow) (2.10.0)\nRequirement already satisfied: certifi>=2017.4.17 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (2019.11.28)\nRequirement already satisfied: chardet<3.1.0,>=3.0.2 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (3.0.4)\nRequirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (1.25.8)\nRequirement already satisfied: idna<2.9,>=2.5 in /opt/venv/lib/python3.7/site-packages (from requests<3,>=2.21.0->tensorboard<2.2.0,>=2.1.0->tensorflow) (2.8)\nRequirement already satisfied: requests-oauthlib>=0.7.0 in /opt/venv/lib/python3.7/site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow) (1.3.0)\nRequirement already satisfied: pyasn1-modules>=0.2.1 in /opt/venv/lib/python3.7/site-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (0.2.8)\nRequirement already satisfied: rsa<4.1,>=3.1.4 in /opt/venv/lib/python3.7/site-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (4.0)\nRequirement already satisfied: cachetools<5.0,>=2.0.0 in /opt/venv/lib/python3.7/site-packages (from google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (4.0.0)\nRequirement already satisfied: oauthlib>=3.0.0 in /opt/venv/lib/python3.7/site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.2.0,>=2.1.0->tensorflow) (3.1.0)\nRequirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /opt/venv/lib/python3.7/site-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard<2.2.0,>=2.1.0->tensorflow) (0.4.8)\nInstalling collected packages: tensorflow\n\u001b[31mERROR: Could not install packages due to an EnvironmentError: [Errno 13] Permission denied: '/opt/venv/lib/python3.7/site-packages/tensorflow_core/libtensorflow_framework.so.2'\nConsider using the `--user` option or check the permissions.\n\u001b[0m\n\u001b[33mWARNING: You are using pip version 20.0.1; however, version 20.0.2 is available.\nYou should consider upgrading via the '/opt/venv/bin/python3 -m pip install --upgrade pip' command.\u001b[0m\n",
     "output_type": "stream"
    }
   ],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "cell_id": "00001-9cfd1d84-0ba4-404d-9614-18190d7ba244",
    "deepnote_cell_type": "code"
   },
   "source": "import numpy as np\nimport tensorflow as tf\nimport cv2\nimport os\nimport sklearn\nimport sklearn.model_selection\nimport matplotlib.pyplot as plt",
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00002-59fab34e-73fd-4dad-a1fd-8dafe2885257",
    "deepnote_cell_type": "code"
   },
   "source": "training_images = []\ntraining_labels = []\n\nlabel_dict = {0:\"Electrocautery Tool\", 1:\"Shaver Tool\"}\n\nfor i in os.listdir(\"training_images/electrocautery_training/electrocauteryMin3_electrocauterysegs/\"):\n    if \"png\" in str(i):\n        print(\"reading image: \" + \"training_images/electrocautery_training/electrocauteryMin3_electrocauterysegs/\" + str(i))\n        img = cv2.imread(\"training_images/electrocautery_training/electrocauteryMin3_electrocauterysegs/\" + str(i))\n        img = cv2.resize(img, (128,128))\n        training_images.append(img)\n        training_labels.append(0)\n\nfor i in os.listdir(\"training_images/shaver_training/electrocauteryMin1_shaverimages/\"):\n    if \"png\" in str(i):\n        print(\"reading image: \" + \"training_images/shaver_training/electrocauteryMin1_shaverimages/\" + str(i))\n        img = cv2.imread(\"training_images/shaver_training/electrocauteryMin1_shaverimages/\" + str(i))\n        img = cv2.resize(img, (128,128))\n        training_images.append(img)\n        training_labels.append(1)\n        \nfor i in os.listdir(\"training_images/shaver_training/electrocauteryMin3_shaverimages/\"):\n    if \"png\" in str(i):\n        print(\"reading image: \" + \"training_images/shaver_training/electrocauteryMin3_shaverimages/\" + str(i))\n        img = cv2.imread(\"training_images/shaver_training/electrocauteryMin3_shaverimages/\" + str(i))\n        img = cv2.resize(img, (128,128))\n        training_images.append(img)\n        training_labels.append(1)",
   "outputs": [
    {
     "name": "stdout",
     "text": "reading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame5501.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame10440.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12920.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame7566.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11551.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12181.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12300.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame5.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11441.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame14435.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame9973.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame9511.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11281.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12471.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12692.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame7539.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame8962.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11961.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame5679.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame9892.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12647.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame2634.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame14421.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame3329.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame2217.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame4119.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame3792.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11995.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame3940.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame2629.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame5449.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13323.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame3795.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame212.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13726.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame14296.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame4835.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13911.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame10619.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame9950.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame7961.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11112.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame4060.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13069.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11602.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11884.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame6726.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame7468.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame3788.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12593.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11949.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11505.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame9522.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame6670.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13386.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame3945.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame6512.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame5670.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11795.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11640.png\nreading image: 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training_images/shaver_training/electrocauteryMin3_shaverimages/frame12632.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame7523.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame14419.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame11877.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame7973.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12170.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13841.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame12840.png\nreading image: training_images/shaver_training/electrocauteryMin3_shaverimages/frame13197.png\n",
     "output_type": "stream"
    }
   ],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00003-11da4e3e-f762-49fa-9551-835ce1d84f5a",
    "deepnote_cell_type": "code"
   },
   "source": "training_images = np.array(training_images)\ntraining_labels = np.array(training_labels)\n\ndef unison_shuffle(A, B):\n    state = np.random.get_state()\n    np.random.shuffle(A)\n    np.random.set_state(state)\n    np.random.shuffle(B)\n    \nunison_shuffle(training_images, training_labels)\n\ntesting_images = training_images[int(len(training_images) * 0.8) : int(len(training_images))]\ntesting_labels = training_labels[int(len(training_labels) * 0.8): int(len(training_labels))]\n\ntraining_images = training_images[0: int(len(training_images)* 0.8)]\ntraining_labels = training_labels[0: int(len(training_labels) * 0.8)]\n",
   "outputs": [],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00004-15d7109f-b189-4208-a445-99972ad8f85e",
    "deepnote_cell_type": "code"
   },
   "source": "model = tf.keras.Sequential()\n#First block\nmodel.add(tf.keras.layers.Conv2D(32, (3,3), input_shape=(128,128, 3), activation='relu', padding=\"same\", kernel_regularizer=tf.keras.regularizers.l2(0.001)))\nmodel.add(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(tf.keras.layers.BatchNormalization())\nmodel.add(tf.keras.layers.Conv2D(32, (3,3), activation='relu', padding=\"same\", kernel_regularizer=tf.keras.regularizers.l2(0.001)))\nmodel.add(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(tf.keras.layers.BatchNormalization())\nmodel.add(tf.keras.layers.Dropout(0.4))\n\n#Second block\nmodel.add(tf.keras.layers.Conv2D(64, (3,3), activation='relu', padding=\"same\", kernel_regularizer=tf.keras.regularizers.l2(0.001)))\nmodel.add(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(tf.keras.layers.BatchNormalization())\nmodel.add(tf.keras.layers.Conv2D(64, (3,3), activation='relu', padding=\"same\", kernel_regularizer=tf.keras.regularizers.l2(0.001)))\nmodel.add(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(tf.keras.layers.BatchNormalization())\nmodel.add(tf.keras.layers.Dropout(0.4))\n\n#Third block\nmodel.add(tf.keras.layers.Conv2D(128, (3,3), activation='relu', padding=\"same\", kernel_regularizer=tf.keras.regularizers.l2(0.001)))\nmodel.add(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(tf.keras.layers.BatchNormalization())\nmodel.add(tf.keras.layers.Conv2D(128, (3,3), activation='relu', padding=\"same\", kernel_regularizer=tf.keras.regularizers.l2(0.001)))\nmodel.add(tf.keras.layers.MaxPooling2D(pool_size=(2,2)))\nmodel.add(tf.keras.layers.BatchNormalization())\nmodel.add(tf.keras.layers.Dropout(0.4))\n\n\n#Fully Connected Layers\nmodel.add(tf.keras.layers.Flatten())\nmodel.add(tf.keras.layers.Dense(128, activation='relu'))\nmodel.add(tf.keras.layers.Dense(64, activation='relu'))\nmodel.add(tf.keras.layers.Dropout(0.5))\nmodel.add(tf.keras.layers.Dense(1, activation='sigmoid'))\n\nprint(model.summary())",
   "outputs": [
    {
     "name": "stdout",
     "text": "Model: \"sequential_5\"\n_________________________________________________________________\nLayer (type)                 Output Shape              Param #   \n=================================================================\nconv2d_30 (Conv2D)           (None, 128, 128, 32)      896       \n_________________________________________________________________\nmax_pooling2d_30 (MaxPooling (None, 64, 64, 32)        0         \n_________________________________________________________________\nbatch_normalization_30 (Batc (None, 64, 64, 32)        128       \n_________________________________________________________________\nconv2d_31 (Conv2D)           (None, 64, 64, 32)        9248      \n_________________________________________________________________\nmax_pooling2d_31 (MaxPooling (None, 32, 32, 32)        0         \n_________________________________________________________________\nbatch_normalization_31 (Batc (None, 32, 32, 32)        128       \n_________________________________________________________________\ndropout_20 (Dropout)         (None, 32, 32, 32)        0         \n_________________________________________________________________\nconv2d_32 (Conv2D)           (None, 32, 32, 64)        18496     \n_________________________________________________________________\nmax_pooling2d_32 (MaxPooling (None, 16, 16, 64)        0         \n_________________________________________________________________\nbatch_normalization_32 (Batc (None, 16, 16, 64)        256       \n_________________________________________________________________\nconv2d_33 (Conv2D)           (None, 16, 16, 64)        36928     \n_________________________________________________________________\nmax_pooling2d_33 (MaxPooling (None, 8, 8, 64)          0         \n_________________________________________________________________\nbatch_normalization_33 (Batc (None, 8, 8, 64)          256       \n_________________________________________________________________\ndropout_21 (Dropout)         (None, 8, 8, 64)          0         \n_________________________________________________________________\nconv2d_34 (Conv2D)           (None, 8, 8, 128)         73856     \n_________________________________________________________________\nmax_pooling2d_34 (MaxPooling (None, 4, 4, 128)         0         \n_________________________________________________________________\nbatch_normalization_34 (Batc (None, 4, 4, 128)         512       \n_________________________________________________________________\nconv2d_35 (Conv2D)           (None, 4, 4, 128)         147584    \n_________________________________________________________________\nmax_pooling2d_35 (MaxPooling (None, 2, 2, 128)         0         \n_________________________________________________________________\nbatch_normalization_35 (Batc (None, 2, 2, 128)         512       \n_________________________________________________________________\ndropout_22 (Dropout)         (None, 2, 2, 128)         0         \n_________________________________________________________________\nflatten_5 (Flatten)          (None, 512)               0         \n_________________________________________________________________\ndense_15 (Dense)             (None, 128)               65664     \n_________________________________________________________________\ndense_16 (Dense)             (None, 64)                8256      \n_________________________________________________________________\ndropout_23 (Dropout)         (None, 64)                0         \n_________________________________________________________________\ndense_17 (Dense)             (None, 1)                 65        \n=================================================================\nTotal params: 362,785\nTrainable params: 361,889\nNon-trainable params: 896\n_________________________________________________________________\nNone\n",
     "output_type": "stream"
    }
   ],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00005-345419b0-c479-447d-bf5a-bc354a87c06a",
    "deepnote_cell_type": "code"
   },
   "source": "print(training_images.shape)\nprint(training_labels.shape)",
   "outputs": [
    {
     "name": "stdout",
     "text": "(13162, 256, 256, 3)\n(13162,)\n",
     "output_type": "stream"
    }
   ],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00006-a1baa0c9-55dc-4005-8d4e-24bf3c530aef",
    "deepnote_cell_type": "code"
   },
   "source": "model.compile(optimizer=tf.keras.optimizers.SGD(), loss='binary_crossentropy', metrics=['accuracy'])\n\ncallback = tf.keras.callbacks.EarlyStopping(monitor='accuracy', patience=3)\nhistory = model.fit(training_images, training_labels, epochs=200, callbacks=[callback])\n\n",
   "outputs": [
    {
     "name": "stdout",
     "text": "Train on 13162 samples\nEpoch 1/200\n13162/13162 [==============================] - 8s 586us/sample - loss: 0.7996 - accuracy: 0.7920\nEpoch 2/200\n13162/13162 [==============================] - 6s 486us/sample - loss: 0.6060 - accuracy: 0.8957\nEpoch 3/200\n13162/13162 [==============================] - 7s 494us/sample - loss: 0.5485 - accuracy: 0.9200\nEpoch 4/200\n13162/13162 [==============================] - 7s 496us/sample - loss: 0.5097 - accuracy: 0.9365\nEpoch 5/200\n13162/13162 [==============================] - 6s 488us/sample - loss: 0.4847 - accuracy: 0.9456\nEpoch 6/200\n13162/13162 [==============================] - 6s 490us/sample - loss: 0.4689 - accuracy: 0.9489\nEpoch 7/200\n13162/13162 [==============================] - 6s 489us/sample - loss: 0.4417 - accuracy: 0.9581\nEpoch 8/200\n13162/13162 [==============================] - 6s 488us/sample - loss: 0.4225 - accuracy: 0.9640\nEpoch 9/200\n13162/13162 [==============================] - 6s 493us/sample - loss: 0.4160 - accuracy: 0.9656\nEpoch 10/200\n13162/13162 [==============================] - 6s 487us/sample - loss: 0.4017 - accuracy: 0.9695\nEpoch 11/200\n13162/13162 [==============================] - 6s 487us/sample - loss: 0.3943 - accuracy: 0.9714\nEpoch 12/200\n13162/13162 [==============================] - 6s 486us/sample - loss: 0.3789 - accuracy: 0.9746\nEpoch 13/200\n13162/13162 [==============================] - 6s 493us/sample - loss: 0.3738 - accuracy: 0.9747\nEpoch 14/200\n13162/13162 [==============================] - 6s 487us/sample - loss: 0.3602 - accuracy: 0.9784\nEpoch 15/200\n13162/13162 [==============================] - 6s 488us/sample - loss: 0.3522 - accuracy: 0.9806\nEpoch 16/200\n13162/13162 [==============================] - 6s 488us/sample - loss: 0.3451 - accuracy: 0.9795\nEpoch 17/200\n13162/13162 [==============================] - 6s 489us/sample - loss: 0.3418 - accuracy: 0.9813\nEpoch 18/200\n13162/13162 [==============================] - 6s 490us/sample - loss: 0.3336 - accuracy: 0.9819\nEpoch 19/200\n13162/13162 [==============================] - 6s 488us/sample - loss: 0.3307 - accuracy: 0.9816\nEpoch 20/200\n13162/13162 [==============================] - 6s 485us/sample - loss: 0.3237 - accuracy: 0.9821\nEpoch 21/200\n13162/13162 [==============================] - 6s 489us/sample - loss: 0.3140 - accuracy: 0.9843\nEpoch 22/200\n13162/13162 [==============================] - 6s 491us/sample - loss: 0.3075 - accuracy: 0.9846\nEpoch 23/200\n13162/13162 [==============================] - 6s 492us/sample - loss: 0.3065 - accuracy: 0.9845\nEpoch 24/200\n13162/13162 [==============================] - 6s 490us/sample - loss: 0.2969 - accuracy: 0.9861\nEpoch 25/200\n13162/13162 [==============================] - 7s 503us/sample - loss: 0.2961 - accuracy: 0.9856\nEpoch 26/200\n13162/13162 [==============================] - 7s 504us/sample - loss: 0.2864 - accuracy: 0.9873\nEpoch 27/200\n13162/13162 [==============================] - 7s 496us/sample - loss: 0.2815 - accuracy: 0.9879\nEpoch 28/200\n13162/13162 [==============================] - 6s 492us/sample - loss: 0.2731 - accuracy: 0.9897\nEpoch 29/200\n13162/13162 [==============================] - 6s 490us/sample - loss: 0.2705 - accuracy: 0.9895\nEpoch 30/200\n13162/13162 [==============================] - 6s 486us/sample - loss: 0.2668 - accuracy: 0.9893\nEpoch 31/200\n13162/13162 [==============================] - 6s 490us/sample - loss: 0.2626 - accuracy: 0.9892\n",
     "output_type": "stream"
    }
   ],
   "execution_count": null
  },
  {
   "cell_type": "code",
   "metadata": {
    "tags": [],
    "cell_id": "00007-6ace5071-0150-4dbe-9ab0-856d813f1f63",
    "deepnote_cell_type": "code"
   },
   "source": "train_loss, train_acc = model.evaluate(training_images, training_labels)\ntest_loss, test_acc = model.evaluate(testing_images, testing_labels)\n\nprint(\"Train Accuracy: \" + str(train_acc) + \" Train Loss: \" + str(train_loss))\nprint(\"Test Accuracy: \" + str(test_acc) + \" Test Loss: \" + str(test_loss))\n\n\nfor i in range(300):\n    pred = 1 if model.predict(np.expand_dims(testing_images[i], 0)) > 0.5 else 0\n    print(\"Model Predicted \" + str(label_dict[pred]) + \" and it was Actually \" + str(label_dict[testing_labels[i]]))\n    \n     ",
   "outputs": [
    {
     "name": "stdout",
     "text": "13162/13162 [==============================] - 3s 217us/sample - loss: 0.4585 - accuracy: 0.9231\n3291/3291 [==============================] - 1s 193us/sample - loss: 0.4897 - accuracy: 0.9149\nTrain Accuracy: 0.923112 Train Loss: 0.45848443901316044\nTest Accuracy: 0.9149195 Test Loss: 0.48969730612573126\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Shaver Tool and it was Actually Shaver Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\nModel Predicted Electrocautery Tool and it was Actually Electrocautery Tool\n",
     "output_type": "stream"
    }
   ],
   "execution_count": null
  },
  {
   "cell_type": "markdown",
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