study_roadmaps/4_image_classification_zoo/Classifier - Simpsons characer recognition.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a href=\"https://colab.research.google.com/github/Tessellate-Imaging/monk_v1/blob/master/study_roadmaps/4_image_classification_zoo/Classifier%20-%20Simpsons%20characer%20recognition.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Table of contents\n",
    "\n",
    "\n",
    "## Install Monk\n",
    "\n",
    "\n",
    "## Using pretrained model for classifying simpsons characters in images\n",
    "\n",
    "\n",
    "## Training a classifier from scratch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='0'></a>\n",
    "# Install Monk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using pip (Recommended)\n",
    "\n",
    "  - colab (gpu) \n",
    "      - All bakcends: `pip install -U monk-colab`\n",
    "      \n",
    "\n",
    "  - kaggle (gpu) \n",
    "      - All backends: `pip install -U monk-kaggle`\n",
    "      \n",
    "\n",
    "  - cuda 10.2\t\n",
    "      - All backends: `pip install -U monk-cuda102`\n",
    "      - Gluon bakcned: `pip install -U monk-gluon-cuda102`\n",
    "\t  - Pytorch backend: `pip install -U monk-pytorch-cuda102`\n",
    "      - Keras backend: `pip install -U monk-keras-cuda102`\n",
    "      \n",
    "\n",
    "  - cuda 10.1\t\n",
    "      - All backend: `pip install -U monk-cuda101`\n",
    "\t  - Gluon bakcned: `pip install -U monk-gluon-cuda101`\n",
    "\t  - Pytorch backend: `pip install -U monk-pytorch-cuda101`\n",
    "\t  - Keras backend: `pip install -U monk-keras-cuda101`\n",
    "      \n",
    "\n",
    "  - cuda 10.0\t\n",
    "      - All backend: `pip install -U monk-cuda100`\n",
    "\t  - Gluon bakcned: `pip install -U monk-gluon-cuda100`\n",
    "\t  - Pytorch backend: `pip install -U monk-pytorch-cuda100`\n",
    "\t  - Keras backend: `pip install -U monk-keras-cuda100`\n",
    "      \n",
    "\n",
    "  - cuda 9.2\t\n",
    "      - All backend: `pip install -U monk-cuda92`\n",
    "\t  - Gluon bakcned: `pip install -U monk-gluon-cuda92`\n",
    "\t  - Pytorch backend: `pip install -U monk-pytorch-cuda92`\n",
    "\t  - Keras backend: `pip install -U monk-keras-cuda92`\n",
    "      \n",
    "\n",
    "  - cuda 9.0\t\n",
    "      - All backend: `pip install -U monk-cuda90`\n",
    "\t  - Gluon bakcned: `pip install -U monk-gluon-cuda90`\n",
    "\t  - Pytorch backend: `pip install -U monk-pytorch-cuda90`\n",
    "\t  - Keras backend: `pip install -U monk-keras-cuda90`\n",
    "      \n",
    "\n",
    "  - cpu \t\t\n",
    "      - All backend: `pip install -U monk-cpu`\n",
    "\t  - Gluon bakcned: `pip install -U monk-gluon-cpu`\n",
    "\t  - Pytorch backend: `pip install -U monk-pytorch-cpu`\n",
    "\t  - Keras backend: `pip install -U monk-keras-cpu`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Install Monk Manually (Not recommended)\n",
    " \n",
    "### Step 1: Clone the library\n",
    " - git clone https://github.com/Tessellate-Imaging/monk_v1.git\n",
    " \n",
    " \n",
    " \n",
    " \n",
    "### Step 2: Install requirements \n",
    " - Linux\n",
    "     - Cuda 9.0\n",
    "         - `cd monk_v1/installation/Linux && pip install -r requirements_cu90.txt`\n",
    "     - Cuda 9.2\n",
    "         - `cd monk_v1/installation/Linux && pip install -r requirements_cu92.txt`\n",
    "     - Cuda 10.0\n",
    "         - `cd monk_v1/installation/Linux && pip install -r requirements_cu100.txt`\n",
    "     - Cuda 10.1\n",
    "         - `cd monk_v1/installation/Linux && pip install -r requirements_cu101.txt`\n",
    "     - Cuda 10.2\n",
    "         - `cd monk_v1/installation/Linux && pip install -r requirements_cu102.txt`\n",
    "     - CPU (Non gpu system)\n",
    "         - `cd monk_v1/installation/Linux && pip install -r requirements_cpu.txt`\n",
    " \n",
    " \n",
    "  - Windows\n",
    "     - Cuda 9.0 (Experimental support)\n",
    "         - `cd monk_v1/installation/Windows && pip install -r requirements_cu90.txt`\n",
    "     - Cuda 9.2 (Experimental support)\n",
    "         - `cd monk_v1/installation/Windows && pip install -r requirements_cu92.txt`\n",
    "     - Cuda 10.0 (Experimental support)\n",
    "         - `cd monk_v1/installation/Windows && pip install -r requirements_cu100.txt`\n",
    "     - Cuda 10.1 (Experimental support)\n",
    "         - `cd monk_v1/installation/Windows && pip install -r requirements_cu101.txt`\n",
    "     - Cuda 10.2 (Experimental support)\n",
    "         - `cd monk_v1/installation/Windows && pip install -r requirements_cu102.txt`\n",
    "     - CPU (Non gpu system)\n",
    "         - `cd monk_v1/installation/Windows && pip install -r requirements_cpu.txt`\n",
    "         \n",
    "         \n",
    "  - Mac\n",
    "     - CPU (Non gpu system)\n",
    "         - `cd monk_v1/installation/Mac && pip install -r requirements_cpu.txt`\n",
    "         \n",
    "         \n",
    "  - Misc\n",
    "      - Colab (GPU)\n",
    "          - `cd monk_v1/installation/Misc && pip install -r requirements_colab.txt`\n",
    "      - Kaggle (GPU)\n",
    "          - `cd monk_v1/installation/Misc && pip install -r requirements_kaggle.txt`\n",
    " \n",
    " \n",
    " \n",
    "### Step 3: Add to system path (Required for every terminal or kernel run)\n",
    " - `import sys`\n",
    " - `sys.path.append(\"monk_v1/\");`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Used trained classifier for demo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Using pytorch backend \n",
    "\n",
    "# When installed using pip\n",
    "from monk.pytorch_prototype import prototype\n",
    "\n",
    "\n",
    "# When installed manually (Uncomment the following)\n",
    "#import os\n",
    "#import sys\n",
    "#sys.path.append(\"monk_v1/\");\n",
    "#sys.path.append(\"monk_v1/monk/\");\n",
    "#from monk.pytorch_prototype import prototype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Download trained weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=1WqBI2QMIw31EQZWzqsH2ywvCtSdfrP9b' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\\1\\n/p')&id=1WqBI2QMIw31EQZWzqsH2ywvCtSdfrP9b\" -O cls_simpsons_trained.zip && rm -rf /tmp/cookies.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "! unzip -qq cls_simpsons_trained.zip "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0m\u001b[01;34mPytorch-alexnet\u001b[0m/  \u001b[01;34mPytorch-vgg16\u001b[0m/\r\n"
     ]
    }
   ],
   "source": [
    "ls workspace/Project-Anime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pytorch Version: 1.4.0\n",
      "\n",
      "Model Details\n",
      "    Loading model - workspace/Project-Anime/Pytorch-vgg16/output/models/final\n",
      "    Model loaded!\n",
      "\n",
      "Experiment Details\n",
      "    Project: Project-Anime\n",
      "    Experiment: Pytorch-vgg16\n",
      "    Dir: /home/ubuntu/Desktop/cls/workspace/Project-Anime/Pytorch-vgg16/\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Load project in inference mode\n",
    "\n",
    "gtf = prototype(verbose=1);\n",
    "gtf.Prototype(\"Project-Anime\", \"Pytorch-vgg16\", eval_infer=True);\n",
    "\n",
    "#Other trained models - uncomment \n",
    "#gtf.Prototype(\"Project-Anime\", \"Pytorch-alexnet\", eval_infer=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Infer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction\n",
      "    Image name:         workspace/test/pic_0001.jpg\n",
      "    Predicted class:      abraham_grampa_simpson\n",
      "    Predicted score:      0.6018852591514587\n",
      "\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_name = \"workspace/test/pic_0001.jpg\"\n",
    "predictions = gtf.Infer(img_name=img_name);\n",
    "from IPython.display import Image\n",
    "Image(filename=img_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction\n",
      "    Image name:         workspace/test/pic_0002.jpg\n",
      "    Predicted class:      bart_simpson\n",
      "    Predicted score:      0.5872443318367004\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_name = \"workspace/test/pic_0002.jpg\"\n",
    "predictions = gtf.Infer(img_name=img_name);\n",
    "from IPython.display import Image\n",
    "Image(filename=img_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction\n",
      "    Image name:         workspace/test/pic_0003.jpg\n",
      "    Predicted class:      fat_tony\n",
      "    Predicted score:      0.8638513088226318\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img_name = \"workspace/test/pic_0003.jpg\"\n",
    "predictions = gtf.Infer(img_name=img_name);\n",
    "from IPython.display import Image\n",
    "Image(filename=img_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training custom classifier from scratch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset\n",
    "    - Credits: https://www.kaggle.com/alexattia/the-simpsons-characters-dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Download"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! wget --load-cookies /tmp/cookies.txt \"https://docs.google.com/uc?export=download&confirm=$(wget --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate 'https://docs.google.com/uc?export=download&id=18uwjlrjZDrmE4zYehQ8f7n4T3wwOKhY2' -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\\1\\n/p')&id=18uwjlrjZDrmE4zYehQ8f7n4T3wwOKhY2\" -O the-simpsons-characters-dataset.zip && rm -rf /tmp/cookies.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "! unzip -q the-simpsons-characters-dataset.zip"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Using mxnet-gluon backend \n",
    "#from monk.gluon_prototype import prototype\n",
    "\n",
    "# For pytorch backend\n",
    "from monk.pytorch_prototype import prototype\n",
    "\n",
    "# For Keras backend\n",
    "#from monk.keras_prototype import prototype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Project and Experiment\n",
    "\n",
    "gtf = prototype(verbose=1);\n",
    "gtf.Prototype(\"Project-Anime\", \"Mxnet-alexnet\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "gtf.Default(dataset_path=\"the-simpsons-characters-dataset/train\",\n",
    "            model_name=\"alexnet\", \n",
    "            freeze_base_network=False,\n",
    "            num_epochs=2);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to change hyper parameters and models \n",
    "  - Docs - https://github.com/Tessellate-Imaging/monk_v1#4\n",
    "  - Examples - https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/1_getting_started_roadmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Start Training\n",
    "gtf.Train();\n",
    "\n",
    "#Read the training summary generated once you run the cell and training is completed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Validating on the same dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Using mxnet-gluon backend \n",
    "#from monk.gluon_prototype import prototype\n",
    "\n",
    "# For pytorch backend\n",
    "from monk.pytorch_prototype import prototype\n",
    "\n",
    "# For Keras backend\n",
    "#from monk.keras_prototype import prototype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create Project and Experiment\n",
    "\n",
    "gtf = prototype(verbose=1);\n",
    "gtf.Prototype(\"Project-Anime\", \"Mxnet-alexnet\", eval_infer=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load dataset for validaion\n",
    "gtf.Dataset_Params(dataset_path=\"the-simpsons-characters-dataset/train\");\n",
    "gtf.Dataset();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run validation\n",
    "accuracy, class_based_accuracy = gtf.Evaluate();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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