Lesson 10, Object Detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
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   "id": "08e0f548",
   "metadata": {},
   "outputs": [],
   "source": [
    "#! pip install pyyaml==5.1\n",
    "#! python -m pip install git+https://github.com/facebookresearch/detectron2.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "66007567",
   "metadata": {},
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "module 'torch.jit' has no attribute 'script_if_tracing'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[1;32m~\\AppData\\Local\\Temp/ipykernel_12076/1516313882.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0msetup_logger\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 5\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmodel_zoo\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      6\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mengine\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mDefaultPredictor\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mget_cfg\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\ml-learning\\ml_env\\lib\\site-packages\\detectron2\\model_zoo\\__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      6\u001b[0m \"\"\"\n\u001b[0;32m      7\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mmodel_zoo\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mget\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_config_file\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_checkpoint_url\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_config\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[0m__all__\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;34m\"get_checkpoint_url\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"get\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"get_config_file\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m\"get_config\"\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\ml-learning\\ml_env\\lib\\site-packages\\detectron2\\model_zoo\\model_zoo.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcheckpoint\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mDetectionCheckpointer\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mconfig\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mCfgNode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mLazyConfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_cfg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minstantiate\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmodeling\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mbuild_model\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     10\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\ml-learning\\ml_env\\lib\\site-packages\\detectron2\\modeling\\__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Copyright (c) Facebook, Inc. and its affiliates.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlayers\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mShapeSpec\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0manchor_generator\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mbuild_anchor_generator\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mANCHOR_GENERATOR_REGISTRY\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m from .backbone import (\n",
      "\u001b[1;32md:\\ml-learning\\ml_env\\lib\\site-packages\\detectron2\\layers\\__init__.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;31m# Copyright (c) Facebook, Inc. and its affiliates.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mbatch_norm\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mFrozenBatchNorm2d\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mget_norm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mNaiveSyncBatchNorm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mCycleBatchNormList\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mdeform_conv\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mDeformConv\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mModulatedDeformConv\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mmask_ops\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mpaste_masks_in_image\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      5\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mnms\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mbatched_nms\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbatched_nms_rotated\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnms\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnms_rotated\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\ml-learning\\ml_env\\lib\\site-packages\\detectron2\\layers\\batch_norm.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      8\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mdetectron2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mutils\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mcomm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0menv\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      9\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 10\u001b[1;33m \u001b[1;32mfrom\u001b[0m \u001b[1;33m.\u001b[0m\u001b[0mwrappers\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mBatchNorm2d\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     11\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     12\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32md:\\ml-learning\\ml_env\\lib\\site-packages\\detectron2\\layers\\wrappers.py\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m    140\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    141\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 142\u001b[1;33m \u001b[1;33m@\u001b[0m\u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mscript_if_tracing\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    143\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0mmove_device_like\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdst\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mTensor\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    144\u001b[0m     \"\"\"\n",
      "\u001b[1;31mAttributeError\u001b[0m: module 'torch.jit' has no attribute 'script_if_tracing'"
     ]
    }
   ],
   "source": [
    "import torch, detectron2\n",
    "from detectron2.utils.logger import setup_logger\n",
    "setup_logger()\n",
    "\n",
    "from detectron2 import model_zoo\n",
    "from detectron2.engine import DefaultPredictor\n",
    "from detectron2.config import get_cfg\n",
    "from detectron2.utils.visualizer import Visualizer\n",
    "from detectron2.data import MetadataCatalog, DatasetCatalog\n",
    "\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef80e0ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "response = requests.get('http://images.cocodataset.org/val2017/000000439715.jpg')\n",
    "open(\"input.jpg\", \"wb\").write(response.content)\n",
    "    \n",
    "im = cv2.imread(\"./input.jpg\")\n",
    "fig, ax = plt.subplots(figsize=(18, 8))\n",
    "ax.imshow(cv2.cvtColor(im, cv2.COLOR_BGR2RGB))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4368262a",
   "metadata": {},
   "outputs": [],
   "source": [
    "cfg = get_cfg()\n",
    "\n",
    "cfg.merge_from_file(model_zoo.get_config_file(\"COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml\"))\n",
    "cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5\n",
    "cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(\"COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml\")\n",
    "# If you don't have a GPU and CUDA enabled, the next line is required\n",
    "# cfg.MODEL.DEVICE = \"cpu\"\n",
    "predictor = DefaultPredictor(cfg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c4bb6b2a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b28f822",
   "metadata": {},
   "outputs": [],
   "source": [
    "outputs = predictor(im)\n",
    "\n",
    "v = Visualizer(im[:, :, ::-1], MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), scale=1.2)\n",
    "out = v.draw_instance_predictions(outputs[\"instances\"].to(\"cpu\"))\n",
    "fig, ax = plt.subplots(figsize=(18, 8))\n",
    "ax.imshow(out.get_image()[:, :, ::-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4bbc54a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "#cap = cv2.VideoCapture(0)\n",
    "cap = cv2.VideoCapture('tesla.mp4')\n",
    "while cap.isOpened():\n",
    "    ret, frame = cap.read()\n",
    "    \n",
    "    # Make detections \n",
    "    results = model(frame)\n",
    "    cv2.imshow('YOLO', np.squeeze(results.render()))\n",
    "    \n",
    "    if cv2.waitKey(10) & 0xFF == ord('q'):\n",
    "        break\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2f371d9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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