YOLO part3-0 processing_video.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/ankit/anaconda/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parsing ./cfg/yolo.cfg\n",
      "Parsing cfg/yolo.cfg\n",
      "Loading bin/yolo.weights ...\n",
      "Successfully identified 203934260 bytes\n",
      "Finished in 0.056984901428222656s\n",
      "Model has a coco model name, loading coco labels.\n",
      "\n",
      "Building net ...\n",
      "Source | Train? | Layer description                | Output size\n",
      "-------+--------+----------------------------------+---------------\n",
      "       |        | input                            | (?, 608, 608, 3)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 608, 608, 32)\n",
      " Load  |  Yep!  | maxp 2x2p0_2                     | (?, 304, 304, 32)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 304, 304, 64)\n",
      " Load  |  Yep!  | maxp 2x2p0_2                     | (?, 152, 152, 64)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 152, 152, 128)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 152, 152, 64)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 152, 152, 128)\n",
      " Load  |  Yep!  | maxp 2x2p0_2                     | (?, 76, 76, 128)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 76, 76, 256)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 76, 76, 128)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 76, 76, 256)\n",
      " Load  |  Yep!  | maxp 2x2p0_2                     | (?, 38, 38, 256)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 38, 38, 512)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 38, 38, 256)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 38, 38, 512)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 38, 38, 256)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 38, 38, 512)\n",
      " Load  |  Yep!  | maxp 2x2p0_2                     | (?, 19, 19, 512)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 19, 19, 512)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 19, 19, 512)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)\n",
      " Load  |  Yep!  | concat [16]                      | (?, 38, 38, 512)\n",
      " Load  |  Yep!  | conv 1x1p0_1  +bnorm  leaky      | (?, 38, 38, 64)\n",
      " Load  |  Yep!  | local flatten 2x2                | (?, 19, 19, 256)\n",
      " Load  |  Yep!  | concat [27, 24]                  | (?, 19, 19, 1280)\n",
      " Load  |  Yep!  | conv 3x3p1_1  +bnorm  leaky      | (?, 19, 19, 1024)\n",
      " Load  |  Yep!  | conv 1x1p0_1    linear           | (?, 19, 19, 425)\n",
      "-------+--------+----------------------------------+---------------\n",
      "GPU mode with 1.0 usage\n",
      "Finished in 4.404870271682739s\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FPS 0.4\n",
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     ]
    }
   ],
   "source": [
    "'''\n",
    "This file removes frames from a videofile.\n",
    "The resulting file will look faster when played back at normal speed.\n",
    "The idea is to create video that can be processed by yolo and look normal speed \n",
    "'''\n",
    "\n",
    "\n",
    "import cv2\n",
    "from darkflow.net.build import TFNet\n",
    "import numpy as np\n",
    "import time\n",
    "\n",
    "option = {\n",
    "    'model': 'cfg/yolo.cfg',\n",
    "    'load': 'bin/yolo.weights',\n",
    "    'threshold': 0.15,\n",
    "    'gpu': 1.0\n",
    "}\n",
    "\n",
    "tfnet = TFNet(option)\n",
    "\n",
    "capture = cv2.VideoCapture('/home/ankit/darkflow/ParkRace.mp4')\n",
    "size = (\n",
    "    int(capture.get(cv2.CAP_PROP_FRAME_WIDTH)),\n",
    "    int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT))\n",
    ")\n",
    "codec = cv2.VideoWriter_fourcc(*'XVID')\n",
    "output = cv2.VideoWriter('output2.avi', codec, 60.0, size)\n",
    "colors = [tuple(255 * np.random.rand(3)) for i in range(5)]\n",
    "\n",
    "\n",
    "i = 0\n",
    "frame_rate_divider = 3\n",
    "while(capture.isOpened()):\n",
    "    stime = time.time()\n",
    "    ret, frame = capture.read()\n",
    "    if ret:\n",
    "        if i % frame_rate_divider == 0:\n",
    "            #frame = cv2.resize(frame, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_CUBIC)\n",
    "            results = tfnet.return_predict(frame)\n",
    "\n",
    "            for color, result in zip(colors, results):\n",
    "                tl = (result['topleft']['x'], result['topleft']['y'])\n",
    "                br = (result['bottomright']['x'], result['bottomright']['y'])\n",
    "                label = result['label']\n",
    "            frame = cv2.rectangle(frame, tl, br, color, 7)\n",
    "            frame = cv2.putText(frame, label, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)\n",
    "            output.write(frame)\n",
    "            cv2.imshow('frame', frame)\n",
    "            \n",
    "            print('FPS {:.1f}'.format(1 / (time.time() - stime)))\n",
    "            i += 1\n",
    "        else:\n",
    "            i += 1\n",
    "        if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "            break\n",
    "    else:\n",
    "        break\n",
    "\n",
    "capture.release()\n",
    "output2.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  }
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