Lecture 6.3 - Mini Project # 6 - Car & Pedestrian Detection.ipynb

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    "## Mini Project # 6 - Car & Pedestrian Detection\n",
    "\n",
    "**NOTE** \n",
    "- If no video loads after running code, you may need to copy your *opencv_ffmpeg.dll* \n",
    "- From: *C:\\opencv2413\\opencv\\sources\\3rdparty\\ffmpeg*\n",
    "- To: Where your python is installed e.g. *C:\\Anaconda2\\* \\\n",
    "- Once it's copied you'll need to rename the file according to the version of OpenCV you're using.\n",
    "- e.g. if you're using OpenCV 2.4.13 then rename the file as:\n",
    "- **opencv_ffmpeg2413_64.dll** or opencv_ffmpeg2413.dll (if you're using an X86 machine)\n",
    "- **opencv_ffmpeg310_64.dll** or opencv_ffmpeg310.dll (if you're using an X86 machine)\n",
    "\n",
    "To find out where you python.exe is installed, just run these two lines of code:"
   ]
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   "execution_count": 1,
   "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C:\\Users\\soura\\Anaconda2\\python.exe\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "print(sys.executable)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pedistrian Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "body_classifier = cv2.CascadeClassifier('Haarcascades/haarcascade_fullbody.xml')\n",
    "\n",
    "cap = cv2.VideoCapture('images/walking.avi')\n",
    "\n",
    "while cap.isOpened():\n",
    "    \n",
    "    time.sleep(0.03)\n",
    "    ret, frame = cap.read()\n",
    "    \n",
    "    frame = cv2.resize(frame, None,fx=0.5, fy=0.5, interpolation = cv2.INTER_LINEAR)\n",
    "    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    bodies = body_classifier.detectMultiScale(gray, 1.2, 3)\n",
    "    \n",
    "    for (x,y,w,h) in bodies:\n",
    "        cv2.rectangle(frame, (x,y), (x+w, y+h), (0,255,0), 2)\n",
    "        cv2.imshow('frame', frame)\n",
    "    \n",
    "    if cv2.waitKey(1) == 13:\n",
    "        break\n",
    "        \n",
    "cap.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Car Detection\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "works\n"
     ]
    },
    {
     "ename": "error",
     "evalue": "C:\\build\\2_4_winpack-bindings-win64-vc14-static\\opencv\\modules\\imgproc\\src\\color.cpp:3783: error: (-215) scn == 3 || scn == 4 in function cv::cvtColor\n",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31merror\u001b[0m                                     Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-f8b9ff20e14f>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m     14\u001b[0m     \u001b[0mret\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mframe\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcap\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 16\u001b[1;33m     \u001b[0mgray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcvtColor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mframe\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCOLOR_BGR2GRAY\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     17\u001b[0m     \u001b[0mcars\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcar_classifier\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdetectMultiScale\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mgray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m1.05\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     18\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31merror\u001b[0m: C:\\build\\2_4_winpack-bindings-win64-vc14-static\\opencv\\modules\\imgproc\\src\\color.cpp:3783: error: (-215) scn == 3 || scn == 4 in function cv::cvtColor\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "car_classifier = cv2.CascadeClassifier('Haarcascades\\haarcascade_car.xml')\n",
    "\n",
    "cap = cv2.VideoCapture('images/cars.avi')\n",
    "\n",
    "print 'works'\n",
    "\n",
    "while cap.isOpened():\n",
    "    time.sleep(0.03)\n",
    "    ret,frame = cap.read()\n",
    "    \n",
    "    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "    cars = car_classifier.detectMultiScale(gray, 1.05, 3)\n",
    "    \n",
    "    for (x,y,w,h) in cars:\n",
    "        cv2.rectangle(frame, (x,y), (x+w, y+h), (0,255,0),3)\n",
    "        cv2.imshow('frame', frame)\n",
    "        \n",
    "    if cv2.waitKey(1) ==13:\n",
    "        break\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **Full Body / Pedestrian Classifier ** - https://github.com/opencv/opencv/blob/master/data/haarcascades/haarcascade_fullbody.xml\n",
    "- **Car Classifier ** - http://www.codeforge.com/read/241845/cars3.xml__html\n"
   ]
  }
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