29_OpticalFlow.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "## LUCAS-KANADE Optical Flow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "corner_tract_params = dict(maxCorners = 10,\n",
    "                           qualityLevel = 0.3, \n",
    "                           minDistance = 7,\n",
    "                           blockSize=7)\n",
    "\n",
    "lk_params = dict(winSize = (200, 200),\n",
    "                 maxLevel = 2,\n",
    "                 criteria = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "cap = cv2.VideoCapture(0)\n",
    "\n",
    "ret, prev_frame = cap.read()\n",
    "\n",
    "prev_gray = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "##Points to Track\n",
    "prevPts = cv2.goodFeaturesToTrack(prev_gray, mask=None, **corner_tract_params)\n",
    "\n",
    "mask = np.zeros_like(prev_frame)\n",
    "\n",
    "while True:\n",
    "    \n",
    "    ret, frame = cap.read()\n",
    "    \n",
    "    frame_gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    #LucasKanade\n",
    "    nextPts, status, err = cv2.calcOpticalFlowPyrLK(prev_gray, frame_gray, prevPts, None, **lk_params)\n",
    "    \n",
    "    good_new = nextPts[status == 1]\n",
    "    good_prev = prevPts[status == 1]\n",
    "    \n",
    "    for i, (new, prev) in enumerate(zip(good_new, good_prev)):\n",
    "        \n",
    "        x_new, y_new = new.ravel()\n",
    "        x_prev, y_prev = prev.ravel()\n",
    "        \n",
    "        mask = cv2.line(mask, (x_new, y_new), (x_prev, y_prev), (0, 255, 0), 3)\n",
    "        \n",
    "        frame = cv2.circle(frame, (x_new, y_new), 8, (0, 0, 255), 3)\n",
    "        \n",
    "    img = cv2.add(frame, mask)\n",
    "    cv2.imshow('tracking', img)\n",
    "    \n",
    "    k = cv2.waitKey(30) & 0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "        \n",
    "    prev_gray = frame_gray.copy()\n",
    "    prevPts = good_new.reshape(-1, 1, 2)\n",
    "    \n",
    "cv2.destroyAllWindows()\n",
    "cap.release()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## FARNEBACK Optical Flow\n",
    "### Coloring Points which are moving"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cap = cv2.VideoCapture(0)\n",
    "\n",
    "ret, frame1 = cap.read()\n",
    "\n",
    "prvsImg = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "hsv_mask = np.zeros_like(frame1)\n",
    "hsv_mask[:, :,1] = 255 #applying saturation values\n",
    "\n",
    "while True:\n",
    "    \n",
    "    ret, frame2 = cap.read()\n",
    "    \n",
    "    nextImg = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    flow = cv2.calcOpticalFlowFarneback(prvsImg, nextImg, None, 0.5, 3, 15, 3, 5, 1.2, 0)\n",
    "    \n",
    "    mag, ang = cv2.cartToPolar(flow[:, :, 0], flow[:, :, 1], angleInDegrees=True)\n",
    "    \n",
    "    hsv_mask[:, :, 0] = ang/2\n",
    "    \n",
    "    hsv_mask[:, :, 2] = cv2.normalize(mag, None, 255, cv2.NORM_MINMAX)\n",
    "    \n",
    "    bgr = cv2.cvtColor(hsv_mask, cv2.COLOR_HSV2BGR)\n",
    "    cv2.imshow('frame', bgr)\n",
    "    \n",
    "    k = cv2.waitKey(10) & 0xFF\n",
    "    if k == 27:\n",
    "        break\n",
    "        \n",
    "    prvsImg = nextImg\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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