Fresh_start_with_optical_flow.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import cv2\n",
    "import time\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Working on  Lucas Kanade Optical Flow Estimation\n",
    "## Working on Video (Not Successful)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(400, 300, 3)\n",
      "all: [[[ 32.  46.]]\n",
      "\n",
      " [[ 38.  34.]]\n",
      "\n",
      " [[ 27.  34.]]\n",
      "\n",
      " [[ 22.  46.]]]\n",
      "just this:\n",
      "32.0 46.0\n",
      "just this:\n",
      "38.0 34.0\n",
      "just this:\n",
      "27.0 34.0\n",
      "just this:\n",
      "22.0 46.0\n",
      "<class 'numpy.ndarray'>\n"
     ]
    },
    {
     "ename": "error",
     "evalue": "OpenCV(4.1.0) C:\\projects\\opencv-python\\opencv\\modules\\video\\src\\lkpyramid.cpp:1229: error: (-215:Assertion failed) (npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0 in function 'cv::`anonymous-namespace'::SparsePyrLKOpticalFlowImpl::calc'\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-1-6f1831e3ad44>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     63\u001b[0m     \u001b[0mframe_grey\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[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     64\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 65\u001b[1;33m     \u001b[0mp1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mstatus\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalcOpticalFlowPyrLK\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mold_grey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mframe_grey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mp0\u001b[0m \u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mlk_params\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     66\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"p1:\"\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mp1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     67\u001b[0m     \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"p0\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mp0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31merror\u001b[0m: OpenCV(4.1.0) C:\\projects\\opencv-python\\opencv\\modules\\video\\src\\lkpyramid.cpp:1229: error: (-215:Assertion failed) (npoints = prevPtsMat.checkVector(2, CV_32F, true)) >= 0 in function 'cv::`anonymous-namespace'::SparsePyrLKOpticalFlowImpl::calc'\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import cv2\n",
    "import time\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "cap = cv2.VideoCapture(r'C:\\Users\\Legion\\Downloads\\vid.mp4')\n",
    "\n",
    "feature_params = dict( maxCorners = 100,\n",
    "                     qualityLevel = 0.1,\n",
    "                     minDistance = 10,\n",
    "                     blockSize = 7,\n",
    "                     useHarrisDetector = True)\n",
    "\n",
    "lk_params = dict(winSize =(15,15),\n",
    "                maxLevel = 2,\n",
    "                criteria = (cv2.TERM_CRITERIA_EPS| cv2.TERM_CRITERIA_COUNT, 10,0.03))\n",
    "\n",
    "\n",
    "color = np.random.randint(0, 255, (100, 3))\n",
    "\n",
    "ret, old_frame = cap.read()\n",
    "old_frame = cv2.resize(old_frame, (300, 400))\n",
    "old_grey = cv2.cvtColor(old_frame, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "print(old_frame.shape)\n",
    "p0 = cv2.goodFeaturesToTrack(old_grey, mask = None, **feature_params)\n",
    "\n",
    "print(\"all:\",p0)\n",
    "\n",
    "for p in p0:\n",
    "    print('just this:')\n",
    "    print(p[0][0], p[0][1])\n",
    "\n",
    "\n",
    "mask = np.zeros_like(old_frame)\n",
    "mask2 = np.zeros_like(old_frame)\n",
    "\n",
    "#cap.release()\n",
    "'''\n",
    "for p in p0:\n",
    "    x, y = p.ravel()\n",
    "    mask2 = cv2.circle(mask2, (x,y), 5, (0,255,0),-1)\n",
    "    \n",
    "cv2.imshow('frame,' , old_frame)\n",
    "cv2.imshow('grey', old_grey)\n",
    "cv2.imshow('w', mask2)\n",
    "cv2.waitKey(0)\n",
    "cv2.destroyAllWindows()\n",
    "'''\n",
    "\n",
    "#'''\n",
    "\n",
    "p0 = np.array([[[100., 60.]]])\n",
    "print(type(p0))\n",
    "while(1):\n",
    "    \n",
    "    ret, frame = cap.read()\n",
    "    \n",
    "    if ret ==0:\n",
    "        break\n",
    "    frame = cv2.resize(frame, (300, 400))\n",
    "    frame_grey = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "    \n",
    "    p1, status, err = cv2.calcOpticalFlowPyrLK(old_grey, frame_grey, p0 , None, **lk_params)\n",
    "    print(\"p1:\",p1)\n",
    "    print(\"p0\", p0)\n",
    "    print('-------------------')\n",
    "    \n",
    "    \n",
    "    good_new = p1[status == 1]\n",
    "    good_old = p1[status == 1]\n",
    "    \n",
    "    \n",
    "    print(\"good new p1:\",good_new)\n",
    "    print(\"good old p0\", good_old)\n",
    "    print('-------------------')\n",
    "    \n",
    "    for idx,(new_pt, old_pt) in enumerate(zip(good_new, good_old)):\n",
    "        \n",
    "        a, b = new_pt.ravel()\n",
    "        c, d = old_pt.ravel()\n",
    "        \n",
    "        mask = cv2.line(mask, (a,b), (c,d), color[idx].tolist(),2)\n",
    "        mask2 = cv2.circle(mask2, (a,b), 5, (0, 255, 0), 1)\n",
    "        \n",
    "    img = cv2.add(frame, mask)\n",
    "    \n",
    "    cv2.imshow('frame', img)\n",
    "    cv2.imshow('mask', mask)\n",
    "    cv2.imshow('mask2', mask2)\n",
    "    k = cv2.waitKey(1) & 0xff\n",
    "    \n",
    "    if k == ord('q'):\n",
    "        break\n",
    "    \n",
    "    old_grey = frame_grey.copy()\n",
    "    p0 = good_new.reshape(-1,1,2)\n",
    "    print(\"shape of p0 before,before p0\",p0.shape,p0)\n",
    "    #any new features found\n",
    "    new_track_pts = cv2.goodFeaturesToTrack(frame_grey, mask = None, **feature_params)\n",
    "    print(\"shape of new pts and new pts\",new_track_pts.shape,new_track_pts)\n",
    "    \n",
    "    #appending the pts at last\n",
    "    p0 = np.concatenate((p0, new_track_pts))\n",
    "    \n",
    "    print(\"final shape p0,final p0:\",p0.shape,p0)\n",
    "        \n",
    "cv2.destroyAllWindows()\n",
    "cap.release()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2.cuda"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "USAGE: opt_flow.py [<video_source>]\n",
      "\n",
      "Keys:\n",
      " 1 - toggle HSV flow visualization\n",
      " 2 - toggle glitch\n",
      "\n",
      "\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "Required argument 'flags' (pos 10) not found",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-25-7c4252d537e2>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m     61\u001b[0m         \u001b[0mret\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mimg\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcam\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[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     62\u001b[0m         \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[0mimg\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[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 63\u001b[1;33m         \u001b[0mflow\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcv2\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcalcOpticalFlowFarneback\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprevgray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mgray\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0.5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m15\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m5\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1.2\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     64\u001b[0m         \u001b[0mprevgray\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgray\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     65\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mTypeError\u001b[0m: Required argument 'flags' (pos 10) not found"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "import numpy as np\n",
    "import cv2\n",
    "\n",
    "\n",
    "help_message = '''\n",
    "USAGE: opt_flow.py [<video_source>]\n",
    "\n",
    "Keys:\n",
    " 1 - toggle HSV flow visualization\n",
    " 2 - toggle glitch\n",
    "\n",
    "'''\n",
    "\n",
    "def draw_flow(img, flow, step=16):\n",
    "    h, w = img.shape[:2]\n",
    "    y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1)\n",
    "    fx, fy = flow[y,x].T\n",
    "    lines = np.vstack([x, y, x+fx, y+fy]).T.reshape(-1, 2, 2)\n",
    "    lines = np.int32(lines + 0.5)\n",
    "    vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)\n",
    "    cv2.polylines(vis, lines, 0, (0, 255, 0))\n",
    "    for (x1, y1), (x2, y2) in lines:\n",
    "        cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)\n",
    "    return vis\n",
    "\n",
    "def draw_hsv(flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    fx, fy = flow[:,:,0], flow[:,:,1]\n",
    "    ang = np.arctan2(fy, fx) + np.pi\n",
    "    v = np.sqrt(fx*fx+fy*fy)\n",
    "    hsv = np.zeros((h, w, 3), np.uint8)\n",
    "    hsv[...,0] = ang*(180/np.pi/2)\n",
    "    hsv[...,1] = 255\n",
    "    hsv[...,2] = np.minimum(v*4, 255)\n",
    "    bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)\n",
    "    return bgr\n",
    "\n",
    "def warp_flow(img, flow):\n",
    "    h, w = flow.shape[:2]\n",
    "    flow = -flow\n",
    "    flow[:,:,0] += np.arange(w)\n",
    "    flow[:,:,1] += np.arange(h)[:,np.newaxis]\n",
    "    res = cv2.remap(img, flow, None, cv2.INTER_LINEAR)\n",
    "    return res\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    import sys\n",
    "    print(help_message)\n",
    "    \n",
    "    \n",
    "    cam = cv2.VideoCapture(r'C:\\Users\\Legion\\Downloads\\vid.mp4')\n",
    "    ret, prev = cam.read()\n",
    "    prevgray = cv2.cvtColor(prev, cv2.COLOR_BGR2GRAY)\n",
    "    show_hsv = False\n",
    "    show_glitch = False\n",
    "    cur_glitch = prev.copy()\n",
    "\n",
    "    while True:\n",
    "        ret, img = cam.read()\n",
    "        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
    "        flow = cv2.calcOpticalFlowFarneback(prevgray, gray, 0.5, 3, 15, 3, 5, int(1.2), 0)\n",
    "        prevgray = gray\n",
    "\n",
    "        cv2.imshow('flow', draw_flow(gray, flow))\n",
    "        if show_hsv:\n",
    "            cv2.imshow('flow HSV', draw_hsv(flow))\n",
    "        if show_glitch:\n",
    "            cur_glitch = warp_flow(cur_glitch, flow)\n",
    "            cv2.imshow('glitch', cur_glitch)\n",
    "\n",
    "        ch = 0xFF & cv2.waitKey(5)\n",
    "        if ch == 27:\n",
    "            break\n",
    "        if ch == ord('1'):\n",
    "            show_hsv = not show_hsv\n",
    "            print('HSV flow visualization is', ['off', 'on'][show_hsv])\n",
    "        if ch == ord('2'):\n",
    "            show_glitch = not show_glitch\n",
    "            if show_glitch:\n",
    "                cur_glitch = img.copy()\n",
    "            print('glitch is', ['off', 'on'][show_glitch])\n",
    "    cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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