opt_v1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "\n",
    "# Set up the camera capture\n",
    "cap = cv2.VideoCapture('sample_video.mp4')\n",
    "\n",
    "# Create a Lucas-Kanade optical flow object\n",
    "lk_params = dict(winSize=(15, 15), maxLevel=2, criteria=(cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 0.03))\n",
    "\n",
    "# Initialize variables\n",
    "old_frame = None\n",
    "old_gray = None\n",
    "p0 = None\n",
    "\n",
    "#defining Saving parameters\n",
    "fps = cap.get(cv2.CAP_PROP_FPS)\n",
    "w = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))\n",
    "h = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))\n",
    "out = cv2.VideoWriter('Final_sparse.avi', cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))\n",
    "\n",
    "while True:\n",
    "    # Capture a frame from the camera\n",
    "    ret, frame = cap.read()\n",
    "    if not ret:\n",
    "        break\n",
    "\n",
    "    # Convert the frame to grayscale\n",
    "    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "    if old_frame is None:\n",
    "        # If this is the first frame, initialize the variables\n",
    "        old_frame = frame\n",
    "        old_gray = gray\n",
    "        p0 = cv2.goodFeaturesToTrack(old_gray, maxCorners=100, qualityLevel=0.3, minDistance=7)\n",
    "        mask = np.zeros_like(old_frame)\n",
    "\n",
    "    else:\n",
    "        # Calculate optical flow using Lucas-Kanade method\n",
    "        p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, gray, p0, None, **lk_params)\n",
    "\n",
    "        # Select only the good points\n",
    "        good_new = p1[st == 1]\n",
    "        good_old = p0[st == 1]\n",
    "\n",
    "        # Draw the movement vectors\n",
    "        if len(good_new) > 0 and len(good_old) > 0:\n",
    "            for i, (new, old) in enumerate(zip(good_new, good_old)):\n",
    "                a, b = new.ravel()\n",
    "                c, d = old.ravel()\n",
    "                mask = cv2.line(mask, (int(a), int(b)), (int(c), int(d)), (0, 255, 0), 2)\n",
    "                frame = cv2.circle(frame, (int(a), int(b)), 5, (0, 0, 255), -1)\n",
    "\n",
    "            # Display the resulting image\n",
    "            img = cv2.add(frame, mask)\n",
    "            cv2.imshow('frame', img)\n",
    "\n",
    "            # Update the previous frame and previous points\n",
    "            old_gray = gray.copy()\n",
    "            p0 = good_new.reshape(-1, 1, 2)\n",
    "\n",
    "            #writing the file\n",
    "            out.write(img)\n",
    "\n",
    "    # Wait for key press and break if 'q' is pressed\n",
    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "# Release the capture and close the window\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "cap.release()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}