calibration_with_mjpeg.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- record a video for about 30 seconds\n",
    "    - resolution: =, shutter speed: fastest, stabilization: turn off\n",
    "    - covering the object in different angles. \n",
    "- drag and drop the video to the exe file.\n",
    "- video -> MJPEG\n",
    "- resolution : 1920*1080\n",
    "- file format : MJPEG\n",
    "- fps: 30fps\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting Camera Matrix value from multiple images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "0 False\n",
      "1 True\n",
      "2 False\n",
      "3 False\n",
      "4 False\n",
      "5 False\n",
      "6 False\n",
      "7 False\n",
      "8 False\n",
      "9 False\n",
      "10 True\n",
      "11 False\n",
      "12 False\n",
      "13 False\n",
      "14 True\n",
      "15 False\n",
      "16 True\n",
      "17 False\n",
      "18 False\n",
      "19 False\n",
      "20 True\n",
      "21 False\n",
      "22 False\n",
      "23 False\n",
      "24\n",
      "24 False\n",
      "[[731.9983358    0.         450.94058942]\n",
      " [  0.         683.60570699 343.07428916]\n",
      " [  0.           0.           1.        ]]\n"
     ]
    }
   ],
   "source": [
    "import cv2 as cv\n",
    "import numpy as np\n",
    "import glob2 as glob\n",
    "\n",
    "# termination criteria\n",
    "criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
    "\n",
    "W=23\n",
    "L=31\n",
    "\n",
    "# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)\n",
    "objp = np.zeros((W*L, 3), np.float32)\n",
    "objp[:,:2] = np.mgrid[0:L,0:W].T.reshape(-1,2)\n",
    " \n",
    "# Arrays to store object points and image points from all the images.\n",
    "objpoints = [] # 3d point in real world space\n",
    "imgpoints = [] # 2d points in image plane.\n",
    " \n",
    "images_regex = 'images/camera_calib*.jpg'\n",
    "images = glob.glob(images_regex) # recursively retrieving files with regex\n",
    " \n",
    "for idx, fname  in enumerate(images):\n",
    "    if idx == 0 or idx == len(images) - 1: print(idx)\n",
    "    img = cv.imread(fname)\n",
    "    grayscaledimg = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\n",
    "    # cv.imshow(fname, grayscaledimg)\n",
    "    # cv.waitKey(0)\n",
    " \n",
    "    # Find the chess board corners\n",
    "    ret, corners = cv.findChessboardCorners(grayscaledimg, (31,23), None)\n",
    "    # if idx == 0 or idx == len(images) - 1: \n",
    "    print(idx, ret) # 10, 19, 22, 24, 5\n",
    "    # Question: some of the sample files returned True for the function fincChessboardCorners and some are not. \n",
    "    # -> https://stackoverflow.com/questions/66225558/cv2-findchessboardcorners-fails-to-find-corners\n",
    " \n",
    "    # If found, add object points, image points (after refining them)\n",
    "    if ret == True:\n",
    "        objpoints.append(objp)\n",
    " \n",
    "        corners2 = cv.cornerSubPix(grayscaledimg,corners, (11,11), (-1,-1), criteria)\n",
    "        imgpoints.append(corners2)\n",
    " \n",
    "        # Draw and display the corners\n",
    "        cv.drawChessboardCorners(img, (31,23), corners2, ret)\n",
    "        window_name = fname + ' outputimg'\n",
    "        cv.imshow(window_name, img)\n",
    "        # cv.waitKey(500)\n",
    "        cv.waitKey(0)\n",
    "\n",
    "ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, grayscaledimg.shape[::-1], None, None)\n",
    "print(mtx)\n",
    "#cv.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting Camera Matrix value from MP4 file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "< cv2.VideoCapture 0x7fded05f1890>\n",
      "chesssboard pattern of 50th frame has been found: True\n",
      "chesssboard pattern of 100th frame has been found: True\n",
      "chesssboard pattern of 150th frame has been found: True\n",
      "chesssboard pattern of 200th frame has been found: True\n",
      "chesssboard pattern of 250th frame has been found: True\n",
      "Fetching Frame ended in INDEX:  283\n",
      "\n",
      "Calibrating the Camera matrix and distortion coefficient\n",
      "\n",
      "Calibration is successfully done.\n",
      "Camera Matrix: \n",
      " [[453.90500549   0.         960.73601046]\n",
      " [  0.         454.8636481  537.22018238]\n",
      " [  0.           0.           1.        ]] \n",
      "\n",
      "Distortion Coefficient: \n",
      " [[-0.22884796  0.06337822  0.00028159  0.00041064 -0.00854537]] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "import cv2 as cv\n",
    "import numpy as np\n",
    "\n",
    "# termination criteria\n",
    "criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
    "\n",
    "W = 7\n",
    "L = 10 \n",
    "\n",
    "# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)\n",
    "objp = np.zeros((W*L, 3), np.float32)\n",
    "objp[:,:2] = np.mgrid[0:L, 0:W].T.reshape(-1, 2)\n",
    "\n",
    "# Arrays to store object points and image points from all the images.\n",
    "objpoints = [] # 3d point in real world space\n",
    "imgpoints = [] # 2d points in image plane.\n",
    "\n",
    "videopath = 'input/2025-02-11-111507-h-3.mp4'\n",
    "cap = cv.VideoCapture(videopath) # capturing a video file. after capturing -> can read the frames one by one.\n",
    "print(cap)\n",
    "# value of the constants: https://docs.opencv.org/4.3.0/d4/d15/group__videoio__flags__base.html ;  stored using enum. \n",
    "\n",
    "idx = 0\n",
    "while (cap.isOpened()):\n",
    "    isframeavailable, frame = cap.read()  # read the next frame of the video. \n",
    "    # print(\"Frame available exist:\", ret)\n",
    "    if isframeavailable != True:\n",
    "        print(\"Fetching Frame ended in INDEX: \", idx)\n",
    "        break\n",
    "    idx += 1\n",
    "\n",
    "    grayscaledimg = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)\n",
    "        \n",
    "    # Find the chess board corners\n",
    "    patternfound, corners = cv.findChessboardCorners(grayscaledimg, (L, W), None)\n",
    "    if idx % 50 == 0: print(f\"chesssboard pattern of {idx}th frame has been found:\", patternfound) \n",
    "\n",
    "    if patternfound:\n",
    "        objpoints.append(objp)\n",
    "    \n",
    "        corners2 = cv.cornerSubPix(grayscaledimg, corners, (11,11), (-1,-1), criteria)\n",
    "        imgpoints.append(corners2)\n",
    "    \n",
    "        # Draw and display the corners\n",
    "        cv.drawChessboardCorners(frame, (L, W), corners2, patternfound)\n",
    "\n",
    "print(\"\\nCalibrating the Camera matrix and distortion coefficient\\n\")\n",
    "iscalibrated, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, grayscaledimg.shape[::-1], None, None)\n",
    "\n",
    "if iscalibrated:\n",
    "    print(\"Calibration is successfully done.\")\n",
    "    print(\"Camera Matrix: \\n\", mtx, \"\\n\")\n",
    "    print(\"Distortion Coefficient: \\n\", dist, \"\\n\")\n",
    "else:\n",
    "    print(\"Calibration failed\")\n",
    "\n",
    "cap.release() # closing a video file\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "chesssboard pattern of 50th frame has been found: True\n",
      "chesssboard pattern of 100th frame has been found: True\n",
      "chesssboard pattern of 150th frame has been found: True\n",
      "chesssboard pattern of 200th frame has been found: True\n",
      "chesssboard pattern of 250th frame has been found: True\n",
      "Fetching Frame ended in INDEX:  283\n",
      "\n",
      "Calibrating the Camera matrix and distortion coefficient\n",
      "\n",
      "Calibration is successfully done.\n",
      "Camera Matrix: \n",
      " [[453.90500549   0.         960.73601046]\n",
      " [  0.         454.8636481  537.22018238]\n",
      " [  0.           0.           1.        ]] \n",
      "\n",
      "Distortion Coefficient: \n",
      " [[-0.22884796  0.06337822  0.00028159  0.00041064 -0.00854537]] \n",
      "\n"
     ]
    }
   ],
   "source": [
    "import cv2 as cv\n",
    "import numpy as np\n",
    "\n",
    "termiation_criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)\n",
    "\n",
    "chessboard_width = 7\n",
    "chessboard_length = 10 \n",
    "\n",
    "objp = np.zeros((chessboard_width * chessboard_length, 3), np.float32)\n",
    "objp[:,:2] = np.mgrid[0:chessboard_length, 0:chessboard_width].T.reshape(-1, 2)\n",
    "\n",
    "realworldpoints = []\n",
    "imgpoints = []\n",
    "\n",
    "videofilename = \"2025-02-11-111507-h-3.mp4\"\n",
    "videopath = f'input/{videofilename}'\n",
    "cap = cv.VideoCapture(videopath)\n",
    "if not cap:\n",
    "    print(\"Error occured while instantiating Video Capture\")\n",
    "\n",
    "idx = 0\n",
    "while (cap.isOpened()):\n",
    "    isframeavailable, frame = cap.read()\n",
    "\n",
    "    if isframeavailable != True:\n",
    "        print(\"Fetching Frame ended in INDEX: \", idx)\n",
    "        break\n",
    "    idx += 1\n",
    "\n",
    "    grayscaledimg = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)\n",
    "    \n",
    "    patternfound, corners = cv.findChessboardCorners(grayscaledimg, (chessboard_length, chessboard_width), None)\n",
    "    if idx % 50 == 0: print(f\"chesssboard pattern of {idx}th frame has been found:\", patternfound) \n",
    "\n",
    "    if patternfound:\n",
    "        realworldpoints.append(objp)\n",
    "    \n",
    "        corners2 = cv.cornerSubPix(grayscaledimg, corners, (11,11), (-1,-1), termiation_criteria)\n",
    "        imgpoints.append(corners2)\n",
    "\n",
    "        cv.drawChessboardCorners(frame, (chessboard_length, chessboard_width), corners2, patternfound)\n",
    "\n",
    "print(\"\\nCalibrating the Camera matrix and distortion coefficient\\n\")\n",
    "iscalibrated, mtx, dist, rvecs, tvecs = cv.calibrateCamera(realworldpoints, imgpoints, grayscaledimg.shape[::-1], None, None)\n",
    "\n",
    "if iscalibrated:\n",
    "    print(\"Calibration is successfully done.\")\n",
    "    print(\"Camera Matrix: \\n\", mtx, \"\\n\")\n",
    "    print(\"Distortion Coefficient: \\n\", dist, \"\\n\")\n",
    "else:\n",
    "    print(\"Calibration failed\")\n",
    "\n",
    "cap.release()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}