Uploading Google Colabs for CV

Author: atan333

Camera Calibration

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+{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":19050,"status":"ok","timestamp":1729115744332,"user":{"displayName":"Benjamin Saenz","userId":"01005784200202624626"},"user_tz":240},"id":"KF29PaJcy7mi","outputId":"bc6cce21-22c3-46e4-faf3-fe383040bf9c"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mounted at /content/drive\n"]}],"source":["# Code taken from OpenCV's Camera Calibration Doc\n","from google.colab import drive\n","drive.mount('/content/drive')\n","import numpy as np\n","import cv2 as cv\n","import glob\n","import matplotlib.pyplot as plt\n","from google.colab.patches import cv2_imshow"]},{"cell_type":"code","execution_count":2,"metadata":{"executionInfo":{"elapsed":6,"status":"ok","timestamp":1729115744333,"user":{"displayName":"Benjamin Saenz","userId":"01005784200202624626"},"user_tz":240},"id":"x84d8dZDKCbe"},"outputs":[],"source":["# termination criteria\n","criteria = (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)"]},{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":5,"status":"ok","timestamp":1729115744333,"user":{"displayName":"Benjamin Saenz","userId":"01005784200202624626"},"user_tz":240},"id":"BEUAP3syKEpn"},"outputs":[],"source":["# prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)\n","objp = np.zeros((6*8,3), np.float32)\n","objp[:,:2] = np.mgrid[0:8,0:6].T.reshape(-1,2)"]},{"cell_type":"code","execution_count":4,"metadata":{"executionInfo":{"elapsed":2501,"status":"ok","timestamp":1729115746829,"user":{"displayName":"Benjamin Saenz","userId":"01005784200202624626"},"user_tz":240},"id":"yNZsWWmiL0JY"},"outputs":[],"source":["# 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","file_path = '/content/drive/MyDrive/Umd/Activities/UMD Loop/Integration CV/Images/calibration_images/*.png'\n","images = glob.glob(file_path)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true,"base_uri":"https://localhost:8080/","height":1000,"output_embedded_package_id":"18WJMkpB4VWIHCvD6bWnibXTIIQnfkYjo"},"id":"9Wj9zLxc4oR0","outputId":"e6356b57-dcb4-4392-ae50-84d29844a7af"},"outputs":[],"source":["# iterate over the images\n","for fname in images:\n","\n","    img = cv.imread(fname)\n","    gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)\n","\n","    # Find the chess board corners\n","    ret, corners = cv.findChessboardCorners(gray, (8,6), None)\n","\n","    # print(corners) if ret else print(\"Unable to detect corners\")\n","\n","    # If found, add object points, image points (after refining them)\n","    if ret:\n","        objpoints.append(objp)\n","\n","        corners2 = cv.cornerSubPix(gray,corners, (11,11), (-1,-1), criteria)\n","        imgpoints.append(corners2)\n","\n","        # Draw and display the corners\n","        cv.drawChessboardCorners(img, (8,6), corners2, ret)\n","        cv2_imshow(img)\n","        cv.waitKey(500)\n","\n","cv.destroyAllWindows()"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true},"id":"-znon8hLfboY"},"outputs":[],"source":["\n","ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], cv.CALIB_USE_LU, None)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true},"id":"8idDxAFTgDyz"},"outputs":[{"data":{"text/plain":["array([[1.27603955e+03, 0.00000000e+00, 9.10947475e+02],\n","       [0.00000000e+00, 1.27661564e+03, 6.22502946e+02],\n","       [0.00000000e+00, 0.00000000e+00, 1.00000000e+00]])"]},"execution_count":7,"metadata":{},"output_type":"execute_result"}],"source":["mtx"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true},"id":"_Lo8uFwnZ3CU"},"outputs":[{"name":"stdout","output_type":"stream","text":["total error: 0.0642139962691941\n"]}],"source":["mean_error = 0\n","for i in range(len(objpoints)):\n","    imgpoints2, _ = cv.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)\n","    error = cv.norm(imgpoints[i], imgpoints2, cv.NORM_L2)/len(imgpoints2)\n","    mean_error += error\n","\n","print( \"total error: {}\".format(mean_error/len(objpoints)) )"]}],"metadata":{"colab":{"name":"","version":""},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}

Depth (ORB).ipynb

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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyOSfmmaFTprygNBN47q/vPJ"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"ad7kGErMLEWs"},"outputs":[],"source":["#include <sl/zed/Camera.hpp>\n","\n","\n","\n","// ... Initialize your ZED camera\n","\n","sl::Camera zed;\n","\n","\n","\n","// Access calibration parameters\n","\n","sl::CalibrationParameters calibration_params = zed.getCameraInformation().calibration_parameters;\n","\n","\n","\n","// Access intrinsic matrix values\n","\n","float fx = calibration_params.left_camera.fx;\n","\n","float fy = calibration_params.left_camera.fy;\n","\n","float cx = calibration_params.left_camera.cx;\n","\n","float cy = calibration_params.left_camera.cy;"]}]}