calib

calib.py

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+import cv2
+
+retval, corners = cv2.findChessboardCorners(image,patternSize, flags)
+
+import cv2
+import numpy as np
+
+# Define the size of the chessboard
+chessboard_size = (22, 16)
+
+# Define the object points of the chessboard
+object_points = np.zeros((np.prod(chessboard_size), 3), dtype=np.float32)
+object_points[:, :2] = np.mgrid[0:chessboard_size[0], 0:chessboard_size[1]].T.reshape(-1, 2)
+
+# Create arrays to store the object points and image points from all the images
+object_points_array = []
+image_points_array = []
+
+# Load the images
+images = []
+images.append(cv2.imread("image1.jpg"))
+images.append(cv2.imread("image2.jpg"))
+# Add more images as needed
+
+# Loop through each image and find the chessboard corners
+for image in images:
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Find the chessboard corners
+    found, corners = cv2.findChessboardCorners(gray, chessboard_size, None)
+
+    # If the corners are found, add the object points and image points to the arrays
+    if found:
+        object_points_array.append(object_points)
+        image_points_array.append(corners)
+
+# Calibrate the camera using the object points and image points
+ret, camera_matrix, distortion_coefficients, rotation_vectors, translation_vectors = cv2.calibrateCamera(
+    object_points_array, image_points_array, gray.shape[::-1], None, None)
+
+# Print the camera matrix and distortion coefficients
+print("Camera matrix:")
+print(camera_matrix)
+print("Distortion coefficients:")
+print(distortion_coefficients)