cv2.error: OpenCV(4.8.1) error: (-215:Assertion failed) nimages > 0 in function 'cv::calibrateCameraRO'

Question

So i want to do calibration with the below image :enter image description here and i encounter this error : ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], camera_matrix, None, flags=cv2.CALIB_USE_INTRINSIC_GUESS) cv2.error: OpenCV(4.8.1) D:\a\opencv-python\opencv-python\opencv\modules\calib3d\src\calibration.cpp:3752: error: (-215:Assertion failed) nimages > 0 in function 'cv::calibrateCameraRO' and my ret in this line of code ret, corners = cv2.findChessboardCorners(gray, (5,5), None) is always False so i changed the (5*5) and put it different number.

and this is my code :

import numpy as np
import cv2
import glob
import scipy.io



# Termination criteria
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

# Prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0)
objp = np.zeros((6*7, 3), np.float32)
objp[:, :2] = np.mgrid[0:7, 0:6].T.reshape(-1, 2)

# Arrays to store object points and image points from all the images.
objpoints = []  # 3d point in real-world space
imgpoints = []  # 2d points in image plane.

images = glob.glob('4/Cube_images/*.jpg')
  
for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # Find the chessboard corners
    ret, corners = cv2.findChessboardCorners(gray, (5,5), None)

    print(ret)
    # If found, add object points, image points (after refining them)
    if ret == True:
        objpoints.append(objp)
        print(objpoints)
        corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)
        imgpoints.append(corners2)
        print(imgpoints)

        # Draw and display the corners
        img = cv2.drawChessboardCorners(img, (5, 5), corners2, ret)
        cv2.imshow('img', img)
        cv2.waitKey(500)

cv2.destroyAllWindows()

# Estimate initial camera matrix using the aspect ratio
aspect_ratio = 1  # You might need to adjust this based on your camera
focal_length = 1  # Some initial guess for the focal length

# Estimate principal point (center) of the image
center = (0,0)

camera_matrix = np.array([[focal_length, 0, center[0]],
                          [0, focal_length, center[1]],
                          [0, 0, 1]])
# Camera calibration
ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], camera_matrix, None,  flags=cv2.CALIB_USE_INTRINSIC_GUESS)

# Extract focal length from the camera matrix
focal_length_x = mtx[0, 0]
focal_length_y = mtx[1, 1]

# Print the camera matrix and distortion coefficients
print("Camera Matrix:")
print(mtx)
print("\nDistortion Coefficients:")
print(dist)
print("\nFocal Length (fx):", focal_length_x)
print("Focal Length (fy):", focal_length_y)


mean_error = 0
tot_error = 0

for i in range(len(objpoints)):
    imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
    error = cv2.norm(imgpoints[i], imgpoints2, cv2.NORM_L2) / len(imgpoints2)
    tot_error += error

a = tot_error/len(objpoints)
print(a)```


i have to do the calibration and find the focal length and fix this issue.