OpenCV Calibration Script

cv_length_calibrate.py

# import the opencv library
import cv2
import numpy as np
  
  
# define a video capture object (continuinity camera)
vid = cv2.VideoCapture(1)

# Define the dimensions of checkerboard
CHECKERBOARD = (6, 9)

# stop the iteration when specified
# accuracy, epsilon, is reached or
# specified number of iterations are completed.
criteria = (cv2.TERM_CRITERIA_EPS +
            cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)


# Vector for 3D points
threedpoints = []
 
# Vector for 2D points
twodpoints = []
 
 
#  3D points real world coordinates
objectp3d = np.zeros((1, CHECKERBOARD[0]
                      * CHECKERBOARD[1],
                      3), np.float32)
objectp3d[0, :, :2] = np.mgrid[0:CHECKERBOARD[0],
                               0:CHECKERBOARD[1]].T.reshape(-1, 2)
prev_img_shape = None

  
while(True):
      
    # Capture the video frame
    # by frame
    ret, frame = vid.read()
    image = frame

    if not ret:
        print("Skipping")
        continue

    grayColor = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    print("Iteration")

    # cv2.imshow('img', grayColor)
    # cv2.waitKey(1)
    # continue

 
    # Find the chess board corners
    # If desired number of corners are
    # found in the image then ret = true
    ret, corners = cv2.findChessboardCorners(
                    grayColor, CHECKERBOARD,
                    cv2.CALIB_CB_ADAPTIVE_THRESH
                    + cv2.CALIB_CB_FAST_CHECK +
                    cv2.CALIB_CB_NORMALIZE_IMAGE)
 
    # If desired number of corners can be detected then,
    # refine the pixel coordinates and display
    # them on the images of checker board
    if ret == True:
        print("Return is TRUE")

        threedpoints.append(objectp3d)
 
        # Refining pixel coordinates
        # for given 2d points.
        corners2 = cv2.cornerSubPix(
            grayColor, corners, (11, 11), (-1, -1), criteria)
 
        twodpoints.append(corners2)
 
        # Draw and display the corners
        image = cv2.drawChessboardCorners(image,
                                          CHECKERBOARD,
                                          corners2, ret)
 
    cv2.imshow('img', image)
    key = cv2.waitKey(1) & 0xFF
    if key == ord('q'):
        break



# After the loop release the cap object
vid.release()
cv2.destroyAllWindows()


h, w = image.shape[:2]
 
# Perform camera calibration by
# passing the value of above found out 3D points (threedpoints)
# and its corresponding pixel coordinates of the
# detected corners (twodpoints)
ret, matrix, distortion, r_vecs, t_vecs = cv2.calibrateCamera(
    threedpoints, twodpoints, grayColor.shape[::-1], None, None)
 
 
# Displaying required output
print(" Camera matrix:")
print(matrix.tolist())
 
print("\n Distortion coefficient:")
print(distortion.tolist())

# import pdb; pdb.set_trace()

# print("\n Rotation Vectors:")
# print(r_vecs)
 
# print("\n Translation Vectors:")
# print(t_vecs)