image_orient.py

import numpy as np
import cv2
import matplotlib.pyplot as plt
import glob


# 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) # 42 rows of 3 elemnts (columns), all zeros

#print(objp)
objp[:,:2] = np.mgrid[0:7,0:6].T.reshape(-1,2) #transpose then reshape to 2 cols 
# then set vals to 0-7, 0-6, and set first two columns of original matrix to that

print(objp)


# 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('img/*.JPG')
print(images)

for fname in images:
    img = cv2.imread(fname)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    # Find the chess board corners
    ret, corners = cv2.findChessboardCorners(gray, (7,6), None)

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

        # # Draw and display the corners
        # cv2.drawChessboardCorners(img, (7,6), corners2, ret)
        # cv2.imshow('img', img)
        # cv2.waitKey(500)

cv2.destroyAllWindows()