chessboard.py 文件源码

def find_chessboard_corners(greyscale_image, neighborhood_size=10, candidate_threshold=.5):
    candidates = find_candidates(greyscale_image, neighborhood_size, candidate_threshold)
    bordered_image = cv2.copyMakeBorder(greyscale_image, neighborhood_size, neighborhood_size, neighborhood_size,
                                        neighborhood_size, cv2.BORDER_CONSTANT, value=0)
    detected_corners = []
    windows = []
    grad_mags = []
    templates = []
    ix_candidate = 0
    for candidate in candidates:
        print(ix_candidate)
        coord = candidate
        window = greyscale_image[coord[0] - neighborhood_size:coord[0] + neighborhood_size + 1,
                 coord[1] - neighborhood_size:coord[1] + neighborhood_size + 1]
        hist, grad_mag = __filter_candidate(bordered_image, candidate, neighborhood_size)
        win_b = cv2.copyMakeBorder(window, 5, 5, 5, 5, cv2.BORDER_CONSTANT, value=0)
        windows.append(win_b)
        grad_mags.append(prep_img_save(grad_mag))
        angles = __find_dominant_directions(hist)
        if angles is not None:
            template = __build_corner_template(neighborhood_size * 2 + 1, angles)
            templates.append(prep_img_save(template))
        else:
            templates.append(np.zeros_like(win_b))
        ix_candidate += 1
        # if __filter_candidate(bordered_image, candidate, neighborhood_size):
        #      detected_corners.append(candidate)

    ch_test = np.vstack((np.hstack(windows), np.hstack(grad_mags), np.hstack(templates)))
    cv2.imwrite("~/Desktop/TMP/ch_test01.png", ch_test)

    detected_corners = np.array(detected_corners)
    # return detected_corners

    return candidates