Images - python

Scan for sub-image within another image

# This is for finding the best method. The unique methods are logged with their values.
# Code for imaging is commented out at the bottom

def find_image(small_image, large_image):
    img = cv2.imread(small_image)
    img2 = img.copy()
    template = cv2.imread(large_image)
    print(template.shape[::-1])
    w, h, d = template.shape[::-1]
    # All the 6 methods for comparison in a list
    methods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR',
                'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']

    logger.info(f'Small image: {small_image}\nLarge image: {large_image}')

    for meth in methods:
        img = img2.copy()
        method = eval(meth)
        # Apply template Matching
        res = cv2.matchTemplate(img,template,method)
        min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)

        logger.info(f'\n\tMethod: {meth} \n\tMin Val: {min_val}\n\tMax Val: {max_val}\n')

        # If the method is TM_SQDIFF or TM_SQDIFF_NORMED, take minimum
        # if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]:
        #     top_left = min_loc
        # else:
        #     top_left = max_loc
        # bottom_right = (top_left[0] + w, top_left[1] + h)
        # cv2.rectangle(img,top_left, bottom_right, 255, 2)
        # plt.subplot(121),plt.imshow(res)
        # plt.title('Matching Result'), plt.xticks([]), plt.yticks([])
        # plt.subplot(122),plt.imshow(img)
        # plt.title('Detected Point'), plt.xticks([]), plt.yticks([])
        # plt.suptitle(meth)
        # plt.show()