Automatic solution for "find 10 differences in two pictures" tasks

diff_search.py

from skimage.measure import compare_ssim
import argparse
import imutils
import cv2


def are_equal(imageA, imageB):
    if imageA.shape == imageB.shape:
        difference = cv2.subtract(imageA, imageB)
        (b, g, r) = cv2.split(difference)

        if cv2.countNonZero(b) == 0 and cv2.countNonZero(g) == 0 and cv2.countNonZero(r) == 0:
            return True

        else:
            return False

    else:
        return False

def display_diffs(imageA, imageB):
    grayA = cv2.cvtColor(imageA, cv2.COLOR_BGR2GRAY)
    grayB = cv2.cvtColor(imageB, cv2.COLOR_BGR2GRAY)

    (score, diff) = compare_ssim(grayA, grayB, full=True)
    diff = (diff * 255).astype("uint8")

    threshold = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
    cnts = cv2.findContours(threshold.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    cnts = cnts[0] if imutils.is_cv2() else cnts[1]

    for c in cnts:
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(imageA, (x, y), (x + w, y + h), (0, 0, 255), 2)
        cv2.rectangle(imageB, (x, y), (x + w, y + h), (0, 0, 255), 2)

    cv2.imshow("ImageA", imageA)
    cv2.imshow("ImageB", imageB)
    cv2.waitKey(0)
    return cv2.destroyAllWindows()


if __name__ == "__main__":
    ap = argparse.ArgumentParser()
    ap.add_argument("-f", "--first", required=True, help="First image")
    ap.add_argument("-s", "--second", required=True, help="Second image")
    args = vars(ap.parse_args())

    imageA = cv2.imread(args["first"])
    imageB = cv2.imread(args["second"])

    print("Images are completely equal") if are_equal(imageA, imageB) else display_diffs(imageA, imageB)

requirements.txt

scikit-image
imutils
opencv-python