Align two images with only translation and rotation without scaling

edit

Is there any way that we can use while estimating the transformation? I wish the transformation has no scaling involved case I know the exact size of those images cause they are actually scanned images, which means no scaling should be involved.

here is my code:

if __name__ == "__main__":
    full_affine = False
    try_cuda = True
    match_conf = 0.3
    # finder = cv2.ORB.create()
    finder = cv2.ORB_create(scaleFactor=1.2, nlevels=1, edgeThreshold=31,
                             firstLevel=0, WTA_K=2, scoreType=cv2.ORB_HARRIS_SCORE,
                             nfeatures=100, patchSize=31)
    matcher = cv2.detail_AffineBestOf2NearestMatcher(full_affine, try_cuda, match_conf)
    source_img = cv2.imread("000001.jpg")
    target_img = cv2.imread("000000.jpg")

    source_feature = cv2.detail.computeImageFeatures2(featuresFinder=finder, image=source_img)
    target_feature = cv2.detail.computeImageFeatures2(featuresFinder=finder, image=target_img)

    source_info = load_tile_info("000001.xml", img_path, 1)
    target_info = load_tile_info("000000.xml", img_path, 0)

    matching_result = matcher.apply(source_feature, target_feature)

    print("matching_result.confidence")
    print(matching_result.confidence)
    print("matching_result.H")
    print(matching_result.H)
    print("matching_result.dst_img_idx")
    print(matching_result.dst_img_idx)
    print("matching_result.src_img_idx")
    print(matching_result.src_img_idx)

I found an answer years ago. https://answers.opencv.org/question/9...

eduardo https://answers.opencv.org/users/1644... provided an answer that setting nlevels = 1

However the output is still a transform with noticeable scaling, which leads to a wrong alignment.