import cv2 as cv
import numpy as np

if __name__ == '__main__':
    boat_1 = cv.imread("../img/boat_1.jpg", cv.IMREAD_COLOR)
    boat_2 = cv.imread("../img/boat_2.jpg", cv.IMREAD_COLOR)

    boat_1_g = cv.cvtColor(boat_1, cv.COLOR_BGR2GRAY)
    boat_2_g = cv.cvtColor(boat_2, cv.COLOR_BGR2GRAY)

    orb_alg = cv.ORB_create(nfeatures=1000)

    key_points_1, descriptors_1 = orb_alg.detectAndCompute(boat_1_g, None)
    key_points_2, descriptors_2 = orb_alg.detectAndCompute(boat_2_g, None)

    matcher = cv.DescriptorMatcher_create(cv.DESCRIPTOR_MATCHER_BRUTEFORCE_HAMMING)
    matches = matcher.match(descriptors_1, descriptors_2, None)

    matches = list(matches)

    matches.sort(key=lambda x: x.distance, reverse=False)  # sort by distance

    num_good_matches = int(len(matches) * 0.05)  # save 5%
    matches = matches[:num_good_matches]

    qIdx = matches[0].queryIdx
    tIdx = matches[0].trainIdx

    point_1 = key_points_1[qIdx].pt
    point_2 = key_points_2[tIdx].pt

    print(point_1)
    print(point_2)

    cv.circle(boat_1, np.int32(point_1), 10, [0, 255, 255], -1)
    cv.circle(boat_2, np.int32(point_2), 10, [0, 255, 255], -1)

    print(boat_1.shape)
    print(boat_2.shape)

    common_area_width = boat_1.shape[1] - int(point_1[0])

    to_remove = common_area_width + int(point_2[0])

    cropped_boat_2 = boat_2[:, to_remove:boat_2.shape[1], :]

    panorama = np.concatenate((boat_1, cropped_boat_2), axis=1)
    cv.imshow('panorama', panorama)

    cv.waitKey(0)
    cv.destroyAllWindows()