Image Processing: How To Imwarp With Simple Mask On Destination?

Following my own question from 4 years ago, this time in Python only- I am looking for a way to perform texture mapping into a small region in a destination image, defined by 4 cor

Solution 1:

For future generations, here is how to only back and forward warp pixels within the bbox of the warped corner points, as @Micka suggested.

here banner is the grass image, and banner_coords_2d are the corners of the red region on image, which is meme-man.

def transform_banner(banner_coords_2d, banner, image):
    # show_points_on_image("banner corners", image, banner_coords_2d)

    banner_height, banner_width, _ = banner.shape
    src_banner_points = np.float32([
        [0, 0],
        [banner_width - 1, 0],
        [0, banner_height - 1],
        [banner_width - 1, banner_height - 1],
    ])

    # only warp to size of bbox of warped corners, not all of the image
    warped_left = np.round(np.min(banner_coords_2d[:, 0])).astype(int)
    warped_right = np.round(np.max(banner_coords_2d[:, 0])).astype(int)
    warped_top = np.round(np.min(banner_coords_2d[:, 1])).astype(int)
    warped_bottom = np.round(np.max(banner_coords_2d[:, 1])).astype(int)
    warped_width = int(warped_right - warped_left)
    warped_height = int(warped_bottom - warped_top)

    dst_banner_points = banner_coords_2d.astype(np.float32)
    dst_banner_points[:, 0] -= warped_left
    dst_banner_points[:, 1] -= warped_top

    tform = cv2.getPerspectiveTransform(src_banner_points, dst_banner_points)

    warped_banner = cv2.warpPerspective(banner, tform, (warped_width, warped_height))
    # cv2.imshow("warped_banner", warped_banner)
    image_with_banner = image.copy()
    image_with_banner[warped_top: warped_bottom, warped_left: warped_right][warped_banner != 0] = warped_banner[
        warped_banner != 0]
    # cv2.imshow("image_with_banner", image_with_banner)

    return image_with_banner

Likely, this can be done more neatly, I am open to edits.