alignment.py 文件源码

def warp_image(img, triangulation, base_points, coord):
    """
    Realize the mesh warping phase

    triangulation is the Delaunay triangulation of the base points
    base_points are the coordinates of the landmark poitns of the reference image

    code inspired from http://www.learnopencv.com/warp-one-triangle-to-another-using-opencv-c-python/
    """
    all_points, coordinates = preprocess_image_before_triangulation(img)
    img_out = 255 * np.ones(img.shape, dtype=img.dtype)
    for t in triangulation:
        # triangles to map one another
        src_tri = np.array([[all_points[x][0], all_points[x][1]] for x in t]).astype(np.float32)
        dest_tri = np.array([[base_points[x][0], base_points[x][1]] for x in t]).astype(np.float32)
        # bounding boxes
        src_rect = cv2.boundingRect(np.array([src_tri]))
        dest_rect = cv2.boundingRect(np.array([dest_tri]))

        # crop images
        src_crop_tri = np.zeros((3, 2), dtype=np.float32)
        dest_crop_tri = np.zeros((3, 2))
        for k in range(0, 3):
            for dim in range(0, 2):
                src_crop_tri[k][dim] = src_tri[k][dim] - src_rect[dim]
                dest_crop_tri[k][dim] = dest_tri[k][dim] - dest_rect[dim]

        src_crop_img = img[src_rect[1]:src_rect[1] + src_rect[3], src_rect[0]:src_rect[0] + src_rect[2]]

        # affine transformation estimation
        mat = cv2.getAffineTransform(
            np.float32(src_crop_tri),
            np.float32(dest_crop_tri)
        )
        dest_crop_img = cv2.warpAffine(
            src_crop_img,
            mat,
            (dest_rect[2], dest_rect[3]),
            None,
            flags=cv2.INTER_LINEAR,
            borderMode=cv2.BORDER_REFLECT_101
        )

        # Use a mask to keep only the triangle pixels
        # Get mask by filling triangle
        mask = np.zeros((dest_rect[3], dest_rect[2], 3), dtype=np.float32)
        cv2.fillConvexPoly(mask, np.int32(dest_crop_tri), (1.0, 1.0, 1.0), 16, 0)

        # Apply mask to cropped region
        dest_crop_img = dest_crop_img * mask

        # Copy triangular region of the rectangular patch to the output image
        img_out[dest_rect[1]:dest_rect[1] + dest_rect[3], dest_rect[0]:dest_rect[0] + dest_rect[2]] = \
            img_out[dest_rect[1]:dest_rect[1] + dest_rect[3], dest_rect[0]:dest_rect[0] + dest_rect[2]] * (
                (1.0, 1.0, 1.0) - mask)

        img_out[dest_rect[1]:dest_rect[1] + dest_rect[3], dest_rect[0]:dest_rect[0] + dest_rect[2]] = \
            img_out[dest_rect[1]:dest_rect[1] + dest_rect[3], dest_rect[0]:dest_rect[0] + dest_rect[2]] + dest_crop_img

    return img_out[coord[2]:coord[3], coord[0]:coord[1]]