def warp_image_to_bounding_box()

in src/co_op_translator/utils/vision/image_utils.py [0:0]

• 15 lines of code
• 2 McCabe index (conditional complexity)

def warp_image_to_bounding_box(text_img_array, bounding_box, image_width, image_height):
    """
    Apply a perspective warp to a text image so it fits a (possibly rotated)
    bounding box. The text image is first resized to the rectangle defined by
    the bounding box geometry, then warped.
    """
    pts = np.array(bounding_box, dtype=np.float32).reshape(4, 2)
    # Compute destination width and height.
    widthA = np.linalg.norm(pts[0] - pts[1])
    widthB = np.linalg.norm(pts[2] - pts[3])
    maxWidth = max(int(widthA), int(widthB))
    heightA = np.linalg.norm(pts[0] - pts[3])
    heightB = np.linalg.norm(pts[1] - pts[2])
    maxHeight = max(int(heightA), int(heightB))
    src_pts = np.float32([[0, 0], [maxWidth, 0], [maxWidth, maxHeight], [0, maxHeight]])
    # Resize the padded text image to the computed rectangle.
    resized_text = cv2.resize(text_img_array, (maxWidth, maxHeight))
    matrix = cv2.getPerspectiveTransform(src_pts, pts)
    warped = cv2.warpPerspective(
        resized_text, matrix, (image_width, image_height), flags=cv2.INTER_LINEAR
    )
    return warped