colour_checker_detection.detection.reformat_image#
- colour_checker_detection.detection.reformat_image(image: ArrayLike, target_width: int, interpolation_method: Literal[cv2.INTER_AREA, cv2.INTER_CUBIC, cv2.INTER_LANCZOS4, cv2.INTER_LINEAR, cv2.INTER_LINEAR_EXACT, cv2.INTER_MAX, cv2.INTER_NEAREST, cv2.INTER_NEAREST_EXACT, cv2.WARP_FILL_OUTLIERS, cv2.WARP_INVERSE_MAP] = cv2.INTER_CUBIC) NDArrayInt | NDArrayFloat [source]#
Reformat given image so that it is horizontal and resizes it to given target width.
- Parameters:
image (ArrayLike) – Image to reformat.
target_width (int) – Width the image is resized to.
interpolation_method (Literal[cv2.INTER_AREA, cv2.INTER_CUBIC, cv2.INTER_LANCZOS4, cv2.INTER_LINEAR, cv2.INTER_LINEAR_EXACT, cv2.INTER_MAX, cv2.INTER_NEAREST, cv2.INTER_NEAREST_EXACT, cv2.WARP_FILL_OUTLIERS, cv2.WARP_INVERSE_MAP]) – Interpolation method.
- Returns:
Reformatted image.
- Return type:
Examples
>>> image = np.reshape(np.arange(24), (2, 4, 3)) >>> image array([[[ 0, 1, 2], [ 3, 4, 5], [ 6, 7, 8], [ 9, 10, 11]], [[12, 13, 14], [15, 16, 17], [18, 19, 20], [21, 22, 23]]]...)
# NOTE: Need to use cv2.INTER_NEAREST_EXACT or cv2.INTER_LINEAR_EXACT # for integer images.
>>> reformat_image(image, 6, interpolation_method=cv2.INTER_LINEAR_EXACT) ... array([[[ 0, 1, 2], [ 2, 3, 4], [ 4, 5, 6], [ 5, 6, 7], [ 8, 9, 10], [ 9, 10, 11]], [[ 6, 7, 8], [ 8, 9, 10], [10, 11, 12], [12, 13, 14], [14, 15, 16], [15, 16, 17]], [[12, 13, 14], [14, 15, 16], [16, 17, 18], [17, 18, 19], [20, 21, 22], [21, 22, 23]]]...)