def __call__()

in src/controlnet_aux/shuffle/__init__.py [0:0]

• 29 lines of code
• 10 McCabe index (conditional complexity)

    def __call__(self, input_image, h=None, w=None, f=None, detect_resolution=512, image_resolution=512, output_type="pil", **kwargs):
        if "return_pil" in kwargs:
            warnings.warn("return_pil is deprecated. Use output_type instead.", DeprecationWarning)
            output_type = "pil" if kwargs["return_pil"] else "np"
        if type(output_type) is bool:
            warnings.warn("Passing `True` or `False` to `output_type` is deprecated and will raise an error in future versions")
            if output_type:
                output_type = "pil"

        if not isinstance(input_image, np.ndarray):
            input_image = np.array(input_image, dtype=np.uint8)

        input_image = HWC3(input_image)
        input_image = resize_image(input_image, detect_resolution)

        H, W, C = input_image.shape
        if h is None:
            h = H
        if w is None:
            w = W
        if f is None:
            f = 256
        x = make_noise_disk(h, w, 1, f) * float(W - 1)
        y = make_noise_disk(h, w, 1, f) * float(H - 1)
        flow = np.concatenate([x, y], axis=2).astype(np.float32)
        detected_map = cv2.remap(input_image, flow, None, cv2.INTER_LINEAR)

        img = resize_image(input_image, image_resolution)
        H, W, C = img.shape

        detected_map = cv2.resize(detected_map, (W, H), interpolation=cv2.INTER_LINEAR)

        if output_type == "pil":
            detected_map = Image.fromarray(detected_map)

        return detected_map