def METHOD_NAME(height, width, channels_first, label_type):
    channels = 3
    if channels_first:
        data_shape = (2, channels, height, width)
    else:
        data_shape = (2, height, width, channels)
    x = (0.5 * np.ones(data_shape)).astype(ART_NUMPY_DTYPE)
    if label_type == "classification":
        y = np.arange(len(x))
    elif label_type == "object_detection":
        y = []
        for _ in range(len(x)):
            y_1, x_1 = np.random.uniform(0, (height / 2, width / 2))
            y_2, x_2 = np.random.uniform((y_1 + 3, x_1 + 3), (height, width))
            target_dict = {
                "boxes": np.array([[x_1, y_1, x_2, y_2]]),
                "labels": np.array([0]),
            }
            y.append(target_dict)
    else:
        y = None
    return x, y