preprocessing.py 文件源码

def resize_image(image, params={}):
    if params.has_key('height') and params.has_key('width'):
        if np.random.uniform() < params.get('resize_prob', 1.0):
            interpolation_map = {
                'LINEAR': cv2.INTER_LINEAR,
                'AREA': cv2.INTER_AREA,
                'NEAREST': cv2.INTER_NEAREST,
                'CUBIC': cv2.INTER_CUBIC,
                'LANCZOS4': cv2.INTER_LANCZOS4,
            }
            interp = interpolation_map[np.random.choice(params.get('interpolation', ['LINEAR']))]
            image,_ = resize_image_by_warp(image, params['width'], params['height'], interp)

    return image