一种通用的图像预处理方式

图像像素处理 正反向，使像素呈高斯分布：

SQUEEZENET_MEAN = np.array([0.485, 0.456, 0.406], dtype=np.float32)
SQUEEZENET_STD = np.array([0.229, 0.224, 0.225], dtype=np.float32)


def preprocess_image(img):
    """
    Preprocess an image for squeezenet.
    Subtracts the pixel mean and divides by the standard deviation.
    """
    return (img.astype(np.float32) / 255.0 - SQUEEZENET_MEAN) / SQUEEZENET_STD


def deprocess_image(img, rescale=False):
    """Undo preprocessing on an image and convert back to uint8."""
    img = (img * SQUEEZENET_STD + SQUEEZENET_MEAN)
    if rescale:
        vmin, vmax = img.min(), img.max()
        img = (img - vmin) / (vmax - vmin)
    return np.clip(255 * img, 0.0, 255.0).astype(np.uint8)