image_process.py 文件源码

def postprocess_torch(output):

    # Should we?
    def denormalize(image):
        for t in range(3):
            image[t, :, :] = (image[t, :, :] * STD[t]) + MEAN[t]
        return image

    transformer = transforms.Compose([
        transforms.ToPILImage()])

    image = output.cpu().data[0]
    image = torch.clamp(denormalize(image), min=0, max=1)
    return transformer(image)