video.py 文件源码

def _transform(in_image,loaded,m_path):
    if m_path == 'none':
        return in_image
    if not loaded:
        serializers.load_npz(m_path, model)
        if RUN_ON_GPU:
            cuda.get_device(0).use() #assuming only one core
            model.to_gpu()
        print "loaded"

    xp = np if not RUN_ON_GPU else cuda.cupy

    image = xp.asarray(in_image, dtype=xp.float32).transpose(2, 0, 1)
    image = image.reshape((1,) + image.shape)
    image -= 120

    x = Variable(image)
    y = model(x)

    result = cuda.to_cpu(y.data)
    result = result.transpose(0, 2, 3, 1)
    result = result.reshape((result.shape[1:]))
    result += 120
    result = np.uint8(result)

    return result