action_caffe.py 文件源码

def __init__(self, net_proto, net_weights, device_id, input_size=None):
        caffe.set_mode_gpu()
        caffe.set_device(device_id)
        self._net = caffe.Net(net_proto, net_weights, caffe.TEST)

        input_shape = self._net.blobs['data'].data.shape

        if input_size is not None:
            input_shape = input_shape[:2] + input_size

        transformer = caffe.io.Transformer({'data': input_shape})

        if self._net.blobs['data'].data.shape[1] == 3:
            transformer.set_transpose('data', (2, 0, 1))  # move image channels to outermost dimension
            transformer.set_mean('data', np.array([104, 117, 123]))  # subtract the dataset-mean value in each channel
        else:
            pass # non RGB data need not use transformer

        self._transformer = transformer

        self._sample_shape = self._net.blobs['data'].data.shape