faceFeaturesCNN.py 文件源码

def getNet():
    global TRANSFORMER, NET
    if TRANSFORMER is None or NET is None:
        import caffe

        os.environ['GLOG_minloglevel'] = '2'

        caffe.set_mode_cpu()
        ## Opening mean average image
        proto_data = open(mean_path, "rb").read()
        a = caffe.io.caffe_pb2.BlobProto.FromString(proto_data)
        mean = caffe.io.blobproto_to_array(a)[0]
        ## Loading the CNN
        NET = caffe.Classifier(deploy_path, model_path)
        ## Setting up the right transformer for an input image
        TRANSFORMER = caffe.io.Transformer({'data': NET.blobs['data'].data.shape})
        TRANSFORMER.set_transpose('data', (2, 0, 1))
        TRANSFORMER.set_channel_swap('data', (2, 1, 0))
        TRANSFORMER.set_raw_scale('data', 255.0)
        TRANSFORMER.set_mean('data', mean)
        print('> CNN Model loaded to regress 3D Shape and Texture!')
    return TRANSFORMER, NET