generate.py 文件源码

def __create_data_layer(self, n, deploy):
        if deploy:
            n.data = L.Input(input_param={
                'shape': [
                    {
                        'dim': [
                            self.__config['deploy-batch-size'],
                            self.__config['deploy-num-channels'],
                            self.__config['crop-size'],
                            self.__config['crop-size']
                        ]
                    }
                ]
            })
        else:
            transform_param = {
                'mirror': True,
                'crop_size': self.__config['crop-size'],
                'scale': 0.00390625
            }
            if self.__config['mean-file']:
                transform_param['mean_file'] = self.__config['mean-file']

            n.data, n.label = L.Data(batch_size=self.__config['train-batch-size'],
                                     include={'phase': caffe.TRAIN},
                                     backend=P.Data.LMDB,
                                     source=self.__config['train-database'],
                                     ntop=2,
                                     transform_param=transform_param)

            transform_param = dict.copy(transform_param)
            transform_param['mirror'] = False
            n.data__test, n.label__test = L.Data(batch_size=self.__config['test-batch-size'],
                                                 include={'phase': caffe.TEST},
                                                 backend=P.Data.LMDB,
                                                 source=self.__config['test-database'],
                                                 ntop=2,
                                                 transform_param=transform_param)
        return n.data