def _parse_config(self, config):
        """ Parses a tensorflow configuration """
        self._batch_size = config['batch_size']
        self._im_height = config['im_height']
        self._im_width = config['im_width']
        self._num_channels = config['channels']
        self._output_layer = config['out_layer']
        self._feature_layer = config['feature_layer']
        self._out_size = None
        if 'out_size' in config.keys():
            self._out_size = config['out_size']
        self._input_arr = np.zeros([self._batch_size, self._im_height,
                                    self._im_width, self._num_channels])

        if self._model_dir is None:
            self._net_data = np.load(config['caffe_weights']).item()
            self._mean = np.load(config['mean_file'])
            self._model_filename = None
        else:
            self._net_data = None
            self._mean = np.load(os.path.join(self._model_dir, 'mean.npy'))
            self._model_filename = os.path.join(self._model_dir, 'model.ckpt')
def _parse_config ( self , config ) : self . _batch_size = config [ 'batch_size' ] self . _im_height = config [ 'im_height' ] self . _im_width = config [ 'im_width' ] self . _num_channels = config [ 'channels' ] self . _output_layer = config [ 'out_layer' ] self . _feature_layer = config [ 'feature_layer' ] self . _out_size = None if 'out_size' in config . keys ( ) : self . _out_size = config [ 'out_size' ] self . _input_arr = np . zeros ( [ self . _batch_size , self . _im_height , self . _im_width , self . _num_channels ] ) if self . _model_dir is None : self . _net_data = np . load ( config [ 'caffe_weights' ] ) . item ( ) self . _mean = np . load ( config [ 'mean_file' ] ) self . _model_filename = None else : self . _net_data = None self . _mean = np . load ( os . path . join ( self . _model_dir , 'mean.npy' ) ) self . _model_filename = os . path . join ( self . _model_dir , 'model.ckpt' )
Parses a tensorflow configuration