064befd0e41c3045cee206f9ec8d56f1b027115e,niftynet/engine/windows_aggregator_resize.py,ResizeSamplesAggregator,decode_batch,#ResizeSamplesAggregator#Any#Any#Any#,60

Before Change

                        n_channels=window[w].shape[-1])
                    self.image_out[w] = window[w][batch_id, ...]
                else:
                    if isinstance(window[w], (np.int, np.float32, np.bool)):
                        window_loc = np.reshape(window[w], [1, 1])
                        self.csv_out[w] = self._initialise_empty_csv(
                            n_channel=1)

After Change

                        window[w] = window[w][..., np.newaxis, :]
                    self.image_out[w] = window[w][batch_id, ...]
                else:
                    if not isinstance(window[w], (list, tuple, np.ndarray)):
                        window_loc = np.reshape(window[w], [1, 1])
                        self.csv_out[w] = self._initialise_empty_csv(1)
                    else:
                        window[w] = np.asarray(window[w])
                        try:
                            assert window[w].ndim <= 2
                        except (TypeError, AssertionError):
                            tf.logging.warning(

Instances