def _generate_predictions(model, data_generator, batch_size, nb_samples, vol_params): # whole volumes if vol_params is not None: for _ in range(nb_samples): # assumes nr volume vols = nrn_utils.predict_volumes(model, data_generator, batch_size, vol_params["patch_size"], vol_params["patch_stride"], vol_params["grid_size"]) vol_true, vol_pred = vols[0], vols[1] yield (vol_true, vol_pred) # just one batch else: for _ in range(nb_samples): # assumes nr batches vol_pred, vol_true = nrn_utils.next_label(model, data_generator) yield (vol_true, vol_pred)