def load_dataset_in_memory_and_resize(data_access, set, division, dataset_path, targets_path, tmp_size, final_size, batch_size): if data_access == "in-memory": with timer("Loading %s data"%set): dataset = InMemoryDataset(set, dataset_path, source_targets=targets_path, division=division) draw_data = np.copy(dataset.dataset) targets = np.copy(dataset.targets) del dataset elif data_access == "fuel": with timer("Loading %s data"%set): dataset = FuelDataset(set, tmp_size, batch_size=batch_size, shuffle=False, division=division) draw_data,targets = dataset.return_whole_dataset() del dataset else: raise Exception("Data access not available. Must be 'fuel' or 'in-memory'. Here : %s."%data_access) if tmp_size != final_size: # Resize images from the validset out = np.zeros((draw_data.shape[0], final_size[0], final_size[1], final_size[2]), dtype="float32") with timer("Resizing %s images"%set): for i in range(draw_data.shape[0]): out[i] = resize_pil(draw_data[i], final_size[0:2]) del draw_data return out, targets else: return draw_data, targets