volumes.py 文件源码

def from_toml(filename):
        from keras.utils.data_utils import get_file

        volumes = {}
        with open(filename, 'rb') as fin:
            datasets = toml.load(fin).get('dataset', [])
            for dataset in datasets:
                hdf5_file = dataset['hdf5_file']
                if dataset.get('use_keras_cache', False):
                    hdf5_file = get_file(hdf5_file, dataset['download_url'], md5_hash=dataset.get('download_md5', None))
                image_dataset = dataset.get('image_dataset', None)
                label_dataset = dataset.get('label_dataset', None)
                mask_dataset = dataset.get('mask_dataset', None)
                mask_bounds = dataset.get('mask_bounds', None)
                resolution = dataset.get('resolution', None)
                hdf5_pathed_file = os.path.join(os.path.dirname(filename), hdf5_file)
                volume = HDF5Volume(hdf5_pathed_file,
                                    image_dataset,
                                    label_dataset,
                                    mask_dataset,
                                    mask_bounds=mask_bounds)
                # If the volume configuration specifies an explicit resolution,
                # override any provided in the HDF5 itself.
                if resolution:
                    logging.info('Overriding resolution for volume "%s"', dataset['name'])
                    volume.resolution = np.array(resolution)
                volumes[dataset['name']] = volume

        return volumes