Beispiel #1
0
    def __init__(self, cfg, name):
        super(PreprocessedDataset, self).__init__()

        # Check whether the preprocessed images have all required features
        data_dir = get_preproc_data_dir(cfg, name)
        if not os.path.isdir(data_dir):
            self.num_images = 0
            return
        data_cfg = load_config(data_dir)
        if not all(f in data_cfg.features for f in cfg.features):
            error(
                'the preprocessed images have an incompatible set of features')
        if data_cfg.transfer != cfg.transfer:
            error(
                'the preprocessed images have a mismatching transfer function')

        self.tile_size = cfg.tile_size
        self.features = cfg.features
        self.data_channels = get_channels(data_cfg.features)
        self.channels = get_channels(cfg.features)
        self.num_channels = len(self.channels)
        self.channel_order = get_channel_indices(self.channels,
                                                 self.data_channels)

        # Get the image samples
        samples_filename = os.path.join(data_dir, 'samples.json')
        self.samples = load_json(samples_filename)
        self.num_images = len(self.samples)

        if self.num_images == 0:
            return

        # Map the images into memory
        tza_filename = os.path.join(data_dir, 'images.tza')
        self.images = tza.Reader(tza_filename)
Beispiel #2
0
  def __init__(self, cfg, name):
    super(PreprocessedDataset, self).__init__()

    # Check whether the preprocessed images have all required features
    data_dir = get_preproc_data_dir(cfg, name)
    if not os.path.isdir(data_dir):
      self.num_images = 0
      return
    data_cfg = load_config(data_dir)

    self.tile_size = cfg.tile_size

    # Get the features
    self.features = cfg.features
    self.main_feature = get_main_feature(cfg.features)
    self.auxiliary_features = get_auxiliary_features(cfg.features)

    # Get the channels
    self.channels = get_dataset_channels(cfg.features)
    self.all_channels = get_dataset_channels(data_cfg.features)
    self.num_main_channels = len(get_model_channels(self.main_feature))

    # Get the image samples
    samples_filename = os.path.join(data_dir, 'samples.json')
    self.samples = load_json(samples_filename)
    self.num_images = len(self.samples)

    if self.num_images == 0:
      return

    # Create the memory mapping based image reader
    tza_filename = os.path.join(data_dir, 'images.tza')
    self.images = tza.Reader(tza_filename)