'Constructor sets keys_to_features and items_to_handlers.'

def __init__(self):

    self.keys_to_features = {'image/encoded': tf.FixedLenFeature((), tf.string, default_value=''), 'image/format': tf.FixedLenFeature((), tf.string, default_value='jpeg'), 'image/filename': tf.FixedLenFeature((), tf.string, default_value=''), 'image/key/sha256': tf.FixedLenFeature((), tf.string, default_value=''), 'image/source_id': tf.FixedLenFeature((), tf.string, default_value=''), 'image/height': tf.FixedLenFeature((), tf.int64, 1), 'image/width': tf.FixedLenFeature((), tf.int64, 1), 'image/object/bbox/xmin': tf.VarLenFeature(tf.float32), 'image/object/bbox/xmax': tf.VarLenFeature(tf.float32), 'image/object/bbox/ymin': tf.VarLenFeature(tf.float32), 'image/object/bbox/ymax': tf.VarLenFeature(tf.float32), 'image/object/class/label': tf.VarLenFeature(tf.int64), 'image/object/area': tf.VarLenFeature(tf.float32), 'image/object/is_crowd': tf.VarLenFeature(tf.int64), 'image/object/difficult': tf.VarLenFeature(tf.int64), 'image/segmentation/object': tf.VarLenFeature(tf.int64), 'image/segmentation/object/class': tf.VarLenFeature(tf.int64)}
    self.items_to_handlers = {fields.InputDataFields.image: slim_example_decoder.Image(image_key='image/encoded', format_key='image/format', channels=3), fields.InputDataFields.source_id: slim_example_decoder.Tensor('image/source_id'), fields.InputDataFields.key: slim_example_decoder.Tensor('image/key/sha256'), fields.InputDataFields.filename: slim_example_decoder.Tensor('image/filename'), fields.InputDataFields.groundtruth_boxes: slim_example_decoder.BoundingBox(['ymin', 'xmin', 'ymax', 'xmax'], 'image/object/bbox/'), fields.InputDataFields.groundtruth_classes: slim_example_decoder.Tensor('image/object/class/label'), fields.InputDataFields.groundtruth_area: slim_example_decoder.Tensor('image/object/area'), fields.InputDataFields.groundtruth_is_crowd: slim_example_decoder.Tensor('image/object/is_crowd'), fields.InputDataFields.groundtruth_difficult: slim_example_decoder.Tensor('image/object/difficult'), fields.InputDataFields.groundtruth_instance_masks: slim_example_decoder.ItemHandlerCallback(['image/segmentation/object', 'image/height', 'image/width'], self._reshape_instance_masks), fields.InputDataFields.groundtruth_instance_classes: slim_example_decoder.Tensor('image/segmentation/object/class')}
