Internal change

PiperOrigin-RevId: 353289158

official/vision/beta/dataloaders/tf_example_decoder.py

@@ -17,8 +17,6 @@
 A decoder to decode string tensors containing serialized tensorflow.Example
 protos for object detection.
 """
-import csv
-# Import libraries
 import tensorflow as tf
 
 from official.vision.beta.dataloaders import decoder
@@ -172,44 +170,3 @@ class TfExampleDecoder(decoder.Decoder):
           'groundtruth_instance_masks_png': parsed_tensors['image/object/mask'],
       })
     return decoded_tensors
-
-
-class TfExampleDecoderLabelMap(TfExampleDecoder):
-  """Tensorflow Example proto decoder."""
-
-  def __init__(self, label_map, include_mask=False, regenerate_source_id=False):
-    super(TfExampleDecoderLabelMap, self).__init__(
-        include_mask=include_mask, regenerate_source_id=regenerate_source_id)
-    self._keys_to_features.update({
-        'image/object/class/text': tf.io.VarLenFeature(tf.string),
-    })
-    name_to_id = self._process_label_map(label_map)
-    self._name_to_id_table = tf.lookup.StaticHashTable(
-        tf.lookup.KeyValueTensorInitializer(
-            keys=tf.constant(list(name_to_id.keys()), dtype=tf.string),
-            values=tf.constant(list(name_to_id.values()), dtype=tf.int64)),
-        default_value=-1)
-
-  def _process_label_map(self, label_map):
-    if label_map.endswith('.csv'):
-      name_to_id = self._process_csv(label_map)
-    else:
-      raise ValueError('The label map file is in incorrect format.')
-    return name_to_id
-
-  def _process_csv(self, label_map):
-    name_to_id = {}
-    with tf.io.gfile.GFile(label_map, 'r') as f:
-      reader = csv.reader(f, delimiter=',')
-      for row in reader:
-        if len(row) != 2:
-          raise ValueError('Each row of the csv label map file must be in '
-                           '`id,name` format. length = {}'.format(len(row)))
-        id_index = int(row[0])
-        name = row[1]
-        name_to_id[name] = id_index
-    return name_to_id
-
-  def _decode_classes(self, parsed_tensors):
-    return self._name_to_id_table.lookup(
-        parsed_tensors['image/object/class/text'])

official/vision/beta/tasks/retinanet.py

@@ -94,16 +94,7 @@ class RetinaNetTask(base_task.Task):
           regenerate_source_id=decoder_cfg.regenerate_source_id)
     else:
       raise ValueError('Unknown decoder type: {}!'.format(params.decoder.type))
-    decoder_cfg = params.decoder.get()
-    if params.decoder.type == 'simple_decoder':
-      decoder = tf_example_decoder.TfExampleDecoder(
-          regenerate_source_id=decoder_cfg.regenerate_source_id)
-    elif params.decoder.type == 'label_map_decoder':
-      decoder = tf_example_decoder.TfExampleDecoderLabelMap(
-          label_map=decoder_cfg.label_map,
-          regenerate_source_id=decoder_cfg.regenerate_source_id)
-    else:
-      raise ValueError('Unknown decoder type: {}!'.format(params.decoder.type))
+
     parser = retinanet_input.Parser(
         output_size=self.task_config.model.input_size[:2],
         min_level=self.task_config.model.min_level,