Python object_detection.utils.label_map_util.convert_label_map_to_categories() Examples

The following are 30 code examples of object_detection.utils.label_map_util.convert_label_map_to_categories(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module object_detection.utils.label_map_util , or try the search function .
Example #1
Source File: eval.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #2
Source File: eval.py    From tensorflow with BSD 2-Clause "Simplified" License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #3
Source File: eval.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #4
Source File: detector.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def load_model(self):
        """
        Loads the detection model

        Args:

        Returns:

        """

        with self._detection_graph.as_default():
            od_graph_def = tf.GraphDef()
            with tf.gfile.GFile(self._path_to_ckpt, 'rb') as fid:
                serialized_graph = fid.read()
                od_graph_def.ParseFromString(serialized_graph)
                tf.import_graph_def(od_graph_def, name='')

        label_map = label_map_util.load_labelmap(self._path_to_labels)
        categories = label_map_util.convert_label_map_to_categories(\
            label_map, max_num_classes=self._num_classes, use_display_name=True)
        self.category_index = label_map_util.create_category_index(categories)
Example #5
Source File: eval.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #6
Source File: object_detection_trainer.py    From CVTron with Apache License 2.0 6 votes vote down vote up 
def evaluate(self, eval_pipeline_file, model_dir, eval_dir):
        configs = self._get_configs_from_pipeline_file(eval_pipeline_file)
        model_config = configs['model']
        eval_config = configs['eval_config']
        input_config = configs['eval_input_config']
        model_fn = functools.partial(
            model_builder.build,
            model_config=model_config,
            is_training=True)
        create_input_dict_fn = functools.partial(self.get_next, input_config)
        label_map = label_map_util.load_labelmap(input_config.label_map_path)
        max_num_classes = max([item.id for item in label_map.item])
        categories = label_map_util.convert_label_map_to_categories(
                        label_map, max_num_classes)
        evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                        model_dir, eval_dir)
Example #7
Source File: eval.py    From HereIsWally with MIT License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #8
Source File: eval.py    From moveo_ros with MIT License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #9
Source File: eval.py    From hands-detection with MIT License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #10
Source File: eval.py    From object_detector_app with MIT License 6 votes vote down vote up 
def main(unused_argv):
  assert FLAGS.checkpoint_dir, '`checkpoint_dir` is missing.'
  assert FLAGS.eval_dir, '`eval_dir` is missing.'
  if FLAGS.pipeline_config_path:
    model_config, eval_config, input_config = get_configs_from_pipeline_file()
  else:
    model_config, eval_config, input_config = get_configs_from_multiple_files()

  model_fn = functools.partial(
      model_builder.build,
      model_config=model_config,
      is_training=False)

  create_input_dict_fn = functools.partial(
      input_reader_builder.build,
      input_config)

  label_map = label_map_util.load_labelmap(input_config.label_map_path)
  max_num_classes = max([item.id for item in label_map.item])
  categories = label_map_util.convert_label_map_to_categories(
      label_map, max_num_classes)

  evaluator.evaluate(create_input_dict_fn, model_fn, eval_config, categories,
                     FLAGS.checkpoint_dir, FLAGS.eval_dir)
Example #11
Source File: label_map_util_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_keep_categories_with_unique_id(self):
    label_map_proto = string_int_label_map_pb2.StringIntLabelMap()
    label_map_string = """
      item {
        id:2
        name:'cat'
      }
      item {
        id:1
        name:'child'
      }
      item {
        id:1
        name:'person'
      }
      item {
        id:1
        name:'n00007846'
      }
    """
    text_format.Merge(label_map_string, label_map_proto)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    self.assertListEqual([{
        'id': 2,
        'name': u'cat'
    }, {
        'id': 1,
        'name': u'child'
    }], categories)
Example #12
Source File: label_map_util_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories_with_few_classes(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    cat_no_offset = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=2)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }]
    self.assertListEqual(expected_categories_list, cat_no_offset)
Example #13
Source File: label_map_util_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories_with_few_classes(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    cat_no_offset = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=2)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }]
    self.assertListEqual(expected_categories_list, cat_no_offset)
Example #14
Source File: label_map_util_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_categories_no_label_map(self):
    categories = label_map_util.convert_label_map_to_categories(
        None, max_num_classes=3)
    expected_categories_list = [{
        'name': u'category_1',
        'id': 1
    }, {
        'name': u'category_2',
        'id': 2
    }, {
        'name': u'category_3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #15
Source File: label_map_util_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def test_convert_label_map_to_categories_no_label_map(self):
    categories = label_map_util.convert_label_map_to_categories(
        None, max_num_classes=3)
    expected_categories_list = [{
        'name': u'category_1',
        'id': 1
    }, {
        'name': u'category_2',
        'id': 2
    }, {
        'name': u'category_3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #16
Source File: label_map_util_test.py    From Gun-Detector with Apache License 2.0 5 votes vote down vote up 
def test_keep_categories_with_unique_id(self):
    label_map_proto = string_int_label_map_pb2.StringIntLabelMap()
    label_map_string = """
      item {
        id:2
        name:'cat'
      }
      item {
        id:1
        name:'child'
      }
      item {
        id:1
        name:'person'
      }
      item {
        id:1
        name:'n00007846'
      }
    """
    text_format.Merge(label_map_string, label_map_proto)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    self.assertListEqual([{
        'id': 2,
        'name': u'cat'
    }, {
        'id': 1,
        'name': u'child'
    }], categories)
Example #17
Source File: label_map_util_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }, {
        'name': u'3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #18
Source File: label_map_util_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_categories_no_label_map(self):
    categories = label_map_util.convert_label_map_to_categories(
        None, max_num_classes=3)
    expected_categories_list = [{
        'name': u'category_1',
        'id': 1
    }, {
        'name': u'category_2',
        'id': 2
    }, {
        'name': u'category_3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #19
Source File: label_map_util_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def test_convert_label_map_to_categories_no_label_map(self):
    categories = label_map_util.convert_label_map_to_categories(
        None, max_num_classes=3)
    expected_categories_list = [{
        'name': u'category_1',
        'id': 1
    }, {
        'name': u'category_2',
        'id': 2
    }, {
        'name': u'category_3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #20
Source File: label_map_util_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories_with_few_classes(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    cat_no_offset = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=2)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }]
    self.assertListEqual(expected_categories_list, cat_no_offset)
Example #21
Source File: label_map_util_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }, {
        'name': u'3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #22
Source File: label_map_util_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def test_convert_label_map_to_categories_no_label_map(self):
    categories = label_map_util.convert_label_map_to_categories(
        None, max_num_classes=3)
    expected_categories_list = [{
        'name': u'category_1',
        'id': 1
    }, {
        'name': u'category_2',
        'id': 2
    }, {
        'name': u'category_3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #23
Source File: label_map_util_test.py    From tensorflow with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def test_keep_categories_with_unique_id(self):
    label_map_proto = string_int_label_map_pb2.StringIntLabelMap()
    label_map_string = """
      item {
        id:2
        name:'cat'
      }
      item {
        id:1
        name:'child'
      }
      item {
        id:1
        name:'person'
      }
      item {
        id:1
        name:'n00007846'
      }
    """
    text_format.Merge(label_map_string, label_map_proto)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    self.assertListEqual([{
        'id': 2,
        'name': u'cat'
    }, {
        'id': 1,
        'name': u'child'
    }], categories)
Example #24
Source File: label_map_util_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories_with_few_classes(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    cat_no_offset = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=2)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }]
    self.assertListEqual(expected_categories_list, cat_no_offset)
Example #25
Source File: label_map_util_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }, {
        'name': u'3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #26
Source File: label_map_util_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_categories_no_label_map(self):
    categories = label_map_util.convert_label_map_to_categories(
        None, max_num_classes=3)
    expected_categories_list = [{
        'name': u'category_1',
        'id': 1
    }, {
        'name': u'category_2',
        'id': 2
    }, {
        'name': u'category_3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #27
Source File: label_map_util_test.py    From Hands-On-Machine-Learning-with-OpenCV-4 with MIT License 5 votes vote down vote up 
def test_keep_categories_with_unique_id(self):
    label_map_proto = string_int_label_map_pb2.StringIntLabelMap()
    label_map_string = """
      item {
        id:2
        name:'cat'
      }
      item {
        id:1
        name:'child'
      }
      item {
        id:1
        name:'person'
      }
      item {
        id:1
        name:'n00007846'
      }
    """
    text_format.Merge(label_map_string, label_map_proto)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    self.assertListEqual([{
        'id': 2,
        'name': u'cat'
    }, {
        'id': 1,
        'name': u'child'
    }], categories)
Example #28
Source File: label_map_util_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories_with_few_classes(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    cat_no_offset = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=2)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }]
    self.assertListEqual(expected_categories_list, cat_no_offset)
Example #29
Source File: label_map_util_test.py    From Traffic-Rule-Violation-Detection-System with MIT License 5 votes vote down vote up 
def test_convert_label_map_to_coco_categories(self):
    label_map_proto = self._generate_label_map(num_classes=4)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    expected_categories_list = [{
        'name': u'1',
        'id': 1
    }, {
        'name': u'2',
        'id': 2
    }, {
        'name': u'3',
        'id': 3
    }]
    self.assertListEqual(expected_categories_list, categories)
Example #30
Source File: label_map_util_test.py    From object_detector_app with MIT License 5 votes vote down vote up 
def test_keep_categories_with_unique_id(self):
    label_map_proto = string_int_label_map_pb2.StringIntLabelMap()
    label_map_string = """
      item {
        id:2
        name:'cat'
      }
      item {
        id:1
        name:'child'
      }
      item {
        id:1
        name:'person'
      }
      item {
        id:1
        name:'n00007846'
      }
    """
    text_format.Merge(label_map_string, label_map_proto)
    categories = label_map_util.convert_label_map_to_categories(
        label_map_proto, max_num_classes=3)
    self.assertListEqual([{
        'id': 2,
        'name': u'cat'
    }, {
        'id': 1,
        'name': u'child'
    }], categories)