Python object_detection.exporter.export_inference_graph() Examples

The following are 30 code examples of object_detection.exporter.export_inference_graph(). 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.exporter , or try the search function .
Example #1
Source File: exporter_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_moving_averages(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = True
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
    expected_variables = set(['conv2d/bias', 'conv2d/kernel', 'global_step'])
    actual_variables = set(
        [var_name for var_name, _ in tf.train.list_variables(output_directory)])
    self.assertTrue(expected_variables.issubset(actual_variables))
Example #2
Source File: exporter_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_export_frozen_graph(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=False)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
Example #3
Source File: export_inference_graph.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def main(_):
  pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
  with tf.gfile.GFile(FLAGS.pipeline_config_path, 'r') as f:
    text_format.Merge(f.read(), pipeline_config)
  text_format.Merge(FLAGS.config_override, pipeline_config)
  if FLAGS.input_shape:
    input_shape = [
        int(dim) if dim != '-1' else None
        for dim in FLAGS.input_shape.split(',')
    ]
  else:
    input_shape = None
  exporter.export_inference_graph(
      FLAGS.input_type, pipeline_config, FLAGS.trained_checkpoint_prefix,
      FLAGS.output_directory, input_shape=input_shape,
      write_inference_graph=FLAGS.write_inference_graph)
Example #4
Source File: exporter_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_with_encoded_image_string_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='encoded_image_string_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #5
Source File: exporter_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_with_tf_example_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='tf_example',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #6
Source File: exporter_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_export_frozen_graph_with_moving_averages(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=True)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(num_classes=1)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = True
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
Example #7
Source File: exporter_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_export_frozen_graph(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=False)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(num_classes=1)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
Example #8
Source File: exporter_test.py    From HereIsWally with MIT License 6 votes vote down vote up 
def test_export_frozen_graph_with_moving_averages(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=True)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(num_classes=1)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = True
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
Example #9
Source File: exporter_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_image_tensor_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #10
Source File: exporter_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_with_image_tensor_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #11
Source File: exporter_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_export_model_with_all_output_nodes(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=False)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(add_detection_masks=True)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
    inference_graph = self._load_inference_graph(inference_graph_path)
    with self.test_session(graph=inference_graph):
      inference_graph.get_tensor_by_name('image_tensor:0')
      inference_graph.get_tensor_by_name('detection_boxes:0')
      inference_graph.get_tensor_by_name('detection_scores:0')
      inference_graph.get_tensor_by_name('detection_classes:0')
      inference_graph.get_tensor_by_name('detection_masks:0')
      inference_graph.get_tensor_by_name('num_detections:0')
Example #12
Source File: exporter_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_export_model_with_detection_only_nodes(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=False)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(add_detection_masks=False)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
    inference_graph = self._load_inference_graph(inference_graph_path)
    with self.test_session(graph=inference_graph):
      inference_graph.get_tensor_by_name('image_tensor:0')
      inference_graph.get_tensor_by_name('detection_boxes:0')
      inference_graph.get_tensor_by_name('detection_scores:0')
      inference_graph.get_tensor_by_name('detection_classes:0')
      inference_graph.get_tensor_by_name('num_detections:0')
      with self.assertRaises(KeyError):
        inference_graph.get_tensor_by_name('detection_masks:0')
Example #13
Source File: exporter_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_export_frozen_graph(self):
    checkpoint_path = os.path.join(self.get_temp_dir(), 'model-ckpt')
    self._save_checkpoint_from_mock_model(checkpoint_path,
                                          use_moving_averages=False)
    inference_graph_path = os.path.join(self.get_temp_dir(),
                                        'exported_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(num_classes=1)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          checkpoint_path=checkpoint_path,
          inference_graph_path=inference_graph_path)
Example #14
Source File: exporter_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_write_inference_graph(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory,
          write_inference_graph=True)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'inference_graph.pbtxt')))
Example #15
Source File: exporter_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_tf_example_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='tf_example',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #16
Source File: exporter_test.py    From yolo_v2 with Apache License 2.0 6 votes vote down vote up 
def test_export_model_with_all_output_nodes(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    inference_graph_path = os.path.join(output_directory,
                                        'frozen_inference_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(add_detection_masks=True)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
    inference_graph = self._load_inference_graph(inference_graph_path)
    with self.test_session(graph=inference_graph):
      inference_graph.get_tensor_by_name('image_tensor:0')
      inference_graph.get_tensor_by_name('detection_boxes:0')
      inference_graph.get_tensor_by_name('detection_scores:0')
      inference_graph.get_tensor_by_name('detection_classes:0')
      inference_graph.get_tensor_by_name('detection_masks:0')
      inference_graph.get_tensor_by_name('num_detections:0')
Example #17
Source File: exporter_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_moving_averages(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = True
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
Example #18
Source File: exporter_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_encoded_image_string_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='encoded_image_string_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
Example #19
Source File: exporter_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_saves_pipeline_file(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      expected_pipeline_path = os.path.join(
          output_directory, 'pipeline.config')
      self.assertTrue(os.path.exists(expected_pipeline_path))

      written_pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      with tf.gfile.GFile(expected_pipeline_path, 'r') as f:
        proto_str = f.read()
        text_format.Merge(proto_str, written_pipeline_config)
        self.assertProtoEquals(pipeline_config, written_pipeline_config)
Example #20
Source File: exporter_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_tf_example_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='tf_example',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
Example #21
Source File: exporter_test.py    From garbage-object-detection-tensorflow with MIT License 6 votes vote down vote up 
def test_export_graph_with_image_tensor_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
Example #22
Source File: exporter_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_with_image_tensor_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #23
Source File: exporter_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_export_graph_saves_pipeline_file(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      expected_pipeline_path = os.path.join(
          output_directory, 'pipeline.config')
      self.assertTrue(os.path.exists(expected_pipeline_path))

      written_pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      with tf.gfile.GFile(expected_pipeline_path, 'r') as f:
        proto_str = f.read()
        text_format.Merge(proto_str, written_pipeline_config)
        self.assertProtoEquals(pipeline_config, written_pipeline_config)
Example #24
Source File: exporter_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_with_tf_example_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='tf_example',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #25
Source File: exporter_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_with_encoded_image_string_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='encoded_image_string_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #26
Source File: exporter_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_export_model_with_all_output_nodes(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    inference_graph_path = os.path.join(output_directory,
                                        'frozen_inference_graph.pb')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel(add_detection_masks=True)
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
    inference_graph = self._load_inference_graph(inference_graph_path)
    with self.test_session(graph=inference_graph):
      inference_graph.get_tensor_by_name('image_tensor:0')
      inference_graph.get_tensor_by_name('detection_boxes:0')
      inference_graph.get_tensor_by_name('detection_scores:0')
      inference_graph.get_tensor_by_name('detection_classes:0')
      inference_graph.get_tensor_by_name('detection_masks:0')
      inference_graph.get_tensor_by_name('num_detections:0')
Example #27
Source File: exporter_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_export_graph_with_encoded_image_string_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='encoded_image_string_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #28
Source File: exporter_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_export_graph_saves_pipeline_file(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=True)
    output_directory = os.path.join(tmp_dir, 'output')
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      expected_pipeline_path = os.path.join(
          output_directory, 'pipeline.config')
      self.assertTrue(os.path.exists(expected_pipeline_path))

      written_pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      with tf.gfile.GFile(expected_pipeline_path, 'r') as f:
        proto_str = f.read()
        text_format.Merge(proto_str, written_pipeline_config)
        self.assertProtoEquals(pipeline_config, written_pipeline_config)
Example #29
Source File: exporter_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_export_graph_with_tf_example_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='tf_example',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))
Example #30
Source File: exporter_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_export_graph_with_image_tensor_input(self):
    tmp_dir = self.get_temp_dir()
    trained_checkpoint_prefix = os.path.join(tmp_dir, 'model.ckpt')
    self._save_checkpoint_from_mock_model(trained_checkpoint_prefix,
                                          use_moving_averages=False)
    with mock.patch.object(
        model_builder, 'build', autospec=True) as mock_builder:
      mock_builder.return_value = FakeModel()
      output_directory = os.path.join(tmp_dir, 'output')
      pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
      pipeline_config.eval_config.use_moving_averages = False
      exporter.export_inference_graph(
          input_type='image_tensor',
          pipeline_config=pipeline_config,
          trained_checkpoint_prefix=trained_checkpoint_prefix,
          output_directory=output_directory)
      self.assertTrue(os.path.exists(os.path.join(
          output_directory, 'saved_model', 'saved_model.pb')))