Python object_detection.utils.config_util.create_configs_from_pipeline_proto() Examples

The following are 10 code examples of object_detection.utils.config_util.create_configs_from_pipeline_proto(). 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.config_util , or try the search function .
Example #1
Source File: config_util_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_configs"])
Example #2
Source File: config_util_test.py    From Person-Detection-and-Tracking with MIT License 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_config"])
Example #3
Source File: config_util_test.py    From Gun-Detector with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_config"])
Example #4
Source File: config_util_test.py    From ros_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_config"])
Example #5
Source File: config_util_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_config"])
Example #6
Source File: config_util_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_configs"])
Example #7
Source File: config_util_test.py    From MAX-Object-Detector with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_configs"])
Example #8
Source File: config_util_test.py    From g-tensorflow-models with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_configs"])
Example #9
Source File: config_util_test.py    From models with Apache License 2.0 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_configs"])
Example #10
Source File: config_util_test.py    From multilabel-image-classification-tensorflow with MIT License 6 votes vote down vote up 
def test_create_configs_from_pipeline_proto(self):
    """Tests creating configs dictionary from pipeline proto."""

    pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()
    pipeline_config.model.faster_rcnn.num_classes = 10
    pipeline_config.train_config.batch_size = 32
    pipeline_config.train_input_reader.label_map_path = "path/to/label_map"
    pipeline_config.eval_config.num_examples = 20
    pipeline_config.eval_input_reader.add().queue_capacity = 100

    configs = config_util.create_configs_from_pipeline_proto(pipeline_config)
    self.assertProtoEquals(pipeline_config.model, configs["model"])
    self.assertProtoEquals(pipeline_config.train_config,
                           configs["train_config"])
    self.assertProtoEquals(pipeline_config.train_input_reader,
                           configs["train_input_config"])
    self.assertProtoEquals(pipeline_config.eval_config, configs["eval_config"])
    self.assertProtoEquals(pipeline_config.eval_input_reader,
                           configs["eval_input_configs"])