Python object_detection.builders.preprocessor_builder.build() Examples

The following are 30 code examples of object_detection.builders.preprocessor_builder.build(). 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.builders.preprocessor_builder , or try the search function .
Example #1
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_build_random_vertical_flip(self):
    preprocessor_text_proto = """
    random_vertical_flip {
      keypoint_flip_permutation: 1
      keypoint_flip_permutation: 0
      keypoint_flip_permutation: 2
      keypoint_flip_permutation: 3
      keypoint_flip_permutation: 5
      keypoint_flip_permutation: 4
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_vertical_flip)
    self.assertEqual(args, {'keypoint_flip_permutation': (1, 0, 2, 3, 5, 4)})
Example #2
Source File: preprocessor_builder_test.py    From object_detector_app with MIT License 6 votes vote down vote up 
def test_build_normalize_image(self):
    preprocessor_text_proto = """
    normalize_image {
      original_minval: 0.0
      original_maxval: 255.0
      target_minval: -1.0
      target_maxval: 1.0
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.normalize_image)
    self.assertEqual(args, {
        'original_minval': 0.0,
        'original_maxval': 255.0,
        'target_minval': -1.0,
        'target_maxval': 1.0,
    })
Example #3
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_build_random_crop_image(self):
    preprocessor_text_proto = """
    random_crop_image {
      min_object_covered: 0.75
      min_aspect_ratio: 0.75
      max_aspect_ratio: 1.5
      min_area: 0.25
      max_area: 0.875
      overlap_thresh: 0.5
      clip_boxes: False
      random_coef: 0.125
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_crop_image)
    self.assertEqual(args, {
        'min_object_covered': 0.75,
        'aspect_ratio_range': (0.75, 1.5),
        'area_range': (0.25, 0.875),
        'overlap_thresh': 0.5,
        'clip_boxes': False,
        'random_coef': 0.125,
    })
Example #4
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_build_normalize_image(self):
    preprocessor_text_proto = """
    normalize_image {
      original_minval: 0.0
      original_maxval: 255.0
      target_minval: -1.0
      target_maxval: 1.0
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.normalize_image)
    self.assertEqual(args, {
        'original_minval': 0.0,
        'original_maxval': 255.0,
        'target_minval': -1.0,
        'target_maxval': 1.0,
    })
Example #5
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 6 votes vote down vote up 
def test_build_random_horizontal_flip(self):
    preprocessor_text_proto = """
    random_horizontal_flip {
      keypoint_flip_permutation: 1
      keypoint_flip_permutation: 0
      keypoint_flip_permutation: 2
      keypoint_flip_permutation: 3
      keypoint_flip_permutation: 5
      keypoint_flip_permutation: 4
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_horizontal_flip)
    self.assertEqual(args, {'keypoint_flip_permutation': (1, 0, 2, 3, 5, 4)})
Example #6
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_build_random_vertical_flip(self):
    preprocessor_text_proto = """
    random_vertical_flip {
      keypoint_flip_permutation: 1
      keypoint_flip_permutation: 0
      keypoint_flip_permutation: 2
      keypoint_flip_permutation: 3
      keypoint_flip_permutation: 5
      keypoint_flip_permutation: 4
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_vertical_flip)
    self.assertEqual(args, {'keypoint_flip_permutation': (1, 0, 2, 3, 5, 4)})
Example #7
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_build_random_horizontal_flip(self):
    preprocessor_text_proto = """
    random_horizontal_flip {
      keypoint_flip_permutation: 1
      keypoint_flip_permutation: 0
      keypoint_flip_permutation: 2
      keypoint_flip_permutation: 3
      keypoint_flip_permutation: 5
      keypoint_flip_permutation: 4
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_horizontal_flip)
    self.assertEqual(args, {'keypoint_flip_permutation': (1, 0, 2, 3, 5, 4)})
Example #8
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 6 votes vote down vote up 
def test_build_normalize_image(self):
    preprocessor_text_proto = """
    normalize_image {
      original_minval: 0.0
      original_maxval: 255.0
      target_minval: -1.0
      target_maxval: 1.0
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.normalize_image)
    self.assertEqual(args, {
        'original_minval': 0.0,
        'original_maxval': 255.0,
        'target_minval': -1.0,
        'target_maxval': 1.0,
    })
Example #9
Source File: preprocessor_builder_test.py    From DOTA_models with Apache License 2.0 6 votes vote down vote up 
def test_build_normalize_image(self):
    preprocessor_text_proto = """
    normalize_image {
      original_minval: 0.0
      original_maxval: 255.0
      target_minval: -1.0
      target_maxval: 1.0
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.normalize_image)
    self.assertEqual(args, {
        'original_minval': 0.0,
        'original_maxval': 255.0,
        'target_minval': -1.0,
        'target_maxval': 1.0,
    })
Example #10
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_resize_method(self):
    preprocessor_text_proto = """
    random_resize_method {
      target_height: 75
      target_width: 100
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_resize_method)
    self.assert_dictionary_close(args, {'target_size': [75, 100]})
Example #11
Source File: inputs.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def augment_input_data(tensor_dict, data_augmentation_options):
  """Applies data augmentation ops to input tensors.

  Args:
    tensor_dict: A dictionary of input tensors keyed by fields.InputDataFields.
    data_augmentation_options: A list of tuples, where each tuple contains a
      function and a dictionary that contains arguments and their values.
      Usually, this is the output of core/preprocessor.build.

  Returns:
    A dictionary of tensors obtained by applying data augmentation ops to the
    input tensor dictionary.
  """
  tensor_dict[fields.InputDataFields.image] = tf.expand_dims(
      tf.to_float(tensor_dict[fields.InputDataFields.image]), 0)

  include_instance_masks = (fields.InputDataFields.groundtruth_instance_masks
                            in tensor_dict)
  include_keypoints = (fields.InputDataFields.groundtruth_keypoints
                       in tensor_dict)
  tensor_dict = preprocessor.preprocess(
      tensor_dict, data_augmentation_options,
      func_arg_map=preprocessor.get_default_func_arg_map(
          include_instance_masks=include_instance_masks,
          include_keypoints=include_keypoints))
  tensor_dict[fields.InputDataFields.image] = tf.squeeze(
      tensor_dict[fields.InputDataFields.image], axis=0)
  return tensor_dict
Example #12
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_jitter_boxes(self):
    preprocessor_text_proto = """
    random_jitter_boxes {
      ratio: 0.1
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_jitter_boxes)
    self.assert_dictionary_close(args, {'ratio': 0.1})
Example #13
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_distort_color(self):
    preprocessor_text_proto = """
    random_distort_color {
      color_ordering: 1
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_distort_color)
    self.assertEqual(args, {'color_ordering': 1})
Example #14
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_adjust_saturation(self):
    preprocessor_text_proto = """
    random_adjust_saturation {
      min_delta: 0.75
      max_delta: 1.15
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_adjust_saturation)
    self.assert_dictionary_close(args, {'min_delta': 0.75, 'max_delta': 1.15})
Example #15
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_adjust_brightness(self):
    preprocessor_text_proto = """
    random_adjust_brightness {
      max_delta: 0.2
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_adjust_brightness)
    self.assert_dictionary_close(args, {'max_delta': 0.2})
Example #16
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_rgb_to_gray(self):
    preprocessor_text_proto = """
    random_rgb_to_gray {
      probability: 0.8
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_rgb_to_gray)
    self.assert_dictionary_close(args, {'probability': 0.8})
Example #17
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_image_scale(self):
    preprocessor_text_proto = """
    random_image_scale {
      min_scale_ratio: 0.8
      max_scale_ratio: 2.2
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_image_scale)
    self.assert_dictionary_close(args, {'min_scale_ratio': 0.8,
                                        'max_scale_ratio': 2.2})
Example #18
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_pixel_value_scale(self):
    preprocessor_text_proto = """
    random_pixel_value_scale {
      minval: 0.8
      maxval: 1.2
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_pixel_value_scale)
    self.assert_dictionary_close(args, {'minval': 0.8, 'maxval': 1.2})
Example #19
Source File: preprocessor_builder_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_build_random_adjust_contrast(self):
    preprocessor_text_proto = """
    random_adjust_contrast {
      min_delta: 0.7
      max_delta: 1.1
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_adjust_contrast)
    self.assert_dictionary_close(args, {'min_delta': 0.7, 'max_delta': 1.1})
Example #20
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_crop_to_aspect_ratio(self):
    preprocessor_text_proto = """
    random_crop_to_aspect_ratio {
      aspect_ratio: 0.85
      overlap_thresh: 0.35
      clip_boxes: False
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_crop_to_aspect_ratio)
    self.assert_dictionary_close(args, {'aspect_ratio': 0.85,
                                        'overlap_thresh': 0.35,
                                        'clip_boxes': False})
Example #21
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_crop_pad_image_with_optional_parameters(self):
    preprocessor_text_proto = """
    random_crop_pad_image {
      min_object_covered: 0.75
      min_aspect_ratio: 0.75
      max_aspect_ratio: 1.5
      min_area: 0.25
      max_area: 0.875
      overlap_thresh: 0.5
      clip_boxes: False
      random_coef: 0.125
      min_padded_size_ratio: 0.5
      min_padded_size_ratio: 0.75
      max_padded_size_ratio: 0.5
      max_padded_size_ratio: 0.75
      pad_color: 0.5
      pad_color: 0.5
      pad_color: 1.0
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_crop_pad_image)
    self.assertEqual(args, {
        'min_object_covered': 0.75,
        'aspect_ratio_range': (0.75, 1.5),
        'area_range': (0.25, 0.875),
        'overlap_thresh': 0.5,
        'clip_boxes': False,
        'random_coef': 0.125,
        'min_padded_size_ratio': (0.5, 0.75),
        'max_padded_size_ratio': (0.5, 0.75),
        'pad_color': (0.5, 0.5, 1.0)
    })
Example #22
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_pad_image(self):
    preprocessor_text_proto = """
    random_pad_image {
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_pad_image)
    self.assertEqual(args, {
        'min_image_size': None,
        'max_image_size': None,
        'pad_color': None,
    })
Example #23
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_jitter_boxes(self):
    preprocessor_text_proto = """
    random_jitter_boxes {
      ratio: 0.1
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_jitter_boxes)
    self.assert_dictionary_close(args, {'ratio': 0.1})
Example #24
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_distort_color(self):
    preprocessor_text_proto = """
    random_distort_color {
      color_ordering: 1
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_distort_color)
    self.assertEqual(args, {'color_ordering': 1})
Example #25
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_adjust_saturation(self):
    preprocessor_text_proto = """
    random_adjust_saturation {
      min_delta: 0.75
      max_delta: 1.15
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_adjust_saturation)
    self.assert_dictionary_close(args, {'min_delta': 0.75, 'max_delta': 1.15})
Example #26
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_adjust_contrast(self):
    preprocessor_text_proto = """
    random_adjust_contrast {
      min_delta: 0.7
      max_delta: 1.1
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_adjust_contrast)
    self.assert_dictionary_close(args, {'min_delta': 0.7, 'max_delta': 1.1})
Example #27
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_adjust_brightness(self):
    preprocessor_text_proto = """
    random_adjust_brightness {
      max_delta: 0.2
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_adjust_brightness)
    self.assert_dictionary_close(args, {'max_delta': 0.2})
Example #28
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_rgb_to_gray(self):
    preprocessor_text_proto = """
    random_rgb_to_gray {
      probability: 0.8
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_rgb_to_gray)
    self.assert_dictionary_close(args, {'probability': 0.8})
Example #29
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_image_scale(self):
    preprocessor_text_proto = """
    random_image_scale {
      min_scale_ratio: 0.8
      max_scale_ratio: 2.2
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_image_scale)
    self.assert_dictionary_close(args, {'min_scale_ratio': 0.8,
                                        'max_scale_ratio': 2.2})
Example #30
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_random_pixel_value_scale(self):
    preprocessor_text_proto = """
    random_pixel_value_scale {
      minval: 0.8
      maxval: 1.2
    }
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.random_pixel_value_scale)
    self.assert_dictionary_close(args, {'minval': 0.8, 'maxval': 1.2})