Python object_detection.core.preprocessor.random_pad_image() Examples

The following are 30 code examples of object_detection.core.preprocessor.random_pad_image(). 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.core.preprocessor , or try the search function .
Example #1
Source File: preprocessor_builder_test.py    From object_detection_with_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 #2
Source File: preprocessor_builder_test.py    From Traffic-Rule-Violation-Detection-System 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 #3
Source File: preprocessor_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #4
Source File: preprocessor_builder_test.py    From ros_tensorflow with Apache License 2.0 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 #5
Source File: preprocessor_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #6
Source File: preprocessor_builder_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 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 #7
Source File: preprocessor_builder_test.py    From moveo_ros 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 #8
Source File: preprocessor_builder_test.py    From hands-detection 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 #9
Source File: preprocessor_builder_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_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 #10
Source File: preprocessor_builder_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_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 #11
Source File: preprocessor_builder_test.py    From object_detection_kitti with Apache License 2.0 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 #12
Source File: preprocessor_builder_test.py    From MBMD 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 #13
Source File: preprocessor_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #14
Source File: preprocessor_builder_test.py    From Elphas with Apache License 2.0 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 #15
Source File: preprocessor_builder_test.py    From object_detection_with_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 #16
Source File: preprocessor_builder_test.py    From DOTA_models with Apache License 2.0 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 #17
Source File: preprocessor_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #18
Source File: preprocessor_builder_test.py    From AniSeg with Apache License 2.0 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 #19
Source File: preprocessor_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #20
Source File: preprocessor_builder_test.py    From MAX-Object-Detector with Apache License 2.0 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 #21
Source File: preprocessor_test.py    From Accident-Detection-on-Indian-Roads with GNU Affero General Public License v3.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #22
Source File: preprocessor_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #23
Source File: preprocessor_builder_test.py    From g-tensorflow-models with Apache License 2.0 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 #24
Source File: preprocessor_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #25
Source File: preprocessor_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def testRandomAbsolutePadImageWithKeypoints(self):
    height_padding = 10
    width_padding = 20
    def graph_fn():
      images = self.createTestImages()
      boxes = self.createTestBoxes()
      labels = self.createTestLabels()
      keypoints, _ = self.createTestKeypoints()
      tensor_dict = {
          fields.InputDataFields.image: tf.cast(images, dtype=tf.float32),
          fields.InputDataFields.groundtruth_boxes: boxes,
          fields.InputDataFields.groundtruth_classes: labels,
          fields.InputDataFields.groundtruth_keypoints: keypoints,
      }

      preprocessing_options = [(preprocessor.random_absolute_pad_image, {
          'max_height_padding': height_padding,
          'max_width_padding': width_padding
      })]
      padded_tensor_dict = preprocessor.preprocess(tensor_dict,
                                                   preprocessing_options)
      original_shape = tf.shape(images)
      final_shape = tf.shape(padded_tensor_dict[fields.InputDataFields.image])
      padded_keypoints = padded_tensor_dict[
          fields.InputDataFields.groundtruth_keypoints]
      return (original_shape, final_shape, padded_keypoints)
    for _ in range(100):
      original_shape, output_shape, padded_keypoints_ = self.execute_cpu(
          graph_fn, [])
      _, height, width, _ = original_shape
      self.assertGreaterEqual(output_shape[1], height)
      self.assertLess(output_shape[1], height + height_padding)
      self.assertGreaterEqual(output_shape[2], width)
      self.assertLess(output_shape[2], width + width_padding)
      # Verify the keypoints are populated. The correctness of the keypoint
      # coordinates are already tested in random_pad_image function.
      self.assertEqual(padded_keypoints_.shape, (2, 3, 2))
Example #26
Source File: preprocessor_builder_test.py    From models with Apache License 2.0 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 #27
Source File: preprocessor_builder_test.py    From motion-rcnn 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 #28
Source File: preprocessor_builder_test.py    From mtl-ssl with Apache License 2.0 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 #29
Source File: preprocessor_test.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
def testRandomPadImageWithCache(self):
    preprocess_options = [(preprocessor.normalize_image, {
        'original_minval': 0,
        'original_maxval': 255,
        'target_minval': 0,
        'target_maxval': 1,}), (preprocessor.random_pad_image, {})]
    self._testPreprocessorCache(preprocess_options,
                                test_boxes=True,
                                test_masks=True,
                                test_keypoints=True)
Example #30
Source File: preprocessor_builder_test.py    From multilabel-image-classification-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,
    })