Python object_detection.core.preprocessor.rgb_to_gray() Examples

The following are 30 code examples of object_detection.core.preprocessor.rgb_to_gray(). 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 AniSeg with Apache License 2.0 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #2
Source File: preprocessor_test.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #3
Source File: preprocessor_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #4
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_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #5
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_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #6
Source File: preprocessor_test.py    From object_detection_kitti with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #7
Source File: preprocessor_test.py    From MBMD with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #8
Source File: preprocessor_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #9
Source File: preprocessor_builder_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #10
Source File: preprocessor_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #11
Source File: preprocessor_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #12
Source File: preprocessor_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #13
Source File: preprocessor_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #14
Source File: preprocessor_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    weights = self.createTestGroundtruthWeights()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
        fields.InputDataFields.groundtruth_weights: weights,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #15
Source File: preprocessor_builder_test.py    From MAX-Object-Detector with Apache License 2.0 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #16
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 testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #17
Source File: preprocessor_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    weights = self.createTestGroundtruthWeights()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
        fields.InputDataFields.groundtruth_weights: weights,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #18
Source File: preprocessor_builder_test.py    From g-tensorflow-models with Apache License 2.0 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #19
Source File: preprocessor_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):

    def graph_fn():
      preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                               (preprocessor.normalize_image, {
                                   'original_minval': 0,
                                   'original_maxval': 255,
                                   'target_minval': 0,
                                   'target_maxval': 1,
                               }), (preprocessor.random_crop_image, {})]
      images = self.createTestImages()
      boxes = self.createTestBoxes()
      labels = self.createTestLabels()
      weights = self.createTestGroundtruthWeights()
      tensor_dict = {
          fields.InputDataFields.image: images,
          fields.InputDataFields.groundtruth_boxes: boxes,
          fields.InputDataFields.groundtruth_classes: labels,
          fields.InputDataFields.groundtruth_weights: weights,
      }
      distorted_tensor_dict = preprocessor.preprocess(tensor_dict,
                                                      preprocessing_options)
      distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
      distorted_boxes = distorted_tensor_dict[
          fields.InputDataFields.groundtruth_boxes]
      boxes_rank = tf.rank(boxes)
      distorted_boxes_rank = tf.rank(distorted_boxes)
      images_rank = tf.rank(images)
      distorted_images_rank = tf.rank(distorted_images)
      return [
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ]

    (boxes_rank_, distorted_boxes_rank_, images_rank_,
     distorted_images_rank_) = self.execute_cpu(graph_fn, [])
    self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
    self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #20
Source File: preprocessor_builder_test.py    From models with Apache License 2.0 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #21
Source File: preprocessor_test.py    From motion-rcnn with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #22
Source File: preprocessor_test.py    From mtl-ssl with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #23
Source File: preprocessor_test.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    weights = self.createTestGroundtruthWeights()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
        fields.InputDataFields.groundtruth_weights: weights,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #24
Source File: preprocessor_builder_test.py    From multilabel-image-classification-tensorflow with MIT License 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #25
Source File: preprocessor_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #26
Source File: preprocessor_test.py    From object_detector_app with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #27
Source File: preprocessor_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    weights = self.createTestGroundtruthWeights()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
        fields.InputDataFields.groundtruth_weights: weights,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #28
Source File: preprocessor_builder_test.py    From vehicle_counting_tensorflow with MIT License 5 votes vote down vote up 
def test_build_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})
Example #29
Source File: preprocessor_test.py    From ros_people_object_detection_tensorflow with Apache License 2.0 5 votes vote down vote up 
def testRandomCropImageGrayscale(self):
    preprocessing_options = [(preprocessor.rgb_to_gray, {}),
                             (preprocessor.normalize_image, {
                                 'original_minval': 0,
                                 'original_maxval': 255,
                                 'target_minval': 0,
                                 'target_maxval': 1,
                             }),
                             (preprocessor.random_crop_image, {})]
    images = self.createTestImages()
    boxes = self.createTestBoxes()
    labels = self.createTestLabels()
    tensor_dict = {
        fields.InputDataFields.image: images,
        fields.InputDataFields.groundtruth_boxes: boxes,
        fields.InputDataFields.groundtruth_classes: labels,
    }
    distorted_tensor_dict = preprocessor.preprocess(
        tensor_dict, preprocessing_options)
    distorted_images = distorted_tensor_dict[fields.InputDataFields.image]
    distorted_boxes = distorted_tensor_dict[
        fields.InputDataFields.groundtruth_boxes]
    boxes_rank = tf.rank(boxes)
    distorted_boxes_rank = tf.rank(distorted_boxes)
    images_rank = tf.rank(images)
    distorted_images_rank = tf.rank(distorted_images)
    self.assertEqual(1, distorted_images.get_shape()[3])

    with self.test_session() as sess:
      session_results = sess.run([
          boxes_rank, distorted_boxes_rank, images_rank, distorted_images_rank
      ])
      (boxes_rank_, distorted_boxes_rank_, images_rank_,
       distorted_images_rank_) = session_results
      self.assertAllEqual(boxes_rank_, distorted_boxes_rank_)
      self.assertAllEqual(images_rank_, distorted_images_rank_)
Example #30
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_rgb_to_gray(self):
    preprocessor_text_proto = """
    rgb_to_gray {}
    """
    preprocessor_proto = preprocessor_pb2.PreprocessingStep()
    text_format.Merge(preprocessor_text_proto, preprocessor_proto)
    function, args = preprocessor_builder.build(preprocessor_proto)
    self.assertEqual(function, preprocessor.rgb_to_gray)
    self.assertEqual(args, {})