Python object_detection.protos.image_resizer_pb2.ImageResizer() Examples

The following are 30 code examples of object_detection.protos.image_resizer_pb2.ImageResizer(). 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.protos.image_resizer_pb2 , or try the search function .
Example #1
Source File: infer_from_image.py    From AniSeg with Apache License 2.0 6 votes vote down vote up 
def build_input():
  image_tensor = image_ph = tf.placeholder(dtype=tf.uint8, shape=[None, None, 3], name='image_ph')
  image_resizer_text_proto = """
    keep_aspect_ratio_resizer {
      min_dimension: 800
      max_dimension: 1365
    }
  """
  image_resizer_config = image_resizer_pb2.ImageResizer()
  text_format.Merge(image_resizer_text_proto, image_resizer_config)
  image_resizer_fn = image_resizer_builder.build(image_resizer_config)
  resized_image_tensor, _ = image_resizer_fn(image_tensor)
  resized_image_tensor = tf.cast(resized_image_tensor, dtype=tf.uint8)
  resized_image_tensor = tf.expand_dims(resized_image_tensor, 0)

  return image_ph, resized_image_tensor
Example #2
Source File: image_resizer_builder.py    From hands-detection with MIT License 5 votes vote down vote up 
def build(image_resizer_config):
  """Builds callable for image resizing operations.

  Args:
    image_resizer_config: image_resizer.proto object containing parameters for
      an image resizing operation.

  Returns:
    image_resizer_fn: Callable for image resizing.  This callable always takes
      a rank-3 image tensor (corresponding to a single image) and returns a
      rank-3 image tensor, possibly with new spatial dimensions.

  Raises:
    ValueError: if `image_resizer_config` is of incorrect type.
    ValueError: if `image_resizer_config.image_resizer_oneof` is of expected
      type.
    ValueError: if min_dimension > max_dimension when keep_aspect_ratio_resizer
      is used.
  """
  if not isinstance(image_resizer_config, image_resizer_pb2.ImageResizer):
    raise ValueError('image_resizer_config not of type '
                     'image_resizer_pb2.ImageResizer.')

  if image_resizer_config.WhichOneof(
      'image_resizer_oneof') == 'keep_aspect_ratio_resizer':
    keep_aspect_ratio_config = image_resizer_config.keep_aspect_ratio_resizer
    if not (keep_aspect_ratio_config.min_dimension
            <= keep_aspect_ratio_config.max_dimension):
      raise ValueError('min_dimension > max_dimension')
    return functools.partial(
        preprocessor.resize_to_range,
        min_dimension=keep_aspect_ratio_config.min_dimension,
        max_dimension=keep_aspect_ratio_config.max_dimension)
  if image_resizer_config.WhichOneof(
      'image_resizer_oneof') == 'fixed_shape_resizer':
    fixed_shape_resizer_config = image_resizer_config.fixed_shape_resizer
    return functools.partial(preprocessor.resize_image,
                             new_height=fixed_shape_resizer_config.height,
                             new_width=fixed_shape_resizer_config.width)
  raise ValueError('Invalid image resizer option.')
Example #3
Source File: image_resizer_builder_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images, _ = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #4
Source File: config_util_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def test_get_spatial_image_size_from_aspect_preserving_resizer_dynamic(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [-1, -1])
Example #5
Source File: image_resizer_builder_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images, _ = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #6
Source File: config_util_test.py    From AniSeg with Apache License 2.0 5 votes vote down vote up 
def test_get_spatial_image_size_from_aspect_preserving_resizer_config(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_resizer_config.keep_aspect_ratio_resizer.pad_to_max_dimension = True
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [600, 600])
Example #7
Source File: image_resizer_builder_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #8
Source File: image_resizer_builder_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def _resized_image_given_text_proto(self, image, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    image_placeholder = tf.placeholder(tf.uint8, [1, None, None, 3])
    resized_image = image_resizer_fn(image_placeholder)
    with self.test_session() as sess:
      return sess.run(resized_image, feed_dict={image_placeholder: image})
Example #9
Source File: image_resizer_builder_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #10
Source File: image_resizer_builder_test.py    From Elphas with Apache License 2.0 5 votes vote down vote up 
def _resized_image_given_text_proto(self, image, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    image_placeholder = tf.placeholder(tf.uint8, [1, None, None, 3])
    resized_image, _ = image_resizer_fn(image_placeholder)
    with self.test_session() as sess:
      return sess.run(resized_image, feed_dict={image_placeholder: image})
Example #11
Source File: image_resizer_builder_test.py    From object_detection_with_tensorflow with MIT License 5 votes vote down vote up 
def _resized_image_given_text_proto(self, image, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    image_placeholder = tf.placeholder(tf.uint8, [1, None, None, 3])
    resized_image = image_resizer_fn(image_placeholder)
    with self.test_session() as sess:
      return sess.run(resized_image, feed_dict={image_placeholder: image})
Example #12
Source File: image_resizer_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 _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.cast(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32),
        dtype=tf.float32)
    resized_images, _ = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #13
Source File: config_util_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromConditionalShapeResizer(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.conditional_shape_resizer.size_threshold = 100
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [-1, -1])
Example #14
Source File: config_util_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromAspectPreservingResizerDynamic(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [-1, -1])
Example #15
Source File: config_util_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromAspectPreservingResizerConfig(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_resizer_config.keep_aspect_ratio_resizer.pad_to_max_dimension = True
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [600, 600])
Example #16
Source File: config_util_test.py    From Live-feed-object-device-identification-using-Tensorflow-and-OpenCV with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromFixedShapeResizerConfig(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.fixed_shape_resizer.height = 100
    image_resizer_config.fixed_shape_resizer.width = 200
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [100, 200])
Example #17
Source File: image_resizer_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 _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.cast(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32),
        dtype=tf.float32)
    resized_images, _ = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #18
Source File: image_resizer_builder_test.py    From hands-detection with MIT License 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(
      self, input_shape, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(tf.random_uniform(
        input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #19
Source File: image_resizer_builder.py    From moveo_ros with MIT License 5 votes vote down vote up 
def build(image_resizer_config):
  """Builds callable for image resizing operations.

  Args:
    image_resizer_config: image_resizer.proto object containing parameters for
      an image resizing operation.

  Returns:
    image_resizer_fn: Callable for image resizing.  This callable always takes
      a rank-3 image tensor (corresponding to a single image) and returns a
      rank-3 image tensor, possibly with new spatial dimensions.

  Raises:
    ValueError: if `image_resizer_config` is of incorrect type.
    ValueError: if `image_resizer_config.image_resizer_oneof` is of expected
      type.
    ValueError: if min_dimension > max_dimension when keep_aspect_ratio_resizer
      is used.
  """
  if not isinstance(image_resizer_config, image_resizer_pb2.ImageResizer):
    raise ValueError('image_resizer_config not of type '
                     'image_resizer_pb2.ImageResizer.')

  if image_resizer_config.WhichOneof(
      'image_resizer_oneof') == 'keep_aspect_ratio_resizer':
    keep_aspect_ratio_config = image_resizer_config.keep_aspect_ratio_resizer
    if not (keep_aspect_ratio_config.min_dimension
            <= keep_aspect_ratio_config.max_dimension):
      raise ValueError('min_dimension > max_dimension')
    return functools.partial(
        preprocessor.resize_to_range,
        min_dimension=keep_aspect_ratio_config.min_dimension,
        max_dimension=keep_aspect_ratio_config.max_dimension)
  if image_resizer_config.WhichOneof(
      'image_resizer_oneof') == 'fixed_shape_resizer':
    fixed_shape_resizer_config = image_resizer_config.fixed_shape_resizer
    return functools.partial(preprocessor.resize_image,
                             new_height=fixed_shape_resizer_config.height,
                             new_width=fixed_shape_resizer_config.width)
  raise ValueError('Invalid image resizer option.')
Example #20
Source File: image_resizer_builder_test.py    From moveo_ros with MIT License 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(
      self, input_shape, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(tf.random_uniform(
        input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #21
Source File: image_resizer_builder_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def _resized_image_given_text_proto(self, image, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    image_placeholder = tf.placeholder(tf.uint8, [1, None, None, 3])
    resized_image, _ = image_resizer_fn(image_placeholder)
    with self.test_session() as sess:
      return sess.run(resized_image, feed_dict={image_placeholder: image})
Example #22
Source File: image_resizer_builder_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images, _ = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #23
Source File: config_util_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromAspectPreservingResizerDynamic(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [-1, -1])
Example #24
Source File: config_util_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromAspectPreservingResizerConfig(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_resizer_config.keep_aspect_ratio_resizer.pad_to_max_dimension = True
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [600, 600])
Example #25
Source File: config_util_test.py    From BMW-TensorFlow-Training-GUI with Apache License 2.0 5 votes vote down vote up 
def testGetSpatialImageSizeFromFixedShapeResizerConfig(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.fixed_shape_resizer.height = 100
    image_resizer_config.fixed_shape_resizer.width = 200
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [100, 200])
Example #26
Source File: image_resizer_builder_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def _resized_image_given_text_proto(self, image, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    image_placeholder = tf.placeholder(tf.uint8, [1, None, None, 3])
    resized_image, _ = image_resizer_fn(image_placeholder)
    with self.test_session() as sess:
      return sess.run(resized_image, feed_dict={image_placeholder: image})
Example #27
Source File: image_resizer_builder_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(self, input_shape,
                                                      text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(
        tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images, _ = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape
Example #28
Source File: config_util_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_get_spatial_image_size_from_aspect_preserving_resizer_dynamic(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [-1, -1])
Example #29
Source File: config_util_test.py    From ros_tensorflow with Apache License 2.0 5 votes vote down vote up 
def test_get_spatial_image_size_from_aspect_preserving_resizer_config(self):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    image_resizer_config.keep_aspect_ratio_resizer.min_dimension = 100
    image_resizer_config.keep_aspect_ratio_resizer.max_dimension = 600
    image_resizer_config.keep_aspect_ratio_resizer.pad_to_max_dimension = True
    image_shape = config_util.get_spatial_image_size(image_resizer_config)
    self.assertAllEqual(image_shape, [600, 600])
Example #30
Source File: image_resizer_builder_test.py    From DOTA_models with Apache License 2.0 5 votes vote down vote up 
def _shape_of_resized_random_image_given_text_proto(
      self, input_shape, text_proto):
    image_resizer_config = image_resizer_pb2.ImageResizer()
    text_format.Merge(text_proto, image_resizer_config)
    image_resizer_fn = image_resizer_builder.build(image_resizer_config)
    images = tf.to_float(tf.random_uniform(
        input_shape, minval=0, maxval=255, dtype=tf.int32))
    resized_images = image_resizer_fn(images)
    with self.test_session() as sess:
      return sess.run(resized_images).shape