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])
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})
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
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])