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"""Tests for object_detection.builders.image_resizer_builder.""" |
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import numpy as np |
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import tensorflow as tf |
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from google.protobuf import text_format |
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from object_detection.builders import image_resizer_builder |
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from object_detection.protos import image_resizer_pb2 |
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class ImageResizerBuilderTest(tf.test.TestCase): |
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def _shape_of_resized_random_image_given_text_proto(self, input_shape, |
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text_proto): |
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image_resizer_config = image_resizer_pb2.ImageResizer() |
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text_format.Merge(text_proto, image_resizer_config) |
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image_resizer_fn = image_resizer_builder.build(image_resizer_config) |
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images = tf.to_float( |
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tf.random_uniform(input_shape, minval=0, maxval=255, dtype=tf.int32)) |
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resized_images, _ = image_resizer_fn(images) |
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with self.test_session() as sess: |
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return sess.run(resized_images).shape |
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def test_build_keep_aspect_ratio_resizer_returns_expected_shape(self): |
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image_resizer_text_proto = """ |
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keep_aspect_ratio_resizer { |
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min_dimension: 10 |
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max_dimension: 20 |
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} |
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""" |
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input_shape = (50, 25, 3) |
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expected_output_shape = (20, 10, 3) |
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output_shape = self._shape_of_resized_random_image_given_text_proto( |
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input_shape, image_resizer_text_proto) |
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self.assertEqual(output_shape, expected_output_shape) |
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def test_build_keep_aspect_ratio_resizer_grayscale(self): |
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image_resizer_text_proto = """ |
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keep_aspect_ratio_resizer { |
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min_dimension: 10 |
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max_dimension: 20 |
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convert_to_grayscale: true |
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} |
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""" |
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input_shape = (50, 25, 3) |
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expected_output_shape = (20, 10, 1) |
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output_shape = self._shape_of_resized_random_image_given_text_proto( |
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input_shape, image_resizer_text_proto) |
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self.assertEqual(output_shape, expected_output_shape) |
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def test_build_keep_aspect_ratio_resizer_with_padding(self): |
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image_resizer_text_proto = """ |
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keep_aspect_ratio_resizer { |
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min_dimension: 10 |
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max_dimension: 20 |
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pad_to_max_dimension: true |
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per_channel_pad_value: 3 |
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per_channel_pad_value: 4 |
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per_channel_pad_value: 5 |
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} |
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""" |
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input_shape = (50, 25, 3) |
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expected_output_shape = (20, 20, 3) |
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output_shape = self._shape_of_resized_random_image_given_text_proto( |
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input_shape, image_resizer_text_proto) |
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self.assertEqual(output_shape, expected_output_shape) |
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def test_built_fixed_shape_resizer_returns_expected_shape(self): |
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image_resizer_text_proto = """ |
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fixed_shape_resizer { |
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height: 10 |
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width: 20 |
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} |
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""" |
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input_shape = (50, 25, 3) |
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expected_output_shape = (10, 20, 3) |
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output_shape = self._shape_of_resized_random_image_given_text_proto( |
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input_shape, image_resizer_text_proto) |
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self.assertEqual(output_shape, expected_output_shape) |
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def test_built_fixed_shape_resizer_grayscale(self): |
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image_resizer_text_proto = """ |
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fixed_shape_resizer { |
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height: 10 |
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width: 20 |
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convert_to_grayscale: true |
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} |
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""" |
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input_shape = (50, 25, 3) |
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expected_output_shape = (10, 20, 1) |
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output_shape = self._shape_of_resized_random_image_given_text_proto( |
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input_shape, image_resizer_text_proto) |
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self.assertEqual(output_shape, expected_output_shape) |
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def test_identity_resizer_returns_expected_shape(self): |
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image_resizer_text_proto = """ |
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identity_resizer { |
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} |
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""" |
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input_shape = (10, 20, 3) |
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expected_output_shape = (10, 20, 3) |
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output_shape = self._shape_of_resized_random_image_given_text_proto( |
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input_shape, image_resizer_text_proto) |
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self.assertEqual(output_shape, expected_output_shape) |
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def test_raises_error_on_invalid_input(self): |
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invalid_input = 'invalid_input' |
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with self.assertRaises(ValueError): |
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image_resizer_builder.build(invalid_input) |
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def _resized_image_given_text_proto(self, image, text_proto): |
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image_resizer_config = image_resizer_pb2.ImageResizer() |
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text_format.Merge(text_proto, image_resizer_config) |
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image_resizer_fn = image_resizer_builder.build(image_resizer_config) |
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image_placeholder = tf.placeholder(tf.uint8, [1, None, None, 3]) |
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resized_image, _ = image_resizer_fn(image_placeholder) |
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with self.test_session() as sess: |
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return sess.run(resized_image, feed_dict={image_placeholder: image}) |
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def test_fixed_shape_resizer_nearest_neighbor_method(self): |
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image_resizer_text_proto = """ |
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fixed_shape_resizer { |
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height: 1 |
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width: 1 |
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resize_method: NEAREST_NEIGHBOR |
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} |
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""" |
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image = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) |
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image = np.expand_dims(image, axis=2) |
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image = np.tile(image, (1, 1, 3)) |
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image = np.expand_dims(image, axis=0) |
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resized_image = self._resized_image_given_text_proto( |
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image, image_resizer_text_proto) |
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vals = np.unique(resized_image).tolist() |
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self.assertEqual(len(vals), 1) |
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self.assertEqual(vals[0], 1) |
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if __name__ == '__main__': |
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tf.test.main() |
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