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# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for anchor_generator.py."""
from absl.testing import parameterized
import tensorflow as tf, tf_keras
from official.vision.ops import anchor_generator
class AnchorGeneratorTest(parameterized.TestCase, tf.test.TestCase):
@parameterized.parameters(
# Single scale anchor.
(5, [1.0], [[[-16., -16., 48., 48.], [-16., 16., 48., 80.]],
[[16., -16., 80., 48.], [16., 16., 80., 80.]]]),
# # Multi aspect ratio anchor.
(6, [1.0, 4.0, 0.25],
[[[-32., -32., 96., 96., 0., -96., 64., 160., -96., 0., 160., 64.]]]),
)
def testAnchorGeneration(self, level, aspect_ratios, expected_boxes):
image_size = [64, 64]
anchor_size = 2**(level + 1)
stride = 2**level
anchor_gen = anchor_generator._SingleAnchorGenerator(
anchor_size=anchor_size,
scales=[1.],
aspect_ratios=aspect_ratios,
stride=stride,
clip_boxes=False)
anchors = anchor_gen(image_size).numpy()
self.assertAllClose(expected_boxes, anchors)
@parameterized.parameters(
# Single scale anchor.
(5, [1.0], [[[0., 0., 48., 48.], [0., 16., 48., 64.]],
[[16., 0., 64., 48.], [16., 16., 64., 64.]]]),
# # Multi aspect ratio anchor.
(6, [1.0, 4.0, 0.25
], [[[0., 0., 64., 64., 0., 0., 64., 64., 0., 0., 64., 64.]]]),
)
def testAnchorGenerationClipped(self, level, aspect_ratios, expected_boxes):
image_size = [64, 64]
anchor_size = 2**(level + 1)
stride = 2**level
anchor_gen = anchor_generator._SingleAnchorGenerator(
anchor_size=anchor_size,
scales=[1.],
aspect_ratios=aspect_ratios,
stride=stride,
clip_boxes=True)
anchors = anchor_gen(image_size).numpy()
self.assertAllClose(expected_boxes, anchors)
class MultiScaleAnchorGeneratorTest(parameterized.TestCase, tf.test.TestCase):
@parameterized.parameters(
# Multi scale anchor.
(5, 6, [[1.0], [1.0]], [[-16, -16, 48, 48], [-16, 16, 48, 80],
[16, -16, 80, 48], [16, 16, 80, 80],
[-32, -32, 96, 96]]),)
def testAnchorGeneration(self, min_level, max_level, aspect_ratios,
expected_boxes):
image_size = [64, 64]
levels = range(min_level, max_level + 1)
anchor_sizes = [2**(level + 1) for level in levels]
strides = [2**level for level in levels]
anchor_gen = anchor_generator.AnchorGenerator(
anchor_sizes=anchor_sizes,
scales=[1.],
aspect_ratios=aspect_ratios,
strides=strides)
anchors = anchor_gen(image_size)
anchors = [tf.reshape(anchor, [-1, 4]) for anchor in anchors]
anchors = tf.concat(anchors, axis=0).numpy()
self.assertAllClose(expected_boxes, anchors)
@parameterized.parameters(
# Multi scale anchor.
(5, 6, [[1.0], [1.0]], [[-16, -16, 48, 48], [-16, 16, 48, 80],
[16, -16, 80, 48], [16, 16, 80, 80],
[-32, -32, 96, 96]]),)
def testAnchorGenerationClipped(self, min_level, max_level, aspect_ratios,
expected_boxes):
image_size = [64, 64]
levels = range(min_level, max_level + 1)
anchor_sizes = [2**(level + 1) for level in levels]
strides = [2**level for level in levels]
anchor_gen = anchor_generator.AnchorGenerator(
anchor_sizes=anchor_sizes,
scales=[1.],
aspect_ratios=aspect_ratios,
strides=strides,
clip_boxes=False)
anchors = anchor_gen(image_size)
anchors = [tf.reshape(anchor, [-1, 4]) for anchor in anchors]
anchors = tf.concat(anchors, axis=0).numpy()
self.assertAllClose(expected_boxes, anchors)
@parameterized.parameters(
# Multi scale anchor.
(5, 6, [1.0], {
'5': [[[-16., -16., 48., 48.], [-16., 16., 48., 80.]],
[[16., -16., 80., 48.], [16., 16., 80., 80.]]],
'6': [[[-32, -32, 96, 96]]]
}),)
def testAnchorGenerationDict(self, min_level, max_level, aspect_ratios,
expected_boxes):
image_size = [64, 64]
levels = range(min_level, max_level + 1)
anchor_sizes = dict((str(level), 2**(level + 1)) for level in levels)
strides = dict((str(level), 2**level) for level in levels)
anchor_gen = anchor_generator.AnchorGenerator(
anchor_sizes=anchor_sizes,
scales=[1.],
aspect_ratios=aspect_ratios,
strides=strides,
clip_boxes=False)
anchors = anchor_gen(image_size)
for k in expected_boxes.keys():
self.assertAllClose(expected_boxes[k], anchors[k].numpy())
if __name__ == '__main__':
tf.test.main()
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