official/projects/centernet/modeling/centernet_model_test.py
# Copyright 2024 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.
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"""Test for centernet detection model."""
from absl.testing import parameterized
import tensorflow as tf, tf_keras
from official.projects.centernet.configs import backbones
from official.projects.centernet.modeling import centernet_model
from official.projects.centernet.modeling.backbones import hourglass
from official.projects.centernet.modeling.heads import centernet_head
from official.projects.centernet.modeling.layers import detection_generator
from official.vision.configs import common
class CenterNetTest(parameterized.TestCase, tf.test.TestCase):
def testBuildCenterNet(self):
backbone = hourglass.build_hourglass(
input_specs=tf_keras.layers.InputSpec(shape=[None, 512, 512, 3]),
backbone_config=backbones.Backbone(type='hourglass'),
norm_activation_config=common.NormActivation(use_sync_bn=True)
)
task_config = {
'ct_heatmaps': 90,
'ct_offset': 2,
'ct_size': 2,
}
input_levels = ['2_0', '2']
head = centernet_head.CenterNetHead(
task_outputs=task_config,
input_specs=backbone.output_specs,
input_levels=input_levels)
detection_ge = detection_generator.CenterNetDetectionGenerator()
model = centernet_model.CenterNetModel(
backbone=backbone,
head=head,
detection_generator=detection_ge
)
outputs = model(tf.zeros((5, 512, 512, 3)))
self.assertLen(outputs['raw_output'], 3)
self.assertLen(outputs['raw_output']['ct_heatmaps'], 2)
self.assertLen(outputs['raw_output']['ct_offset'], 2)
self.assertLen(outputs['raw_output']['ct_size'], 2)
self.assertEqual(outputs['raw_output']['ct_heatmaps'][0].shape,
(5, 128, 128, 90))
self.assertEqual(outputs['raw_output']['ct_offset'][0].shape,
(5, 128, 128, 2))
self.assertEqual(outputs['raw_output']['ct_size'][0].shape,
(5, 128, 128, 2))
if __name__ == '__main__':
tf.test.main()