63 lines
2.1 KiB
Python
63 lines
2.1 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import os
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import unittest
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from ppdet.core.workspace import load_config
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from ppdet.engine import Trainer
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class TestMultiScaleInference(unittest.TestCase):
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def setUp(self):
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self.set_config()
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def set_config(self):
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self.mstest_cfg_file = 'configs/faster_rcnn/faster_rcnn_r34_fpn_multiscaletest_1x_coco.yml'
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# test evaluation with multi scale test
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def test_eval_mstest(self):
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cfg = load_config(self.mstest_cfg_file)
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trainer = Trainer(cfg, mode='eval')
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cfg.weights = 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams'
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trainer.load_weights(cfg.weights)
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trainer.evaluate()
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# test inference with multi scale test
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def test_infer_mstest(self):
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cfg = load_config(self.mstest_cfg_file)
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trainer = Trainer(cfg, mode='test')
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cfg.weights = 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams'
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trainer.load_weights(cfg.weights)
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tests_img_root = os.path.join(os.path.dirname(__file__), 'imgs')
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# input images to predict
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imgs = [
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'coco2017_val2017_000000000139.jpg',
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'coco2017_val2017_000000000724.jpg'
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]
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imgs = [os.path.join(tests_img_root, img) for img in imgs]
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trainer.predict(
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imgs, draw_threshold=0.5, output_dir='output', save_results=False)
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if __name__ == '__main__':
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unittest.main()
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