forked from PulseFocusPlatform/PulseFocusPlatform
123 lines
3.5 KiB
Python
123 lines
3.5 KiB
Python
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# 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 sys
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# add python path of PadleDetection to sys.path
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parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
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if parent_path not in sys.path:
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sys.path.append(parent_path)
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# ignore warning log
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import warnings
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warnings.filterwarnings('ignore')
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import paddle
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from paddle.distributed import ParallelEnv
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from ppdet.core.workspace import load_config, merge_config
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from ppdet.engine import Tracker
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from ppdet.utils.check import check_gpu, check_version, check_config
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from ppdet.utils.cli import ArgsParser
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from ppdet.utils.logger import setup_logger
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logger = setup_logger('eval')
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def parse_args():
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parser = ArgsParser()
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parser.add_argument(
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"--data_type",
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type=str,
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default='mot',
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help='Data type of tracking dataset, should be in ["mot", "kitti"]')
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parser.add_argument(
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"--det_results_dir",
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type=str,
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default=None,
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help="Directory name for detection results.")
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parser.add_argument(
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'--output_dir',
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type=str,
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default='output',
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help='Directory name for output tracking results.')
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parser.add_argument(
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'--save_images',
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action='store_true',
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help='Save tracking results (image).')
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parser.add_argument(
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'--save_videos',
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action='store_true',
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help='Save tracking results (video).')
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parser.add_argument(
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'--show_image',
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action='store_true',
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help='Show tracking results (image).')
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args = parser.parse_args()
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return args
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def run(FLAGS, cfg):
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task = cfg['EvalMOTDataset'].task
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dataset_dir = cfg['EvalMOTDataset'].dataset_dir
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data_root = cfg['EvalMOTDataset'].data_root
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data_root = '{}/{}'.format(dataset_dir, data_root)
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seqs = cfg['MOTDataZoo'][task]
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# build Tracker
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tracker = Tracker(cfg, mode='eval')
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# load weights
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if cfg.architecture in ['DeepSORT']:
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if cfg.det_weights != 'None':
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tracker.load_weights_sde(cfg.det_weights, cfg.reid_weights)
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else:
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tracker.load_weights_sde(None, cfg.reid_weights)
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else:
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tracker.load_weights_jde(cfg.weights)
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# inference
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tracker.mot_evaluate(
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data_root=data_root,
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seqs=seqs,
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data_type=FLAGS.data_type,
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model_type=cfg.architecture,
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output_dir=FLAGS.output_dir,
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save_images=FLAGS.save_images,
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save_videos=FLAGS.save_videos,
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show_image=FLAGS.show_image,
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det_results_dir=FLAGS.det_results_dir)
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def main():
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FLAGS = parse_args()
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cfg = load_config(FLAGS.config)
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merge_config(FLAGS.opt)
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check_config(cfg)
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check_gpu(cfg.use_gpu)
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check_version()
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place = 'gpu:{}'.format(ParallelEnv().dev_id) if cfg.use_gpu else 'cpu'
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place = paddle.set_device(place)
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run(FLAGS, cfg)
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if __name__ == '__main__':
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main()
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