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# Copyright (c) 2021 PaddlePaddle 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.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import sys
# add python path of PaddleDetection to sys.path
parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
sys.path.insert(0, parent_path)
# ignore warning log
import warnings
warnings.filterwarnings('ignore')
import paddle
from ppdet.core.workspace import load_config, merge_config
from ppdet.utils.check import check_gpu, check_npu, check_xpu, check_mlu, check_version, check_config
from ppdet.utils.cli import ArgsParser
from ppdet.engine import Tracker
def parse_args():
parser = ArgsParser()
parser.add_argument(
"--det_results_dir",
type=str,
default='',
help="Directory name for detection results.")
parser.add_argument(
'--output_dir',
type=str,
default='output',
help='Directory name for output tracking results.')
parser.add_argument(
'--save_images',
action='store_true',
help='Save tracking results (image).')
parser.add_argument(
'--save_videos',
action='store_true',
help='Save tracking results (video).')
parser.add_argument(
'--show_image',
action='store_true',
help='Show tracking results (image).')
parser.add_argument(
'--scaled',
type=bool,
default=False,
help="Whether coords after detector outputs are scaled, False in JDE YOLOv3 "
"True in general detector.")
args = parser.parse_args()
return args
def run(FLAGS, cfg):
dataset_dir = cfg['EvalMOTDataset'].dataset_dir
data_root = cfg['EvalMOTDataset'].data_root
data_root = '{}/{}'.format(dataset_dir, data_root)
seqs = os.listdir(data_root)
seqs.sort()
# build Tracker
tracker = Tracker(cfg, mode='eval')
# load weights
if cfg.architecture in ['DeepSORT', 'ByteTrack']:
tracker.load_weights_sde(cfg.det_weights, cfg.reid_weights)
else:
tracker.load_weights_jde(cfg.weights)
# inference
tracker.mot_evaluate(
data_root=data_root,
seqs=seqs,
data_type=cfg.metric.lower(),
model_type=cfg.architecture,
output_dir=FLAGS.output_dir,
save_images=FLAGS.save_images,
save_videos=FLAGS.save_videos,
show_image=FLAGS.show_image,
scaled=FLAGS.scaled,
det_results_dir=FLAGS.det_results_dir)
def main():
FLAGS = parse_args()
cfg = load_config(FLAGS.config)
merge_config(FLAGS.opt)
# disable npu in config by default
if 'use_npu' not in cfg:
cfg.use_npu = False
# disable xpu in config by default
if 'use_xpu' not in cfg:
cfg.use_xpu = False
if 'use_gpu' not in cfg:
cfg.use_gpu = False
# disable mlu in config by default
if 'use_mlu' not in cfg:
cfg.use_mlu = False
if cfg.use_gpu:
place = paddle.set_device('gpu')
elif cfg.use_npu:
place = paddle.set_device('npu')
elif cfg.use_xpu:
place = paddle.set_device('xpu')
elif cfg.use_mlu:
place = paddle.set_device('mlu')
else:
place = paddle.set_device('cpu')
check_config(cfg)
check_gpu(cfg.use_gpu)
check_npu(cfg.use_npu)
check_xpu(cfg.use_xpu)
check_mlu(cfg.use_mlu)
check_version()
run(FLAGS, cfg)
if __name__ == '__main__':
main()
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