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LockzhinerAI/PaddleDetection

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eval_mot.py
export_model.py
gen_semi_coco.py
infer.py
infer_culane.py
infer_mot.py
post_quant.py
slice_image.py
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x2coco.py
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infer_mot.py 4.39 KB
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chenxujun 提交于 3年前 . Fix some words (#7667)
# 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.engine import Tracker
from ppdet.utils.check import check_gpu, check_npu, check_xpu, check_mlu, check_version, check_config
from ppdet.utils.cli import ArgsParser
def parse_args():
parser = ArgsParser()
parser.add_argument(
'--video_file', type=str, default=None, help='Video name for tracking.')
parser.add_argument(
'--frame_rate',
type=int,
default=-1,
help='Video frame rate for tracking.')
parser.add_argument(
"--image_dir",
type=str,
default=None,
help="Directory for images to perform inference on.")
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.")
parser.add_argument(
"--draw_threshold",
type=float,
default=0.5,
help="Threshold to reserve the result for visualization.")
args = parser.parse_args()
return args
def run(FLAGS, cfg):
# build Tracker
tracker = Tracker(cfg, mode='test')
# 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_predict_seq(
video_file=FLAGS.video_file,
frame_rate=FLAGS.frame_rate,
image_dir=FLAGS.image_dir,
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,
draw_threshold=FLAGS.draw_threshold)
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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