chihy d53808c9d0 | 2 years ago | |
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.idea | 2 years ago | |
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data | 2 years ago | |
datasets | 2 years ago | |
doc | 2 years ago | |
losses | 2 years ago | |
models | 2 years ago | |
utils | 2 years ago | |
vgg | 2 years ago | |
README.md | 2 years ago | |
__init__.py | 2 years ago | |
demo.py | 2 years ago | |
preprocess_dataset.py | 2 years ago | |
test_1.py | 2 years ago | |
train.py | 2 years ago | |
train.txt | 2 years ago | |
val.txt | 2 years ago | |
vgg19-fpn-new.pth | 2 years ago |
多尺度贝叶斯人群计数
Multi-Scale-Bayesian-Crowd-Counting
Zhiheng Ma, Xing Wei, Xiaopeng Hong, Yihong Gong
人群计数
在UCF-QNRF上达到当前最优性能
在UCF-QNRF上 MAE = 86.50;MSE = 146.55;
MAE MSE
UCF-QNRF
https://www.crcv.ucf.edu/data/ucf-qnrf/
|类别|名称|版本|
|os|ubuntu|14.04|
|深度学习框架|pytorch|1.0.0|
||opencv|3.4.9|
|名称|说明|
|输入|RGB图像|
|输出|多尺度热力图|计数值|
在terminal下运行以下命令。
python preprocess_dataset.py --origin_dir <directory of original data> --data_dir <directory of processed data>
python train.py --data_dir <directory of processed data> --save_dir <directory of log and model>
python test.py --data_dir <directory of processed data> --save_dir <directory of log and model>
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