Awesome

MSSRM

An implementation of "Super-Resolution Information Enhancement For Crowd Counting" (Accepted by ICASSP 2023)

Environment

python >=3.7<br /> pytorch >=1.7<br /> opencv-python >=4.0<br /> scipy >=1.4.0<br /> h5py >=2.10<br /> pillow >=7.0.0<br />

Datasets

Download SR-Crowd dataset from Baidu-Disk, password:mvi3 ; or Google-Drive

Model

Download the pretrained model from from Baidu-Disk, password:ma5g ; or Google-Drive

Quickly test

• git clone https://github.com/Xiejiahao233/MSSRM.git<br /> cd MSSRM<br />

• Download Dataset and Model<br />

• Generate images list

  Edit "make_npydata.py" to change the path to your original dataset folder.<br /> Run python make_npydata.py .<br />

• Test<br /> python val.py --test_dataset Crowdsr --pre ./model/Crowdsr/model_best.pth --gpu_id 0<br />

Training

Coming soon.

Reference

@article{xie2023super,
  title={Super-Resolution Information Enhancement For Crowd Counting},
  author={Xie, Jiahao and Xu, Wei and Liang, Dingkang and Ma, Zhanyu and Liang, Kongming and Liu, Weidong and Wang, Rui and Jin, Ling},
  journal={arXiv preprint arXiv:2303.06925},
  year={2023}
}