Single Domain Generalization for Crowd Counting

This is an official repository for our CVPR2024 work, "Single Domain Generalization for Crowd Counting". You can read our paper here.

Requirements

Python 3.10.12
PyTorch 2.0.1
Torchvision 0.15.2
Others specified in requirements.txt

Data Preparation

Download ShanghaiTech and UCF-QNRF datasets from official sites and unzip them.

Run the following commands to preprocess the datasets:

python utils/preprocess_data.py --origin-dir [path_to_ShanghaiTech]/part_A --data-dir data/sta
python utils/preprocess_data.py --origin-dir [path_to_ShanghaiTech]/part_B --data-dir data/stb
python utils/preprocess_data.py --origin-dir [path_to_UCF-QNRF] --data-dir data/qnrf

Run the following commands to generate GT density maps:

python dmap_gen.py --path data/sta
python dmap_gen.py --path data/stb
python dmap_gen.py --path data/qnrf

Training

Run the following command:

python main.py --task train --config configs/sta_train.yml

You may edit the .yml config file as you like.

Testing

Run the following commands after you specify the path to the model weight in the config file:

python main.py --task test --config configs/sta_test_stb.yml
python main.py --task test --config configs/sta_test_qnrf.yml

Inference

Run the following command:

python inference.py --img_path [path_to_img_file_or_directory] --model_path [path_to_model_weight] --save_path output.txt --vis_dir vis

Pretrained Weights

We provide pretrained weights in the table below:

Source	Performance	Weights
A	B: 11.4MAE, 19.7MSE Q: 115.7MAE, 199.8MSE	OneDrive Google Drive
B	A: 99.6MAE, 182.9MSE Q: 165.6MAE, 290.4MSE	OneDrive Google Drive
Q	A: 65.5MAE, 110.1MSE B: 12.3MAE, 24.1MSE	~~OneDrive~~ Google Drive

Citation

If you find this work helpful in your research, please cite the following:

@inproceedings{pengMPCount2024,
  title = {Single Domain Generalization for Crowd Counting},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2024)},
  author = {Peng, Zhuoxuan and Chan, S.-H. Gary},
  year = {2024}
}

Shimmer93/MPCount