pip install torch==1.10.0+cu111 torchvision==0.11.0+cu111 torchaudio==0.10.0 -f https://download.pytorch.org/whl/torch_stable.html
pip install timm==0.3.2
pip install numpy
pip install matplotlib tqdm 
pip install tensorboard
pip install scipy
pip install imgaug
pip install opencv-python
pip3 install hub

./data/
|--FSC147
|  |--images_384_VarV2
|  |  |--2.jpg
|  |  |--3.jpg
|  |--gt_density_map_adaptive_384_VarV2
|  |  |--2.npy
|  |  |--3.npy
|  |--annotation_FSC147_384.json
|  |--Train_Test_Val_FSC_147.json
|  |--ImageClasses_FSC147.txt
|  |--train.txt
|  |--test.txt
|  |--val.txt
|--CARPK/
|  |--Annotations/
|  |--Images/
|  |--ImageSets/

python datasetmake.py
python biclassify.py

python grounding_pos.py --root_path ./data/FSC147/
python grounding_neg.py --root_path ./data/FSC147/

CUDA_VISIBLE_DEVICES=0 python FSC_pretrain.py \
    --epochs 500 \
    --warmup_epochs 10 \
    --blr 1.5e-4 --weight_decay 0.05

@inproceedings{zhu2024zero,
  title={Zero-shot Object Counting with Good Exemplars},
  author={Zhu, Huilin and Yuan, Jingling and Yang, Zhengwei and Guo, Yu and Wang, Zheng and Zhong, Xian and He, Shengfeng},
  booktitle={Proceedings of the European Conference on Computer Vision},
  year={2024}
}