A simple, fast, and efficient object detector without FPN.
- This repo provides a neat implementation for YOLOF based on Detectron2. A
cvpods
version can be found in https://github.com/megvii-model/YOLOF.
You Only Look One-level Feature,
Qiang Chen, Yingming Wang, Tong Yang, Xiangyu Zhang, Jian Cheng, Jian Sun
- Our project is developed on detectron2. Please follow the official detectron2 installation.
- Install
mish-cuda
to speed up the training and inference when usingCSPDarkNet-53
as the backbone (optional)git clone https://github.com/thomasbrandon/mish-cuda cd mish-cuda python setup.py build install cd ..
- Install
YOLOF
by:python setup.py develop
- Then link your dataset path to
datasets
cd datasets/ ln -s /path/to/coco coco
- Download the pretrained model in OneDrive or in the Baidu Cloud with code
qr6o
to train with the CSPDarkNet-53 backbone (optional)mkdir pretrained_models # download the `cspdarknet53.pth` to the `pretrained_models` directory
- Train with
yolof
python ./tools/train_net.py --num-gpus 8 --config-file ./configs/yolof_R_50_C5_1x.yaml
- Test with
yolof
python ./tools/train_net.py --num-gpus 8 --config-file ./configs/yolof_R_50_C5_1x.yaml --eval-only MODEL.WEIGHTS /path/to/checkpoint_file
- Note that there might be API changes in future detectron2 releases that make the code incompatible.
The models listed below can be found in this onedrive link or in the BaiduCloud link with code qr6o
.
The FPS is tested on a 2080Ti GPU.
More models will be available in the near future.
Model | COCO val mAP | FPS |
---|---|---|
YOLOF_R_50_C5_1x | 37.7 | 36 |
YOLOF_R_50_DC5_1x | 39.2 | 23 |
YOLOF_R_101_C5_1x | 39.8 | 23 |
YOLOF_R_101_DC5_1x | 40.5 | 17 |
YOLOF_X_101_64x4d_C5_1x | 42.2 | 11 |
YOLOF_CSP_D_53_DC5_3x | 41.2 | 41 |
YOLOF_CSP_D_53_DC5_9x | 42.8 | 41 |
YOLOF_CSP_D_53_DC5_9x_stage2_3x | 43.2 | 41 |
- Note that, the speed reported in this repo is 2~3 FPS faster than the one reported in the cvpods version.
If you find this project useful for your research, please use the following BibTeX entry.
@inproceedings{chen2021you,
title={You Only Look One-level Feature},
author={Chen, Qiang and Wang, Yingming and Yang, Tong and Zhang, Xiangyu and Cheng, Jian and Sun, Jian},
booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
year={2021}
}