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Some improvements (center sample) about FCOS (FCOS: Fully Convolutional One-Stage Object Detection).
| Date | Stars |
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| 2026-07-24 | 325 |
| 2026-07-25 | 325 |
| 2026-07-28 | 325 |
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| 2026-09-20 | 325 |
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# FCOS_PLUS
This project contains some improvements about FCOS (Fully Convolutional One-Stage Object Detection).
## Installation
Please check [INSTALL.md](INSTALL.md) (same as original FCOS) for installation instructions.
**Results**
Model | Total training mem (GB) | Multi-scale training | Testing time / im | AP (minival) | link
--- |:---:|:---:|:---:|:---:|:---:|
FCOS_R_50_FPN_1x | 29.3 | No | 71ms | 37.0 | [model](https://pan.baidu.com/s/1Xcbx7EfOGvwnexXAuovM0A) |
FCOS_R_50_FPN_1x_center | 30.61 | No | 71ms | 37.8 | [model](https://pan.baidu.com/s/1Gs7AzmJRmeYhXUPDQZuSLA) |
FCOS_R_50_FPN_1x_center_liou | 30.61 | No | 71ms | 38.1 | [model](https://pan.baidu.com/s/1HpYrkAsVXNvXRFTd06SGgA) |
FCOS_R_50_FPN_1x_center_giou | 30.61 | No | 71ms | 38.2 | [model](https://pan.baidu.com/s/13_o6343Ikg4td01kVXxGSw) |
FCOS_R_101_FPN_2x | 44.1 | Yes | 74ms | 41.4 | [model](https://pan.baidu.com/s/1u_5OD5NURYe1EYFWnohgEA) |
FCOS_R_101_FPN_2x_center_giou | 44.1 | Yes | 74ms | 42.5 | [model](https://pan.baidu.com/s/1qhHM067ywwlEXfamaFq23g) |
[1] *1x and 2x mean the model is trained for 90K and 180K iterations, respectively.* \
[2] center means [center sample](fcos.pdf) is used in our training. \
[3] liou means the model use linear iou loss function. (1 - iou) \
[4] giou means the use giou loss function. (1 - giou)
## Training
The following command line will train FCOS_R_50_FPN_1x on 8 GPUs with Synchronous Stochastic Gradient Descent (SGD):
python -m torch.distributed.launch \
--nproc_per_node=8 \
--master_port=$((RANDOM + 10000)) \
tools/train_net.py \
--skip-test \
--config-file configs/fcos/fcos_R_50_FPN_1x_center_giou.yaml \
DATALOADER.NUM_WORKERS 2 \
OUTPUT_DIR training_dir/fcos_R_50_FPN_1x_center_giou
Note that:
1) If you want to use fewer GPUs, please change `--nproc_per_node` to the number of GPUs. No other settings need to be changed. The total batch size does not depends on `nproc_per_node`. If you want to change the total batch size, please change `SOLVER.IMS_PER_BATCH` in [configs/fcos/fcos_R_50_FPN_1x_center_giou.yaml](configs/fcos/fcos_R_50_FPN_1x_center_giou.yaml).
2) The models will be saved into `OUTPUT_DIR`.
3) If you want to train FCOS with other backbones, please change `--config-file`.
## Citations
Please consider citing original paper in your publications if the project helps your research.
```
@article{tian2019fcos,
title = {{FCOS}: Fully Convolutional One-Stage Object Detection},
author = {Tian, Zhi and Shen, Chunhua and Chen, Hao and He, Tong},
journal = {arXiv preprint arXiv:1904.01355},
year = {2019}
}
```
## License
For academic use, this project is licensed under the 2-clause BSD License - see the LICENSE file for details. For commercial use, please contact the authors.
Excerpt of 2,843 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:69d89e9af463d6f1, topic:computer-vision, topic:object-detection, desc:object detection