Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection.2021. (in PyTorch)
This repository reproduces "Zhang et al. Discriminative Semantic Feature Pyramid Network with Guided Anchoring for Logo Detection.2021." (DSFP-GA) . The implementation is based on MMDetection framework. All the codes for the DSFP-GA model follow the original paper.
To use this framework, please download it at this link: http://123.57.42.89/Dataset_ict/DSFP-GA.zip
To use this repo, please follow README.md of MMDetection.
- To train baseline (i.e., Faster R-CNN)
python tools/train.py ./configs/dsfp_ga/faster_rcnn_r50_fpn_1x_logo3k.py --work-dir work_dirs/faster_rcnn_r50_fpn_1x_logo3k- To train DSFP-GA
python tools/train.py ./configs/dsfp_ga/dsfp_ga_1x_logo3k.py --work-dir work_dirs/dsfp_ga_1x_logo3k- To test baseline (i.e., Faster R-CNN)
python tools/test.py ./configs/dsfp_ga/faster_rcnn_r50_fpn_1x_logo3k.py work_dirs/faster_rcnn_r50_fpn_1x_logo3k/faster_rcnn_r50_fpn_1x_logo3k.pth --eval mAP- To test DSFP-GA
python tools/test.py ./configs/dsfp_ga/dsfp_ga_1x_logo3k.py work_dirs/dsfp_ga_1x_logo3k/dsfp_ga_1x_logo3k.pth --eval mAPBelow is benchmark results. (extraction code of model : dsfp)
| methods | backbone | mAP | download |
|---|---|---|---|
| Faster R-CNN | ResNet-50-FPN | 83.8 | model |
| DSFP-GA | ResNet-50-DSFP | 87.7 | model |
- Code reorganization is needed to be consistent with the style of MMDetection framework