# -c 参数表示指定使用哪个配置文件
# --eval 参数表示边训练边评估,训练过程中会保存验证效果最佳的checkpoint
python tools/train.py -c configs/few-shot/faster_rcnn_r50_vd_fpn_1x_coco_cotuning_roadsign.yml --eval
# -c 参数表示指定使用哪个配置文件
# -o 参数表示指定配置文件中的全局变量(覆盖配置文件中的设置)
python tools/eval.py -c configs/few-shot/faster_rcnn_r50_vd_fpn_1x_coco_cotuning_roadsign.yml \
-o weights=output/faster_rcnn_r50_vd_fpn_1x_coco_cotuning_roadsign/best_model
# -c 参数表示指定使用哪个配置文件
# --infer_img 参数指定预测图像路径
python tools/infer.py -c configs/few-shot/faster_rcnn_r50_vd_fpn_1x_coco_cotuning_roadsign.yml \
--infer_img=demo/road554.png
@article{you2020co,
title={Co-tuning for transfer learning},
author={You, Kaichao and Kou, Zhi and Long, Mingsheng and Wang, Jianmin},
journal={Advances in Neural Information Processing Systems},
volume={33},
pages={17236--17246},
year={2020}
}
@article{khosla2020supervised,
title={Supervised contrastive learning},
author={Khosla, Prannay and Teterwak, Piotr and Wang, Chen and Sarna, Aaron and Tian, Yonglong and Isola, Phillip and Maschinot, Aaron and Liu, Ce and Krishnan, Dilip},
journal={Advances in Neural Information Processing Systems},
volume={33},
pages={18661--18673},
year={2020}
}