简体中文 | [English](README_en.md) # Ambiguity-Resistant Semi-Supervised Learning for Dense Object Detection (ARSL) ## ARSL-FCOS 模型库 | 模型 | COCO监督数据比例 | Semi mAPval
0.5:0.95 | Semi Epochs (Iters) | 模型下载 | 配置文件 | | :------------: | :---------:|:----------------------------: | :------------------: |:--------: |:----------: | | ARSL-FCOS | 1% | **22.8** | 240 (87120) | [download](https://paddledet.bj.bcebos.com/models/arsl_fcos_r50_fpn_coco_semi001.pdparams) | [config](./arsl_fcos_r50_fpn_coco_semi001.yml) | | ARSL-FCOS | 5% | **33.1** | 240 (174240) | [download](https://paddledet.bj.bcebos.com/models/arsl_fcos_r50_fpn_coco_semi005.pdparams) | [config](./arsl_fcos_r50_fpn_coco_semi005.yml ) | | ARSL-FCOS | 10% | **36.9** | 240 (174240) | [download](https://paddledet.bj.bcebos.com/models/arsl_fcos_r50_fpn_coco_semi010.pdparams) | [config](./arsl_fcos_r50_fpn_coco_semi010.yml ) | | ARSL-FCOS | 10% | **38.5(LSJ)** | 240 (174240) | [download](https://paddledet.bj.bcebos.com/models/arsl_fcos_r50_fpn_coco_semi010_lsj.pdparams) | [config](./arsl_fcos_r50_fpn_coco_semi010_lsj.yml ) | | ARSL-FCOS | full(100%) | **45.1** | 240 (174240) | [download](https://paddledet.bj.bcebos.com/models/arsl_fcos_r50_fpn_coco_full.pdparams) | [config](./arsl_fcos_r50_fpn_coco_full.yml ) | ## 使用说明 仅训练时必须使用半监督检测的配置文件去训练,评估、预测、部署也可以按基础检测器的配置文件去执行。 ### 训练 ```bash # 单卡训练 (不推荐,需按线性比例相应地调整学习率) CUDA_VISIBLE_DEVICES=0 python tools/train.py -c configs/semi_det/arsl/arsl_fcos_r50_fpn_coco_semi010.yml --eval # 多卡训练 python -m paddle.distributed.launch --log_dir=arsl_fcos_r50_fpn_coco_semi010/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/semi_det/arsl/arsl_fcos_r50_fpn_coco_semi010.yml --eval ``` ### 评估 ```bash CUDA_VISIBLE_DEVICES=0 python tools/eval.py -c configs/semi_det/arsl/arsl_fcos_r50_fpn_coco_semi010.yml -o weights=output/arsl_fcos_r50_fpn_coco_semi010/model_final.pdparams ``` ### 预测 ```bash CUDA_VISIBLE_DEVICES=0 python tools/infer.py -c configs/semi_det/arsl/arsl_fcos_r50_fpn_coco_semi010.yml -o weights=output/arsl_fcos_r50_fpn_coco_semi010/model_final.pdparams --infer_img=demo/000000014439.jpg ``` ## 引用 ``` ```