2.4 KiB
2.4 KiB
简体中文 | English
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 | config |
| ARSL-FCOS | 5% | 33.1 | 240 (174240) | download | config |
| ARSL-FCOS | 10% | 36.9 | 240 (174240) | download | config |
| ARSL-FCOS | 10% | 38.5(LSJ) | 240 (174240) | download | config |
| ARSL-FCOS | full(100%) | 45.1 | 240 (174240) | download | config |
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
# 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
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
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