ATSS is an advanced adaptive training sample selection method that effectively enhances the performance of both anchor-based and anchor-free object detectors by dynamically choosing positive and negative samples based on the statistical characteristics of objects. The design of ATSS reduces reliance on hyperparameters, simplifies the sample selection process, and significantly improves detection accuracy without adding extra computational costs.
| GPU | IXUCA SDK | Release | Branch |
|---|---|---|---|
| MR-V100 | 4.4.0 | 26.03 | release/26.03 |
| MR-V100 | 4.3.0 | 25.12 | release/25.12 |
Note: 请切换到与您的 SDK 版本对应的 Release 分支进行测试。请勿直接在 master 分支上运行测试，因为 master 分支可能包含与您的本地 SDK 版本不兼容的最新更改。
切换分支命令示例：
git checkout release/26.03
Pretrained model: https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209-985f7bd0.pth
Dataset:
- https://github.com/ultralytics/assets/releases/download/v0.0.0/coco2017labels.zip to download the labels dataset.
- http://images.cocodataset.org/zips/val2017.zip to download the validation dataset.
- http://images.cocodataset.org/zips/train2017.zip to download the train dataset.
unzip -q -d ./ coco2017labels.zip
unzip -q -d ./coco/images/ train2017.zip
unzip -q -d ./coco/images/ val2017.zip
coco
├── annotations
│ └── instances_val2017.json
├── images
│ ├── train2017
│ └── val2017
├── labels
│ ├── train2017
│ └── val2017
├── LICENSE
├── README.txt
├── test-dev2017.txt
├── train2017.cache
├── train2017.txt
├── val2017.cache
└── val2017.txtwget https://download.openmmlab.com/mmdetection/v2.0/atss/atss_r50_fpn_1x_coco/atss_r50_fpn_1x_coco_20200209-985f7bd0.pthContact the Iluvatar administrator to get the missing packages:
- mmcv-*.whl
# Install libGL
## CentOS
yum install -y mesa-libGL
## Ubuntu
apt install -y libgl1-mesa-glx
pip3 install -r requirements.txt# export onnx model
python3 export.py --weight atss_r50_fpn_1x_coco_20200209-985f7bd0.pth --cfg atss_r50_fpn_1x_coco.py --output atss.onnx
# use onnxsim optimize onnx model
onnxsim atss.onnx atss_opt.onnxexport DATASETS_DIR=/Path/to/coco/# Accuracy
bash scripts/infer_atss_fp16_accuracy.sh
# Performance
bash scripts/infer_atss_fp16_performance.sh| Model | BatchSize | Precision | FPS | IOU@0.5 | IOU@0.5:0.95 |
|---|---|---|---|---|---|
| ATSS | 32 | FP16 | 81.671 | 0.541 | 0.367 |