Library of Detection with Transformer
- We recommend you to use Anaconda to create a conda environment:
conda create -n detr python=3.6- Then, activate the environment:
conda activate detr- Requirements:
pip install -r requirements.txt We suggest that PyTorch should be higher than 1.9.0 and Torchvision should be higher than 0.10.3. At least, please make sure your torch is version 1.x.
In this repository, you can enjoy:
- DETR
- Anchor-DETR
- DINO
I evaluate DETR by loading official pretrained weight.
| Model | backbone | FPS 3090 |
FLOPs | Params | AP | Weight |
|---|---|---|---|---|---|---|
| DETR-R50 | R-50 | 37 | 95.2 B | 36.7 M | 41.7 | github |
| DETR-R50-DC5 | R-50 | 20 | 162.1 B | 36.7 M | 43.0 | github |
| DETR-R101 | R-101 | 25 | 174.7 B | 55.7 M | 43.1 | github |
| DETR-R101-DC5 | R-101 | 14 | 241.6 B | 55.7 M | 44.3 | github |
I evaluate AnchorDETR by loading official pretrained weight.
| Model | backbone | FPS 3090 |
FLOPs | Params | AP | Weight |
|---|---|---|---|---|---|---|
| Anchor-DETR-R50 | R-50 | 37 | 97.0 B | 30.7 M | 42.1 | github |
| Anchor-DETR-R50-DC5 | R-50 | 20 | 154.0 B | 30.7 M | 44.2 | github |
| Anchor-DETR-R101 | R-101 | 21 | 176.5 B | 49.7 M | 43.5 | github |
| Anchor-DETR-R101-DC5 | R-101 | 16 | 233.5 B | 49.7 M | 45.2 | github |
sh train.shYou can change the configurations of train.sh, according to your own situation.
However, limited by my GPU, I can't verify whether this repository can reproduce the performance of the official DETR.
python test.py -d coco \
--cuda \
-v detr_r50 \
--weight path/to/weight \
--root path/to/dataset/ \
--showpython eval.py -d coco-val \
--cuda \
-v detr_r50 \
--weight path/to/weight \
--root path/to/dataset/I have provide some images in data/demo/images/, so you can run following command to run a demo:
python demo.py --mode image \
--path_to_img dataset/demo/images/ \
-v detr_r50 \
--cuda \
--weight path/to/weight \
--showIf you want run a demo of streaming video detection, you need to set --mode to video, and give the path to video --path_to_vidใ
python demo.py --mode video \
--path_to_img dataset/demo/videos/video_name \
-v detr_r50 \
--cuda \
--weight path/to/weight \
--showIf you want run video detection with your camera, you need to set --mode to cameraใ
python demo.py --mode camera \
-v detr_r50 \
--cuda \
--weight path/to/weight \
--show
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