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add rtdetr final #8094
add rtdetr final #8094
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lyuwenyu
commented
Apr 18, 2023
- add pp rt-detr
add yoloe reader alter reference points to unsigmoid add 3_0_6_neck_256 base fix amp training alter usage in paddle-inference update new base alter ext_ops add hybrid encoder
Thanks for your contribution! |
value_spatial_shapes, | ||
value_level_start_index, | ||
value_mask=None): | ||
""" |
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说明下和基类的差异
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@register | ||
class PPDETRTransformer(nn.Layer): |
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改为RTDETR?
DETR: | ||
backbone: ResNet | ||
neck: HybridEncoder | ||
transformer: PPDETRTransformer |
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PPDETR->RTDETR
configs/rtdetr/README.md
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# DETRs Beat YOLOs on Real-time Object Detection | ||
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## Introduction | ||
We propose a **R**eal-**T**ime **DE**tection **TR**ansformer (RT-DETR), the first real-time end-to-end object detector to our best knowledge. Specifically, we design an efficient hybrid encoder to efficiently process multi-scale features by decoupling the intra-scale interaction and cross-scale fusion, and propose IoU-aware query selection to improve the initialization of object queries. In addition, our proposed detector supports flexibly adjustment of the inference speed by using different decoder layers without the need for retraining, which facilitates the practical application of real-time object detectors. Our RT-DETR-L achieves 53.0% AP on COCO val2017 and 114 FPS on T4 GPU, while RT-DETR-X achieves 54.8% AP and 74 FPS, outperforming all YOLO detectors of the same scale in both speed and accuracy. Furthermore, our RT-DETR-R50 achieves 53.1% AP and 108 FPS, outperforming DINO-Deformable-DETR-R50 by 2.2% AP in accuracy and by about 21 times in FPS. |
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可以加下arxiv链接,test集数据也加下吧
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checkpoint、模型能转换成TRT engine么 |