From e3f860d466e480868c3f27474d51eecb9ced4526 Mon Sep 17 00:00:00 2001
From: Zhao-Yian <77494834+Zhao-Yian@users.noreply.github.com>
Date: Fri, 10 Mar 2023 17:50:43 +0800
Subject: [PATCH] [doc] add README for group detr (#7881)

* [doc] add README for group detr
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 configs/group_detr/README.md | 49 ++++++++++++++++++++++++++++++++++++
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+# Group DETR: Fast DETR training with group-wise one-to-many assignment
+# Group DETR v2: Strong object detector with encoder-decoder pretraining
+
+## Introduction
+
+[Group DETR](https://arxiv.org/pdf/2207.13085.pdf) is an object detection model based on DETR. We reproduced the model of the paper.
+
+[Group DETR v2](https://arxiv.org/pdf/2211.03594.pdf) is a strong object detection model based on DINO and Group DETR. We reproduced the model of the paper.
+
+## Model Zoo
+
+| Backbone |      Model      | Epochs | Resolution |Box AP |                 Config                  |                                     Download                                     |
+|:------:|:---------------:|:------:|:------:|:---------------------------------------:|:--------------------------------------------------------------------------------:|:------:|
+| R-50 | dino_r50_4scale |   12   | (800, 1333) |  49.6  | [config](./group_dino_r50_4scale_1x_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/group_dino_r50_4scale_1x_coco.pdparams) |
+| Vit-huge | dino_vit_huge_4scale |   12   | (1184, 2000) | 63.3  | [config](./group_dino_vit_huge_4scale_1x_coco.yml) | [model](https://bj.bcebos.com/v1/paddledet/models/group_dino_vit_huge_4scale_1x_coco.pdparams) |
+
+**Notes:**
+
+- Group DETR is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
+- Group DETRv2 requires a ViT-Huge encoder pre-trained and fine-tuned on ImageNet-1K in a self-supervised manner, a detector pre-trained on Object365, and finally it is fine-tuned on trainCOCO. Group DETRv2 is also evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
+- Group DETR and Group DETRv2 are both use 4GPU to train.
+
+GPU multi-card training
+```bash
+python -m paddle.distributed.launch --gpus 0,1,2,3 tools/train.py -c configs/group_detr/group_dino_r50_4scale_1x_coco.yml --fleet --eval
+```
+
+```bash
+python -m paddle.distributed.launch --gpus 0,1,2,3 tools/train.py -c configs/group_detr/group_dino_vit_huge_4scale_1x_coco.yml --fleet --eval
+```
+
+## Citations
+```
+@article{chen2022group,
+  title={Group DETR: Fast DETR training with group-wise one-to-many assignment},
+  author={Chen, Qiang and Chen, Xiaokang and Wang, Jian and Feng, Haocheng and Han, Junyu and Ding, Errui and Zeng, Gang and Wang, Jingdong},
+  journal={arXiv preprint arXiv:2207.13085},
+  volume={1},
+  number={2},
+  year={2022}
+}
+
+@article{chen2022group,
+  title={Group DETR v2: Strong object detector with encoder-decoder pretraining},
+  author={Chen, Qiang and Wang, Jian and Han, Chuchu and Zhang, Shan and Li, Zexian and Chen, Xiaokang and Chen, Jiahui and Wang, Xiaodi and Han, Shuming and Zhang, Gang and others},
+  journal={arXiv preprint arXiv:2211.03594},
+  year={2022}
+}
+```
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