更换文档检测模型

paddle_detection/configs/detr/README.md

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+# DETR
+
+## Introduction
+
+
+DETR is an object detection model based on transformer. We reproduced the model of the paper.
+
+
+## Model Zoo
+
+| Backbone | Model | Images/GPU  | Inf time (fps) | Box AP | Config | Download |
+|:------:|:--------:|:--------:|:--------------:|:------:|:------:|:--------:|
+| R-50 | DETR  | 4 | --- | 42.3 | [config](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/detr/detr_r50_1x_coco.yml) | [model](https://paddledet.bj.bcebos.com/models/detr_r50_1x_coco.pdparams) |
+
+**Notes:**
+
+- DETR is trained on COCO train2017 dataset and evaluated on val2017 results of `mAP(IoU=0.5:0.95)`.
+- DETR uses 8GPU to train 500 epochs.
+
+GPU multi-card training
+```bash
+export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
+python -m paddle.distributed.launch --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/detr/detr_r50_1x_coco.yml --fleet
+```
+
+## Citations
+```
+@inproceedings{detr,
+  author    = {Nicolas Carion and
+               Francisco Massa and
+               Gabriel Synnaeve and
+               Nicolas Usunier and
+               Alexander Kirillov and
+               Sergey Zagoruyko},
+  title     = {End-to-End Object Detection with Transformers},
+  booktitle = {ECCV},
+  year      = {2020}
+}
+```