[ppyoloe-plus] add task reademe and base config, test=document_fix (#6722)

* [ppyoloe-plus] add downstream tasks

* [ppyoloe-plus] add task reademe and base config, test=document_fix

* [ppyoloe-plus] fix config

* Update README.md

* [ppyoloe+] fix readne and name, test=document_fix

* [ppyoloe+] fix base cofig

configs/ppyoloe/application/README.md

+# PP-YOLOE+ 下游任务
+
+我们验证了PP-YOLOE+模型强大的泛化能力，在农业、低光、工业等不同场景下游任务检测效果稳定提升!
+
+农业数据集采用[Embrapa WGISD](https://github.com/thsant/wgisd)，该数据集用于葡萄栽培中基于图像的监测和现场机器人技术，提供了来自5种不同葡萄品种的实地实例，
+处理后的COCO格式，包含图片训练集242张，测试集58张，5个类别，[Embrapa WGISD COCO格式下载](https://bj.bcebos.com/v1/paddledet/data/wgisd.zip)；
+
+低光数据集使用[ExDark](https://github.com/cs-chan/Exclusively-Dark-Image-Dataset/tree/master/Dataset)，该数据集是一个专门在低光照环境下拍摄出针对低光目标检测的数据集，包括从极低光环境到暮光环境等10种不同光照条件下的图片，
+处理后的COCO格式，包含图片训练集5891张，测试集1472张，12个类别，[ExDark COCO格式下载](https://bj.bcebos.com/v1/paddledet/data/Exdark.zip)；
+
+工业数据集使用[PKU-Market-PCB](https://robotics.pkusz.edu.cn/resources/dataset/)，该数据集用于印刷电路板（PCB）的瑕疵检测，提供了6种常见的PCB缺陷，
+处理后的COCO格式，包含图片训练集555张，测试集138张，6个类别，[PKU-Market-PCB COCO格式下载](https://bj.bcebos.com/v1/paddledet/data/PCB_coco.zip)。
+
+
+## 实验结果：
+
+|    模型  |       数据集     | mAP<sup>val<br>0.5:0.95 |  下载链接  | 配置文件 |
+|:---------|:---------------:|:-----------------------:|:---------:| :-----: |
+|PP-YOLOE_m|   Embrapa WGISD  |  52.7 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_80e_wgisd.pdparams) | [配置文件](./ppyoloe_crn_m_80e_wgisd.yml) |
+|PP-YOLOE+_m<br>(obj365_pretrained)|   Embrapa WGISD  |  60.8(+8.1) | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_obj365_pretrained_wgisd.pdparams) | [配置文件](./ppyoloe_plus_crn_m_80e_obj365_pretrained_wgisd.yml) |
+|PP-YOLOE+_m<br>(coco_pretrained)|   Embrapa WGISD  |  59.7(+7.0) | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_coco_pretrained_wgisd.pdparams) | [配置文件](./ppyoloe_plus_crn_m_80e_coco_pretrained_wgisd.yml) |
+|PP-YOLOE_m|      ExDark      |  56.4 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_80e_exdark.pdparams) | [配置文件](./ppyoloe_crn_m_80e_exdark.yml) |
+|PP-YOLOE+_m<br>(obj365_pretrained)|   ExDark  |  57.7(+1.3) | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_obj365_pretrained_exdark.pdparams) | [配置文件](./ppyoloe_plus_crn_m_80e_obj365_pretrained_exdark.yml) |
+|PP-YOLOE+_m<br>(coco_pretrained)|   ExDark  |  58.1(+1.7) | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_coco_pretrained_exdark.pdparams) | [配置文件](./ppyoloe_plus_crn_m_80e_coco_pretrained_exdark.yml) |
+|PP-YOLOE_m|      PKU-Market-PCB      |  50.8 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_80e_pcb.pdparams) | [配置文件](./ppyoloe_crn_m_80e_pcb.yml) |
+|PP-YOLOE+_m<br>(obj365_pretrained)|   PKU-Market-PCB  |  52.7(+1.9) | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_obj365_pretrained_pcb.pdparams) | [配置文件](./ppyoloe_plus_crn_m_80e_obj365_pretrained_pcb.yml) |
+|PP-YOLOE+_m<br>(coco_pretrained)|   PKU-Market-PCB  |  52.4(+1.6) | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_m_80e_coco_pretrained_pcb.pdparams) | [配置文件](./ppyoloe_plus_crn_m_80e_coco_pretrained_pcb.yml) |
+
+**注意:**
+- PP-YOLOE模型训练过程中使用8 GPUs进行训练，如果**GPU卡数**或者**batch size**发生了改变，你需要按照公式 **lr<sub>new</sub> = lr<sub>default</sub> * (batch_size<sub>new</sub> * GPU_number<sub>new</sub>) / (batch_size<sub>default</sub> * GPU_number<sub>default</sub>)** 调整学习率。
+- 具体使用教程请参考[ppyoloe](../ppyoloe#getting-start)。  
+
+
+
+
+
+## 引用
+```
+@article{Exdark,
+title={Getting to Know Low-light Images with The Exclusively Dark Dataset},
+author={Loh, Yuen Peng and Chan, Chee Seng},
+journal={Computer Vision and Image Understanding},
+volume={178},
+pages={30-42},
+year={2019},
+doi={https://doi.org/10.1016/j.cviu.2018.10.010}
+}
+```

configs/ppyoloe/application/_base_/exdark_detection.yml

+metric: COCO
+num_classes: 12
+
+TrainDataset:
+  !COCODataSet
+    image_dir: images
+    anno_path: coco_annotations/train.json
+    dataset_dir: dataset/Exdark/
+    data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']
+
+EvalDataset:
+  !COCODataSet
+    image_dir: images
+    anno_path: coco_annotations/val.json
+    dataset_dir: dataset/Exdark/
+
+TestDataset:
+  !ImageFolder
+    anno_path: coco_annotations/val.json # also support txt (like VOC's label_list.txt)
+    dataset_dir: dataset/Exdark/ # if set, anno_path will be 'dataset_dir/anno_path'

configs/ppyoloe/application/_base_/pcb_detection.yml

+metric: COCO
+num_classes: 6
+
+TrainDataset:
+  !COCODataSet
+    image_dir: images
+    anno_path: pcb_cocoanno/train.json
+    dataset_dir: dataset/PCB_coco/
+    data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']
+
+EvalDataset:
+  !COCODataSet
+    image_dir: images
+    anno_path: pcb_cocoanno/val.json
+    dataset_dir: dataset/PCB_coco/
+
+TestDataset:
+  !ImageFolder
+    anno_path: pcb_cocoanno/val.json # also support txt (like VOC's label_list.txt)
+    dataset_dir: dataset/PCB_coco/ # if set, anno_path will be 'dataset_dir/anno_path'

configs/ppyoloe/application/_base_/wgisd_detection.yml

+metric: COCO
+num_classes: 5
+
+TrainDataset:
+  !COCODataSet
+    image_dir: data
+    anno_path: coco_annotations/new_train_bbox_instances.json
+    dataset_dir: dataset/wgisd/
+    data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd']
+
+EvalDataset:
+  !COCODataSet
+    image_dir: data
+    anno_path: coco_annotations/new_test_bbox_instances.json
+    dataset_dir: dataset/wgisd/
+
+TestDataset:
+  !ImageFolder
+    anno_path: coco_annotations/new_test_bbox_instances.json # also support txt (like VOC's label_list.txt)
+    dataset_dir: dataset/wgisd/ # if set, anno_path will be 'dataset_dir/anno_path'

configs/ppyoloe/application/ppyoloe_crn_m_80e_exdark.yml

+_BASE_: [
+  './_base_/exdark_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../legacy_model/_base_/ppyoloe_crn.yml',
+  '../legacy_model/_base_/ppyoloe_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_crn_m_80e_exdark/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_300e_coco.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_crn_m_80e_pcb.yml

+_BASE_: [
+  './_base_/pcb_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../legacy_model/_base_/ppyoloe_crn.yml',
+  '../legacy_model/_base_/ppyoloe_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_crn_m_80e_pcb/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_300e_coco.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_crn_m_80e_wgisd.yml

+_BASE_: [
+  './_base_/wgisd_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../legacy_model/_base_/ppyoloe_crn.yml',
+  '../legacy_model/_base_/ppyoloe_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_crn_m_80e_wgisd/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_m_300e_coco.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_plus_crn_m_80e_coco_pretrained_exdark.yml

+_BASE_: [
+  './_base_/exdark_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../_base_/ppyoloe_plus_crn.yml',
+  '../_base_/ppyoloe_plus_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_plus_crn_m_80e_coco_pretrained_exdark/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_plus_crn_m_80e_coco_pretrained_pcb.yml

+_BASE_: [
+  './_base_/pcb_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../_base_/ppyoloe_plus_crn.yml',
+  '../_base_/ppyoloe_plus_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_plus_crn_m_80e_coco_pretrained_pcb/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_plus_crn_m_80e_coco_pretrained_wgisd.yml

+_BASE_: [
+  './_base_/wgisd_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../_base_/ppyoloe_plus_crn.yml',
+  '../_base_/ppyoloe_plus_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_plus_crn_m_80e_coco_pretrained_wgisd/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_m_80e_coco.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_plus_crn_m_80e_obj365_pretrained_exdark.yml

+_BASE_: [
+  './_base_/exdark_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../_base_/ppyoloe_plus_crn.yml',
+  '../_base_/ppyoloe_plus_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_plus_crn_m_80e_obj365_pretrained_exdark/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_plus_crn_m_80e_obj365_pretrained_pcb.yml

+_BASE_: [
+  './_base_/pcb_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../_base_/ppyoloe_plus_crn.yml',
+  '../_base_/ppyoloe_plus_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_plus_crn_m_80e_obj365_pretrained_pcb/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams
+depth_mult: 0.67
+width_mult: 0.75

configs/ppyoloe/application/ppyoloe_plus_crn_m_80e_obj365_pretrained_wgisd.yml

+_BASE_: [
+  './_base_/wgisd_detection.yml',
+  '../../runtime.yml',
+  '../_base_/optimizer_80e.yml',
+  '../_base_/ppyoloe_plus_crn.yml',
+  '../_base_/ppyoloe_plus_reader.yml',
+]
+
+log_iter: 100
+snapshot_epoch: 5
+weights: output/ppyoloe_plus_crn_m_80e_obj365_pretrained_wgisd/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/pretrained/ppyoloe_crn_m_obj365_pretrained.pdparams
+depth_mult: 0.67
+width_mult: 0.75