update readme, add yoloe (#5705)

README_cn.md

@@ -244,6 +244,7 @@
 - `Cascade-Faster-RCNN`为`Cascade-Faster-RCNN-ResNet50vd-DCN`，PaddleDetection将其优化到COCO数据mAP为47.8%时推理速度为20FPS
 - `PP-YOLO`在COCO数据集精度45.9%，Tesla V100预测速度72.9FPS，精度速度均优于[YOLOv4](https://arxiv.org/abs/2004.10934)
 - `PP-YOLO v2`是对`PP-YOLO`模型的进一步优化，在COCO数据集精度49.5%，Tesla V100预测速度68.9FPS
+- `PP-YOLOE`是对`PP-YOLO v2`模型的进一步优化，在COCO数据集精度51.4%，Tesla V100预测速度78.1FPS
 - 图中模型均可在[模型库](#模型库)中获取
 
 各移动端模型在COCO数据集上精度mAP和高通骁龙865处理器上预测速度(FPS)对比图。

README_en.md

@@ -243,7 +243,7 @@ The relationship between COCO mAP and FPS on Tesla V100 of representative models
 - `PP-YOLO` achieves mAP of 45.9% on COCO and 72.9FPS on Tesla V100. Both precision and speed surpass [YOLOv4](https://arxiv.org/abs/2004.10934)
 
 - `PP-YOLO v2` is optimized version of `PP-YOLO` which has mAP of 49.5% and 68.9FPS on Tesla V100
-
+- `PP-YOLOE` is optimized version of `PP-YOLO v2` which has mAP of 51.4% and 78.1FPS on Tesla V100
 - All these models can be get in [Model Zoo](#ModelZoo)
 
 The relationship between COCO mAP and FPS on Qualcomm Snapdragon 865 of representative mobile side models.