@@ -61,16 +61,16 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods:
- YOLOv4(AlexyAB) performance and inference speed is copy from single Tesla V100 testing results in [YOLOv4 github repo](https://github.com/AlexeyAB/darknet), Tesla V100 TensorRT FP16 inference speed is testing with tkDNN configuration and TensorRT 5.1.2.2 on single Tesla V100 based on [AlexyAB/darknet repo](https://github.com/AlexeyAB/darknet).
- Download and configuration of YOLOv4(AlexyAB) is reproduced model of YOLOv4 in PaddleDetection, whose evaluation performance is same as YOLOv4(AlexyAB), and finetune training is supported in PaddleDetection currently, reproducing by training from backbone pretrain weights is on working, see [PaddleDetection YOLOv4](../yolov4/README.md) for details.
- PP-YOLO tiny is trained on COCO train2017 datast and evaluated on val2017 & test-dev2017 dataset，Box AP50<sup>val</sup> is evaluation results of `mAP(IoU=0.5)`.
- PP-YOLO tiny used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](../../docs/FAQ.md).
- PP-YOLO tiny inference speeding testing environment and configuration is same as PP-YOLO above.
- PP-YOLO_r18vd is trained on COCO train2017 datast and evaluated on val2017 & test-dev2017 dataset，Box AP50<sup>val</sup> is evaluation results of `mAP(IoU=0.5)`.
- PP-YOLO_r18vd used 4 GPUs for training and mini-batch size as 32 on each GPU, if GPU number and mini-batch size is changed, learning rate and iteration times should be adjusted according [FAQ](../../docs/FAQ.md).
- PP-YOLO_r18vd inference speeding testing environment and configuration is same as PP-YOLO above.
