From f8b119358e45c9cc55e311cb28c0433536168c27 Mon Sep 17 00:00:00 2001 From: dengkaipeng Date: Wed, 23 Sep 2020 07:35:27 +0000 Subject: [PATCH] fix typo --- configs/ppyolo/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/configs/ppyolo/README.md b/configs/ppyolo/README.md index f95d14bc7..768a54169 100644 --- a/configs/ppyolo/README.md +++ b/configs/ppyolo/README.md @@ -60,7 +60,7 @@ PP-YOLO improved performance and speed of YOLOv3 with following methods: - TensorRT FP16 inference speed testing exclude the time cost of bounding-box decoding(`yolo_box`) part comparing with FP32 testing above, which means that data reading, bounding-box decoding and post-processing(NMS) is excluded(test method same as [YOLOv4(AlexyAB)](https://github.com/AlexeyAB/darknet) too) - 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 trained with `batch_size=24` in each GPU with memory as 32G, configuation yml with `batch_size=12` which can be trained on GPU with memory as 16G is provided as `ppyolo_2x_bs12.yml`, training with `batch_size=12` reached `mAP(IoU=0.5:0.95) = 45.1%` on COCO val2017 dataset, download weights by [ppyolo_2x_bs12 model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x_bs12.pdparams) +- PP-YOLO trained with `batch_size=24` in each GPU with memory as 32G, configuation yaml with `batch_size=12` which can be trained on GPU with memory as 16G is provided as `ppyolo_2x_bs12.yml`, training with `batch_size=12` reached `mAP(IoU=0.5:0.95) = 45.1%` on COCO val2017 dataset, download weights by [ppyolo_2x_bs12 model](https://paddlemodels.bj.bcebos.com/object_detection/ppyolo_2x_bs12.pdparams) ### PP-YOLO for mobile -- GitLab