From f938b269dc0e66357c3861dffeb4748a87d8d6ca Mon Sep 17 00:00:00 2001 From: Feng Ni Date: Wed, 18 Jan 2023 22:09:47 +0800 Subject: [PATCH] update docs for yolov8 and yolov6 3.0, test=document_fix (#7633) --- README_cn.md | 33 ++++++---- README_en.md | 19 ++++-- docs/MODEL_ZOO_cn.md | 8 ++- docs/MODEL_ZOO_en.md | 8 ++- docs/feature_models/PaddleYOLO_MODEL.md | 74 +++++++++++++++------- docs/feature_models/PaddleYOLO_MODEL_en.md | 63 ++++++++++++------ 6 files changed, 138 insertions(+), 67 deletions(-) diff --git a/README_cn.md b/README_cn.md index c29a434b3..3b121c478 100644 --- a/README_cn.md +++ b/README_cn.md @@ -86,6 +86,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能 - 新增[少样本迁移学习](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/few-shot); - 新增[半监督检测模型](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/semi_det); - 新增[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8); + - 更新[YOLOv6-v3.0](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6); - [🎗️产业特色模型|产业工具](#️产业特色模型产业工具-1)： - 发布**旋转框检测模型**[PP-YOLOE-R](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/rotate/ppyoloe_r)：Anchor-free旋转框检测SOTA模型，精度速度双高、云边一体，s/m/l/x四个模型适配不用算力硬件、部署友好，避免使用特殊算子，能够轻松使用TensorRT加速； - 发布**小目标检测模型**[PP-YOLOE-SOD](https://github.com/PaddlePaddle/PaddleDetection/tree/develop/configs/smalldet)：基于切图的端到端检测方案、基于原图的检测模型，精度达VisDrone开源最优； @@ -116,7 +117,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能 - **⚽️2022卡塔尔世界杯专题** - `文章传送门`：[世界杯决赛号角吹响！趁周末来搭一套足球3D+AI量化分析系统吧！](https://mp.weixin.qq.com/s/koJxjWDPBOlqgI-98UsfKQ) - +

@@ -124,7 +125,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能 - **🔍旋转框小目标检测专题** - `文章传送门`：[Yes, PP-YOLOE！80.73mAP、38.5mAP，旋转框、小目标检测能力双SOTA！](https://mp.weixin.qq.com/s/6ji89VKqoXDY6SSGkxS8NQ) - +

@@ -258,10 +259,10 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
  • Common
      • -
        +
        • Sync-BN
        • Group Norm
        • DCNv2
          • @@ -350,13 +351,13 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
        • Cascade-RCNN
        • PSS-Det
        • RetinaNet
          • -
        • YOLOv3
          • -
        • YOLOv5
          • -
        • YOLOX
          • -
        • YOLOv6
          • -
        • YOLOv7
          • -
        • YOLOv8
          • -
        • RTMDet
          • +
        • YOLOv3
          • +
        • YOLOX
          • +
        • YOLOv5
          • +
        • YOLOv6
          • +
        • YOLOv7
          • +
        • YOLOv8
          • +
        • RTMDet
        • PP-YOLO
        • PP-YOLO-Tiny
        • PP-PicoDet
          • @@ -368,6 +369,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能
        • SSD
        • CenterNet
        • FCOS
          • +
        • FCOSR
        • TTFNet
        • TOOD
        • GFL
          • @@ -468,7 +470,7 @@ PaddleDetection整理工业、农业、林业、交通、医疗、金融、能 - 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-YOLOE是对PP-YOLO v2模型的进一步优化，L版本在COCO数据集mAP为51.6%，Tesla V100预测速度78.1FPS - PP-YOLOE+是对PPOLOE模型的进一步优化，L版本在COCO数据集mAP为53.3%，Tesla V100预测速度78.1FPS -- YOLOX和YOLOv5均为基于PaddleDetection复现算法，YOLOv5代码在PaddleYOLO中，参照PaddleYOLO_MODEL +- YOLOX和YOLOv5均为基于PaddleDetection复现算法，YOLOv5代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，参照[PaddleYOLO_MODEL](docs/feature_models/PaddleYOLO_MODEL.md) - 图中模型均可在[📱模型库](#模型库)中获取 @@ -805,4 +807,7 @@ PP-Vehicle囊括四大交通场景核心功能：车牌识别、属性识别、 @misc{ppdet2019, title={PaddleDetection, Object detection and instance segmentation toolkit based on PaddlePaddle.}, author={PaddlePaddle Authors}, -howpublished = {\url{https://github.com/PaddlePaddle/PaddleDetection}}, \ No newline at end of file +howpublished = {\url{https://github.com/PaddlePaddle/PaddleDetection}}, +year={2019} +} +``` diff --git a/README_en.md b/README_en.md index 0811e4fb0..9dabc734a 100644 --- a/README_en.md +++ b/README_en.md @@ -17,7 +17,7 @@
    - +
    @@ -47,7 +47,7 @@ - 💡 Cutting-edge algorithms： - - Release [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO) which overs classic and latest models of [YOLO family](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/docs/MODEL_ZOO_en.md): YOLOv3, PP-YOLOE (a real-time high-precision object detection model developed by Baidu PaddlePaddle), and cutting-edge detection algorithms such as YOLOv4, YOLOv5, YOLOX, YOLOv6, and YOLOv7 + - Release [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO) which overs classic and latest models of [YOLO family](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/docs/MODEL_ZOO_en.md): YOLOv3, PP-YOLOE (a real-time high-precision object detection model developed by Baidu PaddlePaddle), and cutting-edge detection algorithms such as YOLOv4, YOLOv5, YOLOX, YOLOv6, YOLOv7 and YOLOv8 - Newly add high precision detection model based on [ViT](configs/vitdet) backbone network, with a 55.7% mAP accuracy on COCO dataset; newly add multi-object tracking model [OC-SORT](configs/mot/ocsort); newly add [ConvNeXt](configs/convnext) backbone network. - 📋 Industrial applications: Newly add [Smart Fitness](https://aistudio.baidu.com/aistudio/projectdetail/4385813), [Fighting recognition](https://aistudio.baidu.com/aistudio/projectdetail/4086987?channelType=0&channel=0),[ and Visitor Analysis](https://aistudio.baidu.com/aistudio/projectdetail/4230123?channelType=0&channel=0). @@ -118,13 +118,20 @@
  • PSS-Det
  • RetinaNet
  • YOLOv3
    • -
  • PP-YOLOv1/v2
    • +
  • YOLOX
    • +
  • YOLOv5
    • +
  • YOLOv6
    • +
  • YOLOv7
    • +
  • YOLOv8
    • +
  • RTMDet
    • +
  • PP-YOLO
  • PP-YOLO-Tiny
    • +
  • PP-PicoDet
    • +
  • PP-YOLOv2
  • PP-YOLOE
  • PP-YOLOE+
    • -
  • PP-YOLOE-R
  • PP-YOLOE-SOD
    • -
  • YOLOX
    • +
  • PP-YOLOE-R
  • SSD
  • CenterNet
  • FCOS
    • @@ -132,7 +139,7 @@
  • TTFNet
  • TOOD
  • GFL
    • -
  • PP-PicoDet
    • +
  • GFLv2
  • DETR
  • Deformable DETR
  • Swin Transformer
    • diff --git a/docs/MODEL_ZOO_cn.md b/docs/MODEL_ZOO_cn.md index 8ff9507ef..c6c76e970 100644 --- a/docs/MODEL_ZOO_cn.md +++ b/docs/MODEL_ZOO_cn.md @@ -28,7 +28,7 @@ ## 通用设置 - 所有模型均在COCO17数据集中训练和测试。 -- [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)、[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)和[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)这3类模型的代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，**PaddleYOLO库开源协议为GPL 3.0**。 +- [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5)、[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6)、[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7)和[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8)这几类模型的代码在[PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO)中，**PaddleYOLO库开源协议为GPL 3.0**。 - 除非特殊说明，所有ResNet骨干网络采用[ResNet-B](https://arxiv.org/pdf/1812.01187)结构。 - **推理时间(fps)**: 推理时间是在一张Tesla V100的GPU上通过'tools/eval.py'测试所有验证集得到，单位是fps(图片数/秒), cuDNN版本是7.5，包括数据加载、网络前向执行和后处理, batch size是1。 @@ -167,7 +167,7 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 请参考[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5) -### YOLOv6 +### YOLOv6(v3.0) 请参考[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) @@ -175,6 +175,10 @@ Paddle提供基于ImageNet的骨架网络预训练模型。所有预训练模型 请参考[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) +### YOLOv8 + +请参考[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8) + ### RTMDet 请参考[RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet) diff --git a/docs/MODEL_ZOO_en.md b/docs/MODEL_ZOO_en.md index 999144c2e..e80b95905 100644 --- a/docs/MODEL_ZOO_en.md +++ b/docs/MODEL_ZOO_en.md @@ -28,7 +28,7 @@ ## General Settings - All models were trained and tested in the COCO17 dataset. -- The codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) and [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) can be found in [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO). Note that **the LICENSE of PaddleYOLO is GPL 3.0**. +- The codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) and [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8) can be found in [PaddleYOLO](https://github.com/PaddlePaddle/PaddleYOLO). Note that **the LICENSE of PaddleYOLO is GPL 3.0**. - Unless special instructions, all the ResNet backbone network using [ResNet-B](https://arxiv.org/pdf/1812.01187) structure. - **Inference time (FPS)**: The reasoning time was calculated on a Tesla V100 GPU by `tools/eval.py` testing all validation sets in FPS (number of pictures/second). CuDNN version is 7.5, including data loading, network forward execution and post-processing, and Batch size is 1. @@ -166,7 +166,7 @@ Please refer to [Model Zoo for PaddleYOLO](https://github.com/PaddlePaddle/Paddl Please refer to [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov5) -### YOLOv6 +### YOLOv6(v3.0) Please refer to [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov6) @@ -174,6 +174,10 @@ Please refer to [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop Please refer to [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov7) +### YOLOv8 + +Please refer to [YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/yolov8) + ### RTMDet Please refer to [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/develop/configs/rtmdet) diff --git a/docs/feature_models/PaddleYOLO_MODEL.md b/docs/feature_models/PaddleYOLO_MODEL.md index e63580a0a..eb7db7109 100644 --- a/docs/feature_models/PaddleYOLO_MODEL.md +++ b/docs/feature_models/PaddleYOLO_MODEL.md @@ -5,11 +5,12 @@ ## 内容 - [简介](#简介) - [模型库](#模型库) - - [PP-YOLOE+](#PP-YOLOE+) + - [PP-YOLOE](#PP-YOLOE) - [YOLOX](#YOLOX) - [YOLOv5](#YOLOv5) - [YOLOv6](#YOLOv6) - [YOLOv7](#YOLOv7) + - [YOLOv8](#YOLOv8) - [RTMDet](#RTMDet) - [VOC](#VOC) - [使用指南](#使用指南) @@ -18,9 +19,10 @@ ## 简介 -**PaddleYOLO**是基于[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)的YOLO系列模型库，**只包含YOLO系列模型的相关代码**，支持`YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`RTMDet`等模型，欢迎一起使用和建设！ +**PaddleYOLO**是基于[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)的YOLO系列模型库，**只包含YOLO系列模型的相关代码**，支持`YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`YOLOv8`,`RTMDet`等模型，欢迎一起使用和建设！ ## 更新日志 +* 【2022/01/10】支持[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)预测和部署； * 【2022/09/29】支持[RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)预测和部署； * 【2022/09/26】发布[`PaddleYOLO`](https://github.com/PaddlePaddle/PaddleYOLO)模型套件； * 【2022/09/19】支持[`YOLOv6`](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)新版，包括n/t/s/m/l模型； @@ -28,7 +30,7 @@ **注意:** - - **PaddleYOLO**代码库协议为**GPL 3.0**，[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)和[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6)这3类模型代码不合入[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)，其余YOLO模型推荐在[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)中使用，**会最先发布PP-YOLO系列特色检测模型的最新进展**；； + - **PaddleYOLO**代码库协议为**GPL 3.0**，[YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7)和[YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)这几类模型代码不合入[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)，其余YOLO模型推荐在[PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection)中使用，**会最先发布PP-YOLO系列特色检测模型的最新进展**；； - **PaddleYOLO**代码库**推荐使用paddlepaddle-2.3.2以上的版本**，请参考[官网](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html)下载对应适合版本，**Windows平台请安装paddle develop版本**； - PaddleYOLO 的[Roadmap](https://github.com/PaddlePaddle/PaddleYOLO/issues/44) issue用于收集用户的需求，欢迎提出您的建议和需求。 - 训练**自定义数据集**请参照[文档](#自定义数据集)和[issue](https://github.com/PaddlePaddle/PaddleYOLO/issues/43)。请首先**确保加载了COCO权重作为预训练**，YOLO检测模型建议**总`batch_size`至少大于`64`**去训练，如果资源不够请**换小模型**或**减小模型的输入尺度**，为了保障较高检测精度，**尽量不要尝试单卡训和总`batch_size`小于`32`训**； @@ -36,7 +38,7 @@ ## 模型库 -### [PP-YOLOE+](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe) +### [PP-YOLOE](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe)
    基础模型 @@ -147,13 +149,10 @@ | 网络网络 | 输入尺寸 | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) | mAP | AP50 | Params(M) | FLOPs(G) | 下载链接 | 配置文件 | | :------------- | :------- | :-------: | :------: | :---------: | :-----: |:-----: | :-----: |:-----: | :-------------: | :-----: | -| YOLOv6-n | 416 | 32 | 400e | 1.0 | 31.1 | 45.3 | 4.74 | 5.16 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_416_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_416_400e_coco.yml) | -| YOLOv6-n | 640 | 32 | 400e | 1.3 | 36.1 | 51.9 | 4.74 | 12.21 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_400e_coco.yml) | -| *YOLOv6-t | 640 | 32 | 400e | 2.1 | 40.7 | 57.4 | 10.63 | 27.29 |[model](https://paddledet.bj.bcebos.com/models/yolov6_t_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_t_400e_coco.yml) | -| *YOLOv6-s | 640 | 32 | 400e | 2.6 | 43.4 | 60.5 | 18.87 | 48.35 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_400e_coco.yml) | -| *YOLOv6-m | 640 | 32 | 300e | 5.0 | 49.0 | 66.5 | 37.17 | 88.82 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) | -| *YOLOv6-l | 640 | 32 | 300e | 7.9 | 51.0 | 68.9 | 63.54 | 155.89 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) | -| *YOLOv6-l-silu | 640 | 32 | 300e | 9.6 | 51.7 | 69.6 | 58.59 | 142.66 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_silu_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_silu_300e_coco.yml) | +| *YOLOv6-n | 640 | 16 | 300e(+300e) | 2.0 | 37.5 | 53.1 | 5.07 | 12.49 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_300e_coco.yml) | +| *YOLOv6-s | 640 | 32 | 300e(+300e) | 2.7 | 44.8 | 61.7 | 20.18 | 49.36 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_300e_coco.yml) | +| *YOLOv6-m | 640 | 32 | 300e(+300e) | - | 49.5 | 66.9 | 37.74 | 92.47 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) | +| *YOLOv6-l(silu) | 640 | 32 | 300e(+300e) | - | 52.2 | 70.2 | 59.66 | 149.4 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) |
    @@ -162,13 +161,10 @@ | 网络模型 | 输入尺寸 | 导出后的权重(w/o NMS) | ONNX(w/o NMS) | | :-------- | :--------: | :---------------------: | :----------------: | -| yolov6-n | 416 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.onnx) | -| yolov6-n | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.onnx) | -| yolov6-t | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.onnx) | -| yolov6-s | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.onnx) | -| yolov6-m | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) | -| yolov6-l | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) | -| yolov6-l-silu | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.onnx) | +| yolov6-n | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.onnx) | +| yolov6-s | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.onnx) | +| yolov6-m | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) | +| yolov6-l(silu) | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) | @@ -208,6 +204,37 @@ + +### [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) + +
    + 基础模型 + +| 网络网络 | 输入尺寸 | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) | mAPval
    0.5:0.95 | mAPval
    0.5 | Params(M) | FLOPs(G) | 下载链接 | 配置文件 | +| :------------- | :------- | :-------: | :------: | :------------: | :---------------------: | :----------------: |:---------: | :------: |:---------------: |:-----: | +| *YOLOv8-n | 640 | 16 | 500e | 2.4 | 37.3 | 53.0 | 3.16 | 8.7 | [model](https://paddledet.bj.bcebos.com/models/yolov8_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_n_300e_coco.yml) | +| *YOLOv8-s | 640 | 16 | 500e | 3.4 | 44.9 | 61.8 | 11.17 | 28.6 | [model](https://paddledet.bj.bcebos.com/models/yolov8_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_s_300e_coco.yml) | +| *YOLOv8-m | 640 | 16 | 500e | 6.5 | 50.2 | 67.3 | 25.90 | 78.9 | [model](https://paddledet.bj.bcebos.com/models/yolov8_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_m_300e_coco.yml) | +| *YOLOv8-l | 640 | 16 | 500e | 10.0 | 52.8 | 69.6 | 43.69 | 165.2 | [model](https://paddledet.bj.bcebos.com/models/yolov8_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_l_300e_coco.yml) | +| *YOLOv8-x | 640 | 16 | 500e | 15.1 | 53.8 | 70.6 | 68.23 | 257.8 | [model](https://paddledet.bj.bcebos.com/models/yolov8_x_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_x_300e_coco.yml) | +| *YOLOv8-P6-x | 1280 | 16 | 500e | 55.0 | - | - | 97.42 | 522.93 | [model](https://paddledet.bj.bcebos.com/models/yolov8p6_x_500e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8p6_x_500e_coco.yml) | + +
    + +
    + 部署模型 + +| 网络模型 | 输入尺寸 | 导出后的权重(w/o NMS) | ONNX(w/o NMS) | +| :-------- | :--------: | :---------------------: | :----------------: | +| YOLOv8-n | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.onnx) | +| YOLOv8-s | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.onnx) | +| YOLOv8-m | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.onnx) | +| YOLOv8-l | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.onnx) | +| YOLOv8-x | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.onnx) | + +
    + + ### [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
    @@ -215,11 +242,11 @@ | 网络网络 | 输入尺寸 | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) | mAP | AP50 | Params(M) | FLOPs(G) | 下载链接 | 配置文件 | | :------------- | :------- | :-------: | :------: | :---------: | :-----: |:-----: | :-----: |:-----: | :-------------: | :-----: | -| *RTMDet-t | 640 | 32 | 300e | 2.8 | 40.9 | 57.9 | 4.90 | 16.21 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_t_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_t_300e_coco.yml) | -| *RTMDet-s | 640 | 32 | 300e | 3.3 | 44.5 | 62.0 | 8.89 | 29.71 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_s_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_s_300e_coco.yml) | -| *RTMDet-m | 640 | 32 | 300e | 6.4 | 49.1 | 66.8 | 24.71 | 78.47 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_m_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_m_300e_coco.yml) | -| *RTMDet-l | 640 | 32 | 300e | 10.2 | 51.2 | 68.8 | 52.31 | 160.32 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_l_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_l_300e_coco.yml) | -| *RTMDet-x | 640 | 32 | 300e | 18.0 | 52.6 | 70.4 | 94.86 | 283.12 |[下载链接](https://paddledet.bj.bcebos.com/models/rtmdet_x_300e_coco.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_x_300e_coco.yml) | +| *RTMDet-t | 640 | 32 | 300e | 2.8 | 40.9 | 57.9 | 4.90 | 16.21 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_t_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_t_300e_coco.yml) | +| *RTMDet-s | 640 | 32 | 300e | 3.3 | 44.5 | 62.0 | 8.89 | 29.71 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_s_300e_coco.yml) | +| *RTMDet-m | 640 | 32 | 300e | 6.4 | 49.1 | 66.8 | 24.71 | 78.47 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_m_300e_coco.yml) | +| *RTMDet-l | 640 | 32 | 300e | 10.2 | 51.2 | 68.8 | 52.31 | 160.32 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_l_300e_coco.yml) | +| *RTMDet-x | 640 | 32 | 300e | 18.0 | 52.6 | 70.4 | 94.86 | 283.12 |[model](https://paddledet.bj.bcebos.com/models/rtmdet_x_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet/rtmdet_x_300e_coco.yml) |
    @@ -264,7 +291,6 @@ | 网络模型 | 输入尺寸 | 图片数/GPU | 学习率策略 | TRT-FP16-Latency(ms) | mAP(0.50,11point) | Params(M) | FLOPs(G) | 下载链接 | 配置文件 | | :-----------: | :-------: | :-------: | :------: | :------------: | :---------------: | :------------------: |:-----------------: | :------: | :------: | | YOLOv5-s | 640 | 16 | 60e | 3.2 | 80.3 | 7.24 | 16.54 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov5_s_60e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov5_s_60e_voc.yml) | -| YOLOv6-s | 640 | 32 | 40e | 2.7 | 84.7 | 18.87 | 48.35 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov6_s_40e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov6_s_40e_voc.yml) | | YOLOv7-tiny | 640 | 32 | 60e | 2.6 | 80.2 | 6.23 | 6.90 | [下载链接](https://paddledet.bj.bcebos.com/models/yolov7_tiny_60e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov7_tiny_60e_voc.yml) | | YOLOX-s | 640 | 8 | 40e | 3.0 | 82.9 | 9.0 | 26.8 | [下载链接](https://paddledet.bj.bcebos.com/models/yolox_s_40e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolox_s_40e_voc.yml) | | PP-YOLOE+_s | 640 | 8 | 30e | 2.9 | 86.7 | 7.93 | 17.36 | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [配置文件](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/ppyoloe_plus_crn_s_30e_voc.yml) | diff --git a/docs/feature_models/PaddleYOLO_MODEL_en.md b/docs/feature_models/PaddleYOLO_MODEL_en.md index 46d348358..b73634759 100644 --- a/docs/feature_models/PaddleYOLO_MODEL_en.md +++ b/docs/feature_models/PaddleYOLO_MODEL_en.md @@ -5,11 +5,12 @@ ## Introduction - [Introduction](#Introduction) - [ModelZoo](#ModelZoo) - - [PP-YOLOE+](#PP-YOLOE+) + - [PP-YOLOE](#PP-YOLOE) - [YOLOX](#YOLOX) - [YOLOv5](#YOLOv5) - [YOLOv6](#YOLOv6) - [YOLOv7](#YOLOv7) + - [YOLOv8](#YOLOv8) - [RTMDet](#RTMDet) - [VOC](#VOC) - [UserGuide](#UserGuide) @@ -18,10 +19,11 @@ ## Introduction -**PaddleYOLO** is a YOLO Series toolbox based on [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **only relevant codes of YOLO series models are included**. It supports `YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`RTMDet` and so on. Welcome to use and build it together! +**PaddleYOLO** is a YOLO Series toolbox based on [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **only relevant codes of YOLO series models are included**. It supports `YOLOv3`,`PP-YOLO`,`PP-YOLOv2`,`PP-YOLOE`,`PP-YOLOE+`,`YOLOX`,`YOLOv5`,`YOLOv6`,`YOLOv7`,`YOLOv8`,`RTMDet` and so on. Welcome to use and build it together! ## Updates +* 【2023/01/10】Support [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) inference and deploy; * 【2022/09/29】Support [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet) inference and deploy; * 【2022/09/26】Release [`PaddleYOLO`](https://github.com/PaddlePaddle/PaddleYOLO); * 【2022/09/19】Support the new version of [`YOLOv6`](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6), including n/t/s/m/l model; @@ -29,13 +31,13 @@ **Notes：** - - The Licence of **PaddleYOLO** is **GPL 3.0**, the codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7) and [YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6) will not be merged into [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection). Except for these three YOLO models, other YOLO models are recommended to use in [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **which will be the first to release the latest progress of PP-YOLO series detection model**; + - The Licence of **PaddleYOLO** is **GPL 3.0**, the codes of [YOLOv5](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov5),[YOLOv6](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6),[YOLOv7](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov7) and [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) will not be merged into [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection). Except for these three YOLO models, other YOLO models are recommended to use in [PaddleDetection](https://github.com/PaddlePaddle/PaddleDetection), **which will be the first to release the latest progress of PP-YOLO series detection model**; - To use **PaddleYOLO**, **PaddlePaddle-2.3.2 or above is recommended**，please refer to the [official website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html) to download the appropriate version. **For Windows platforms, please install the paddle develop version**; - Training **Custom dataset** please refer to [doc](#CustomDataset) and [issue](https://github.com/PaddlePaddle/PaddleYOLO/issues/43). Please **ensure COCO trained weights are loaded as pre-train** at first. We recommend to use YOLO detection model **with a total `batch_size` at least greater than `64` to train**. If the resources are insufficient, please **use the smaller model** or **reduce the input size of the model**. To ensure high detection accuracy, **you'd better never try to using single GPU or total `batch_size` less than `32` for training**; ## ModelZoo -### [PP-YOLOE+](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe) +### [PP-YOLOE](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/ppyoloe)
    Baseline @@ -147,13 +149,10 @@ | Model | Input Size | images/GPU | Epoch | TRT-FP16-Latency(ms) | mAPval
    0.5:0.95 | mAPval
    0.5 | Params(M) | FLOPs(G) | download | config | | :------------- | :------- | :-------: | :------: | :---------: | :-----: |:-----: | :-----: |:-----: | :-------------: | :-----: | -| YOLOv6-n | 416 | 32 | 400e | 1.0 | 31.1 | 45.3 | 4.74 | 5.16 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_416_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_416_400e_coco.yml) | -| YOLOv6-n | 640 | 32 | 400e | 1.3 | 36.1 | 51.9 | 4.74 | 12.21 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_400e_coco.yml) | -| *YOLOv6-t | 640 | 32 | 400e | 2.1 | 40.7 | 57.4 | 10.63 | 27.29 |[model](https://paddledet.bj.bcebos.com/models/yolov6_t_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_t_400e_coco.yml) | -| *YOLOv6-s | 640 | 32 | 400e | 2.6 | 43.4 | 60.5 | 18.87 | 48.35 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_400e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_400e_coco.yml) | -| *YOLOv6-m | 640 | 32 | 300e | 5.0 | 49.0 | 66.5 | 37.17 | 88.82 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) | -| *YOLOv6-l | 640 | 32 | 300e | 7.9 | 51.0 | 68.9 | 63.54 | 155.89 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) | -| *YOLOv6-l-silu | 640 | 32 | 300e | 9.6 | 51.7 | 69.6 | 58.59 | 142.66 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_silu_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_silu_300e_coco.yml) | +| *YOLOv6-n | 640 | 16 | 300e(+300e) | 2.0 | 37.5 | 53.1 | 5.07 | 12.49 |[model](https://paddledet.bj.bcebos.com/models/yolov6_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_n_300e_coco.yml) | +| *YOLOv6-s | 640 | 32 | 300e(+300e) | 2.7 | 44.8 | 61.7 | 20.18 | 49.36 |[model](https://paddledet.bj.bcebos.com/models/yolov6_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_s_300e_coco.yml) | +| *YOLOv6-m | 640 | 32 | 300e(+300e) | - | 49.5 | 66.9 | 37.74 | 92.47 |[model](https://paddledet.bj.bcebos.com/models/yolov6_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_m_300e_coco.yml) | +| *YOLOv6-l(silu) | 640 | 32 | 300e(+300e) | - | 52.2 | 70.2 | 59.66 | 149.4 |[model](https://paddledet.bj.bcebos.com/models/yolov6_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov6/yolov6_l_300e_coco.yml) |
    @@ -162,13 +161,10 @@ | Model | Input Size | Exported weights(w/o NMS) | ONNX(w/o NMS) | | :-------- | :--------: | :---------------------: | :----------------: | -| yolov6-n | 416 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_416_400e_coco_wo_nms.onnx) | -| yolov6-n | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_400e_coco_wo_nms.onnx) | -| yolov6-t | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_t_400e_coco_wo_nms.onnx) | -| yolov6-s | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_400e_coco_wo_nms.onnx) | -| yolov6-m | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) | -| yolov6-l | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) | -| yolov6-l-silu | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_silu_300e_coco_wo_nms.onnx) | +| yolov6-n | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_n_300e_coco_wo_nms.onnx) | +| yolov6-s | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_s_300e_coco_wo_nms.onnx) | +| yolov6-m | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_m_300e_coco_wo_nms.onnx) | +| yolov6-l(silu) | 640 | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.zip) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.zip) | [(w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_w_nms.onnx) | [(w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov6/yolov6_l_300e_coco_wo_nms.onnx) | @@ -209,6 +205,36 @@ +### [YOLOv8](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) + +
    + Baseline + +| Model | Input Size | images/GPU | Epoch | TRT-FP16-Latency(ms) | mAPval
    0.5:0.95 | mAPval
    0.5 | Params(M) | FLOPs(G) | download | config | +| :------------- | :------- | :-------: | :------: | :------------: | :---------------------: | :----------------: |:---------: | :------: |:---------------: |:-----: | +| *YOLOv8-n | 640 | 16 | 500e | 2.4 | 37.3 | 53.0 | 3.16 | 8.7 | [model](https://paddledet.bj.bcebos.com/models/yolov8_n_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_n_300e_coco.yml) | +| *YOLOv8-s | 640 | 16 | 500e | 3.4 | 44.9 | 61.8 | 11.17 | 28.6 | [model](https://paddledet.bj.bcebos.com/models/yolov8_s_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_s_300e_coco.yml) | +| *YOLOv8-m | 640 | 16 | 500e | 6.5 | 50.2 | 67.3 | 25.90 | 78.9 | [model](https://paddledet.bj.bcebos.com/models/yolov8_m_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_m_300e_coco.yml) | +| *YOLOv8-l | 640 | 16 | 500e | 10.0 | 52.8 | 69.6 | 43.69 | 165.2 | [model](https://paddledet.bj.bcebos.com/models/yolov8_l_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_l_300e_coco.yml) | +| *YOLOv8-x | 640 | 16 | 500e | 15.1 | 53.8 | 70.6 | 68.23 | 257.8 | [model](https://paddledet.bj.bcebos.com/models/yolov8_x_300e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8_x_300e_coco.yml) | +| *YOLOv8-P6-x | 1280 | 16 | 500e | 55.0 | - | - | 97.42 | 522.93 | [model](https://paddledet.bj.bcebos.com/models/yolov8p6_x_500e_coco.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8/yolov8p6_x_500e_coco.yml) | + +
    + +
    + Deploy Models + +| Model | Input Size | Exported weights(w/o NMS) | ONNX(w/o NMS) | +| :-------- | :--------: | :---------------------: | :----------------: | +| YOLOv8-n | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_n_500e_coco_wo_nms.onnx) | +| YOLOv8-s | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_s_500e_coco_wo_nms.onnx) | +| YOLOv8-m | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_m_500e_coco_wo_nms.onnx) | +| YOLOv8-l | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_l_500e_coco_wo_nms.onnx) | +| YOLOv8-x | 640 | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.zip) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_w_nms.onnx) | [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/yoloseries/yolov8/yolov8_x_500e_coco_wo_nms.onnx) | + +
    + + ### [RTMDet](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/rtmdet)
    @@ -254,7 +280,6 @@ | Model | Input Size | images/GPU | Epoch | TRT-FP16-Latency(ms) | mAP(0.50,11point) | Params(M) | FLOPs(G) | download | config | | :-----------: | :-------: | :-------: | :------: | :------------: | :---------------: | :------------------: |:-----------------: | :------: | :------: | | YOLOv5-s | 640 | 16 | 60e | 3.2 | 80.3 | 7.24 | 16.54 | [model](https://paddledet.bj.bcebos.com/models/yolov5_s_60e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov5_s_60e_voc.yml) | -| YOLOv6-s | 640 | 32 | 40e | 2.7 | 84.7 | 18.87 | 48.35 | [model](https://paddledet.bj.bcebos.com/models/yolov6_s_40e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov6_s_40e_voc.yml) | | YOLOv7-tiny | 640 | 32 | 60e | 2.6 | 80.2 | 6.23 | 6.90 | [model](https://paddledet.bj.bcebos.com/models/yolov7_tiny_60e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolov7_tiny_60e_voc.yml) | | YOLOX-s | 640 | 8 | 40e | 3.0 | 82.9 | 9.0 | 26.8 | [model](https://paddledet.bj.bcebos.com/models/yolox_s_40e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/yolox_s_40e_voc.yml) | | PP-YOLOE+_s | 640 | 8 | 30e | 2.9 | 86.7 | 7.93 | 17.36 | [model](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_s_30e_voc.pdparams) | [config](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/voc/ppyoloe_plus_crn_s_30e_voc.yml) | -- GitLab