diff --git a/README_cn.md b/README_cn.md index 1bf170dbabdcbb8fdc924437a59858dec2eabd56..442b1ad4bce248821165155e84f3f34b8ae03fbe 100644 --- a/README_cn.md +++ b/README_cn.md @@ -50,7 +50,7 @@ **PaddleDetection**为基于飞桨PaddlePaddle的端到端目标检测套件，内置**30+模型算法**及**250+预训练模型**，覆盖**目标检测、实例分割、跟踪、关键点检测**等方向，其中包括**服务器端和移动端高精度、轻量级**产业级SOTA模型、冠军方案和学术前沿算法，并提供配置化的网络模块组件、十余种数据增强策略和损失函数等高阶优化支持和多种部署方案，在打通数据处理、模型开发、训练、压缩、部署全流程的基础上，提供丰富的案例及教程，加速算法产业落地应用。
- +
## 特性 @@ -61,7 +61,7 @@ - **高性能**: 基于飞桨的高性能内核，模型训练速度及显存占用优势明显。支持FP16训练, 支持多机训练。
- +
## 技术交流 diff --git a/README_en.md b/README_en.md index 61412c19b5a51e430ac07eeb707e7caab9b5ac7c..afbe16d2bc1a4b6bccca85676ccf99f69e2f4bce 100644 --- a/README_en.md +++ b/README_en.md @@ -56,11 +56,9 @@ **PaddleDetection** is an end-to-end object detection development kit based on PaddlePaddle. Providing **over 30 model algorithm** and **over 250 pre-trained models**, it covers object detection, instance segmentation, keypoint detection, multi-object tracking. In particular, PaddleDetection offers **high- performance & light-weight** industrial SOTA models on **servers and mobile** devices, champion solution and cutting-edge algorithm. PaddleDetection provides various data augmentation methods, configurable network components, loss functions and other advanced optimization & deployment schemes. In addition to running through the whole process of data processing, model development, training, compression and deployment, PaddlePaddle also provides rich cases and tutorials to accelerate the industrial application of algorithm.
- +
- - ## Features - **Rich model library**: PaddleDetection provides over 250 pre-trained models including **object detection, instance segmentation, face recognition, multi-object tracking**. It covers a variety of **global competition champion** schemes. @@ -69,8 +67,8 @@ - **High Performance**: Due to the high performance core, PaddlePaddle has clear advantages in training speed and memory occupation. It also supports FP16 training and multi-machine training.
- newstructure -
+ ## Exchanges @@ -312,14 +310,14 @@ The comparison between COCO mAP and FPS on Qualcomm Snapdragon 865 processor of | PicoDet-M | 34.4 | 17.68 | [Link](configs/picodet/picodet_m_320_coco_lcnet.yml) | [Download](https://paddledet.bj.bcebos.com/models/picodet_m_320_coco_lcnet.pdparams) | | PicoDet-L | 36.1 | 25.21 | [Link](configs/picodet/picodet_l_320_coco_lcnet.yml) | [Download](https://paddledet.bj.bcebos.com/models/picodet_l_320_coco_lcnet.pdparams) | -#### Frontier detection algorithm +#### [Frontier detection algorithm](docs/feature_models/YOLOSERIES_MODEL.md) | Model | COCO Accuracy（mAP） | V100 TensorRT FP16 speed(FPS) | Configuration | Download | |:-------- |:------------------:|:-----------------------------:|:--------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------:| | YOLOX-l | 50.1 | 107.5 | [Link](configs/yolox/yolox_l_300e_coco.yml) | [Download](https://paddledet.bj.bcebos.com/models/yolox_l_300e_coco.pdparams) | | YOLOv5-l | 48.6 | 136.0 | [Link](https://github.com/nemonameless/PaddleDetection_YOLOv5/blob/main/configs/yolov5/yolov5_l_300e_coco.yml) | [Download](https://paddledet.bj.bcebos.com/models/yolov5_l_300e_coco.pdparams) | -#### Other general purpose models [doc](docs/MODEL_ZOO_cn.md) +#### Other general purpose models [doc](docs/MODEL_ZOO_en.md) @@ -407,7 +405,7 @@ Please refer to [docs](deploy/pipeline/README_en.md) for details. - [Quick start](docs/tutorials/QUICK_STARTED_cn.md) - [Data preparation](docs/tutorials/data/README.md) - [Geting Started on PaddleDetection](docs/tutorials/GETTING_STARTED_cn.md) -- [FAQ]((docs/tutorials/FAQ) +- [FAQ](docs/tutorials/FAQ) ### Advanced tutorials