From 0dac4bcf75d459eb10fd6005be45f2d1299c1031 Mon Sep 17 00:00:00 2001 From: Guanghua Yu <742925032@qq.com> Date: Tue, 12 May 2020 16:28:26 +0800 Subject: [PATCH] fix contrib link error in release 0.2 (#649) * fix windows python path (#480) * fix link error * fix contrib_link --- README.md | 4 ++-- README_en.md | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 174e93bf2..dd3f9e618 100644 --- a/README.md +++ b/README.md @@ -95,8 +95,8 @@ PaddleDetection的目的是为工业界和学术界提供丰富、易用的目 ## 模型库 - [模型库](docs/MODEL_ZOO_cn.md) -- [人脸检测模型](configs/face_detection/README.md) 开源BlazeFace系列模型，Wider-Face数据集上最高精度达到91.5%，同时具备了较高的预测性能 -- [行人检测和车辆检测预训练模型](contrib/README_cn.md) 针对不同场景的检测模型 +- [人脸检测模型](docs/featured_model/FACE_DETECTION.md) 开源BlazeFace系列模型，Wider-Face数据集上最高精度达到91.5%，同时具备了较高的预测性能 +- [行人检测和车辆检测预训练模型](docs/featured_model/CONTRIB_cn.md) 针对不同场景的检测模型 - [YOLOv3增强模型](docs/featured_model/YOLOv3_ENHANCEMENT.md) 改进原始YOLOv3，精度达到43.2%，原论文精度为33.0%，同时预测速度也得到提升 - [Objects365 2019 Challenge夺冠模型](docs/featured_model/CACascadeRCNN.md) Objects365 Full Track任务中最好的单模型之一,精度达到31.7% - [Open Images V5和Objects365数据集模型](docs/featured_model/OIDV5_BASELINE_MODEL.md) diff --git a/README_en.md b/README_en.md index d78f9550e..4d1ca93f0 100644 --- a/README_en.md +++ b/README_en.md @@ -106,8 +106,8 @@ Advanced Features: ## Model Zoo - Pretrained models are available in the [PaddleDetection model zoo](docs/MODEL_ZOO.md). -- [Face detection models](configs/face_detection/README.md) BlazeFace series model with the highest precision of 91.5% on Wider-Face dataset and outstanding inference performance. -- [Pretrained models for pedestrian and vehicle detection](contrib/README.md) Models for object detection in specific scenarios. +- [Face detection models](docs/featured_model/FACE_DETECTION_en.md) BlazeFace series model with the highest precision of 91.5% on Wider-Face dataset and outstanding inference performance. +- [Pretrained models for pedestrian and vehicle detection](docs/featured_model/CONTRIB.md) Models for object detection in specific scenarios. - [YOLOv3 enhanced model](docs/YOLOv3_ENHANCEMENT.md) Compared to MAP of 33.0% in paper, enhanced YOLOv3 reaches the MAP of 43.2% and inference speed is improved as well - [Objects365 2019 Challenge champion model](docs/CACascadeRCNN.md) One of the best single models in Objects365 Full Track of which MAP reaches 31.7%. - [Open Images Dataset V5 and Objects365 Dataset models](docs/OIDV5_BASELINE_MODEL.md) -- GitLab