fix contrib link error in release 0.2 (#649)

* fix windows python path (#480)

* fix link error

* fix contrib_link

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)

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)