fix some link error (#648)

README.md

@@ -98,17 +98,17 @@
     - [剪枝](slim/prune)
     - [蒸馏](slim/distillation)
     - [神经网络搜索](slim/nas)
-- [推理部署](inference)
-    - [模型导出教程](docs/advanced_tutorials/inference/EXPORT_MODEL.md)
-    - [预测引擎Python API使用示例](docs/advanced_tutorials/inference/INFERENCE.md)
-    - [C++推理部署](deploy/README.md)
-    - [推理Benchmark](docs/advanced_tutorials/inference/BENCHMARK_INFER_cn.md)
+- [推理部署](deploy)
+    - [模型导出教程](docs/advanced_tutorials/deploy/EXPORT_MODEL.md)
+    - [Python端推理部署](deploy/python)
+    - [C++端推理部署](deploy/cpp)
+    - [推理Benchmark](docs/advanced_tutorials/deploy/BENCHMARK_INFER_cn.md)
 
 ## 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43.6%，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

@@ -112,20 +112,20 @@ The following is the relationship between COCO mAP and FPS on Tesla V100 of repr
     - [Model pruning](slim/prune)
     - [Model distillation](slim/distillation)
     - [Neural Architecture Search](slim/nas)
-- [Deployment](inference)
-    - [Export model for inference](docs/advanced_tutorials/inference/EXPORT_MODEL.md)
-    - [Model inference](docs/advanced_tutorials/inference/INFERENCE.md)
-    - [C++ inference](inference/README.md)
+- [Deployment](deploy)
+    - [Export model for inference](docs/advanced_tutorials/deploy/EXPORT_MODEL.md)
+    - [Python inference](deploy/python)
+    - [C++ inference](deploy/cpp)
     - [Inference benchmark](docs/advanced_tutorials/inference/BENCHMARK_INFER_cn.md)
 
 ## 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.
-- [YOLOv3 enhanced model](docs/YOLOv3_ENHANCEMENT.md) Compared to MAP of 33.0% in paper, enhanced YOLOv3 reaches the MAP of 43.6% 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)
+- [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/featured_model/YOLOv3_ENHANCEMENT.md) Compared to MAP of 33.0% in paper, enhanced YOLOv3 reaches the MAP of 43.6% and inference speed is improved as well
+- [Objects365 2019 Challenge champion model](docs/featured_model/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/featured_model/OIDV5_BASELINE_MODEL.md)
 - [Mobile models](configs/mobile/README.md)
 
 

docs/advanced_tutorials/deploy/DEPLOY_CPP.md

+../../../deploy/cpp/README.md
\ No newline at end of file

docs/advanced_tutorials/deploy/DEPLOY_PY.md

+../../../deploy/python/README.md
\ No newline at end of file

docs/advanced_tutorials/inference/index.rst → docs/advanced_tutorials/deploy/index.rst

@@ -5,6 +5,6 @@
    :maxdepth: 2
 
    EXPORT_MODEL.md
-   INFERENCE.md
+   DEPLOY_PY.md
+   DEPLOY_CPP.md
    BENCHMARK_INFER_cn.md
-   DEPLOYMENT.md

docs/advanced_tutorials/index.rst

@@ -4,9 +4,9 @@
 .. toctree::
    :maxdepth: 2
 
+   deploy/index
    READER.md
    MODEL_TECHNICAL.md
    CONFIG_cn.md
    TRANSFER_LEARNING_cn.md
    slim/index
-   inference/index

docs/advanced_tutorials/inference/DEPLOYMENT.md

-../../../../deploy/cpp/README.md
\ No newline at end of file