Bump up to version 0.3.0 (#371)

* Update VERSION_NUMBER

* Update paddle_inference.cmake

* Delete docs directory

* release new docs

* update version number

* add vision result doc

* update version

* fix dead link

* fix vision

* fix dead link

* Update README_EN.md

* Update README_EN.md

* Update README_EN.md

* Update README_EN.md

* Update README_EN.md

* Update README_CN.md

* Update README_EN.md

* Update README_CN.md

* Update README_EN.md

* Update README_CN.md

* Update README_EN.md

* Update README_EN.md

Co-authored-by: leiqing <54695910+leiqing1@users.noreply.github.com>

Author: jiangjiajun

README_CN.md

@@ -28,7 +28,15 @@
 
 ## 近期更新
 
-- 🔥 **2022.8.18：发布FastDeploy [release/v0.2.0](https://github.com/PaddlePaddle/FastDeploy/releases/tag/release%2F0.2.0)** <br>
+- 🔥 **2022.10.15：Release FastDeploy [release v0.3.0](https://github.com/PaddlePaddle/FastDeploy/tree/release%2F0.3.0)** <br>
+  - **New server-side deployment upgrade:更快的推理性能，一键量化，更多的视觉和NLP模型**
+       - 集成 OpenVINO 推理引擎，并且保证了使用 OpenVINO 与 使用 TensorRT、ONNX Runtime、 Paddle Inference一致的开发体验；
+       - 提供[一键模型量化工具](tools/quantization)，支持YOLOv7、YOLOv6、YOLOv5等视觉模型，在CPU和GPU推理速度可提升1.5～2倍；
+       - 新增加 PP-OCRv3, PP-OCRv2, PP-Matting, PP-HumanMatting, ModNet 等视觉模型并提供[端到端部署示例](examples/vision)；
+       - 新增加NLP信息抽取模型 UIE 并提供[端到端部署示例](examples/text/uie).
+       - 
+
+- 🔥 **2022.8.18：发布FastDeploy [release/v0.2.0](https://github.com/PaddlePaddle/FastDeploy/tree/release%2F0.2.0)** <br>
     - **服务端部署全新升级：更快的推理性能，更多的视觉模型支持**  
         - 发布基于x86 CPU、NVIDIA GPU的高性能推理引擎SDK，推理速度大幅提升
         - 集成Paddle Inference、ONNX Runtime、TensorRT等推理引擎并提供统一的部署体验

README_EN.md

@@ -28,17 +28,24 @@ English | [简体中文](README_CN.md)
 | **Face Alignment**                                                                                                                             | **3D Object Detection**                                                                                                                        | **Face Editing**                                                                                                                                 | **Image Animation**                                                                                                                            |
 | <img src='https://user-images.githubusercontent.com/54695910/188059460-9845e717-c30a-4252-bd80-b7f6d4cf30cb.png' height="126px" width="190px"> | <img src='https://user-images.githubusercontent.com/54695910/188270227-1a4671b3-0123-46ab-8d0f-0e4132ae8ec0.gif' height="126px" width="190px"> | <img src='https://user-images.githubusercontent.com/54695910/188054663-b0c9c037-6d12-4e90-a7e4-e9abf4cf9b97.gif' height="126px" width="126px">   | <img src='https://user-images.githubusercontent.com/54695910/188056800-2190e05e-ad1f-40ef-bf71-df24c3407b2d.gif' height="126px" width="190px"> |
 
-## Updates
+## 📣 Recent Updates
 
-- 🔥 **2022.8.18：Release FastDeploy [release/v0.2.0](https://github.com/PaddlePaddle/FastDeploy/releases/tag/release%2F0.2.0)** <br>
-  - **New server-side deployment upgrade: faster inference performance, support more vision model**
+- 🔥 **2022.10.15：Release FastDeploy [release v0.3.0](https://github.com/PaddlePaddle/FastDeploy/tree/release/0.3.0)** <br>
+  - **New server-side deployment upgrade: support more CV model and NLP model**
+       - Integrate OpenVINO and provide a seamless deployment experience with other inference engines include TensorRT、ONNX Runtime、Paddle Inference；
+       - Support [one-click model quantization](tools/quantization) to improve model inference speed by 1.5 to 2 times on CPU & GPU platform. The supported quantized model are YOLOv7, YOLOv6, YOLOv5, etc. 
+       - New CV models include PP-OCRv3, PP-OCRv2, PP-TinyPose, PP-Matting, etc. and provides [end-to-end deployment demos](examples/vision/detection/)
+       - New information extraction model is UIE, and provides [end-to-end deployment demos](examples/text/uie).
+
+- 🔥 **2022.8.18：Release FastDeploy [release v0.2.0](https://github.com/PaddlePaddle/FastDeploy/tree/release%2F0.2.0)** <br>
+  - **New server-side deployment upgrade: faster inference performance, support more CV model**
     - Release high-performance inference engine SDK based on x86 CPUs and NVIDIA GPUs, with significant increase in inference speed
-    - Integrate Paddle Inference, ONNXRuntime, TensorRT and other inference engines and provide a seamless deployment experience
-    - Supports full range of object detection models such as YOLOv7, YOLOv6, YOLOv5, PP-YOLOE and provides [End-To-End Deployment Demos](examples/vision/detection/)
-    - Support over 40 key models and [Demo Examples](examples/vision/) including face detection, face recognition, real-time portrait matting, image segmentation.
+    - Integrate Paddle Inference, ONNX Runtime, TensorRT and other inference engines and provide a seamless deployment experience
+    - Supports full range of object detection models such as YOLOv7, YOLOv6, YOLOv5, PP-YOLOE and provides [end-to-end deployment demos](examples/vision/detection/)
+    - Support over 40 key models and [demo examples](examples/vision/) including face detection, face recognition, real-time portrait matting, image segmentation.
     - Support deployment in both Python and C++
   - **Supports Rockchip, Amlogic, NXP and other NPU chip deployment capabilities on edge device deployment**
-    - Release Lightweight Object Detection [Picodet-NPU Deployment Demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/object_detection/linux/picodet_detection), providing the full quantized inference capability for INT8.
+    - Release Lightweight Object Detection [Picodet-NPU deployment demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/object_detection/linux/picodet_detection), providing the full quantized inference capability for INT8.
 
 ## Contents
 
@@ -71,7 +78,7 @@ English | [简体中文](README_CN.md)
 - python >= 3.6
 - OS: Linux x86_64/macOS/Windows 10
 
-##### Install Library with GPU Support
+##### Install Fastdeploy SDK with CPU&GPU support
 
 ```bash
 pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html
@@ -83,7 +90,7 @@ pip install fastdeploy-gpu-python -f https://www.paddlepaddle.org.cn/whl/fastdep
 conda config --add channels conda-forge && conda install cudatoolkit=11.2 cudnn=8.2
 ```
 
-##### Install CPU-only Library
+##### Install Fastdeploy SDK with only CPU support
 
 ```bash
 pip install fastdeploy-python -f https://www.paddlepaddle.org.cn/whl/fastdeploy.html

VERSION_NUMBER

@@ -1 +1 @@
-0.0.0
+0.3.0

cmake/paddle_inference.cmake

@@ -48,7 +48,7 @@ endif(WIN32)
 
 
 set(PADDLEINFERENCE_URL_BASE "https://bj.bcebos.com/fastdeploy/third_libs/")
-set(PADDLEINFERENCE_VERSION "2.4-dev")
+set(PADDLEINFERENCE_VERSION "2.4-dev1")
 if(WIN32)
   if (WITH_GPU)
     set(PADDLEINFERENCE_FILE "paddle_inference-win-x64-gpu-${PADDLEINFERENCE_VERSION}.zip")