[Doc]Add English version of documents in docs/cn and api/vision_results (#931)

* 第一次提交 * 补充一处漏翻译 * deleted: docs/en/quantize.md * Update one translation * Update en version * Update one translation in code * Standardize one writing * Standardize one writing * Update some en version * Fix a grammer problem * Update en version for api/vision result * Merge branch 'develop' of https://github.com/charl-u/FastDeploy into develop * Checkout the link in README in vision_results/ to the en documents * Modify a title * Add link to serving/docs/ * Finish translation of demo.md
2025-10-05 08:37:06 +08:00 · 2022-12-22 18:15:01 +08:00
parent ac255b8ab8
commit 02eab973ce
80 changed files with 1430 additions and 53 deletions
--- a/docs/en/build_and_install/a311d.md
+++ b/docs/en/build_and_install/a311d.md
@@ -1,3 +1,5 @@
+English | [中文](../../cn/build_and_install/a311d.md)
+
 # How to Build A311D Deployment Environment

 FastDeploy supports AI deployment on Rockchip Soc based on Paddle Lite backend. For more detailed information, please refer to: [Paddle Lite Deployment Example](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html).
--- a/docs/en/build_and_install/android.md
+++ b/docs/en/build_and_install/android.md
@@ -1,3 +1,5 @@
+English | [中文](../../cn/build_and_install/android.md)
+
 # How to Build FastDeploy Android C++ SDK

 FastDeploy supports Paddle Lite backend on Android. It supports both armeabi-v7a and arm64-v8a cpu architectures, and supports fp16 precision inference on the armv8.2 architecture. The relevant compilation options are described as follows:
--- a/docs/en/build_and_install/cpu.md
+++ b/docs/en/build_and_install/cpu.md
@@ -1,4 +1,4 @@
-
+English | [中文](../../cn/build_and_install/cpu.md)

 # How to Build CPU Deployment Environment

--- a/docs/en/build_and_install/download_prebuilt_libraries.md
+++ b/docs/en/build_and_install/download_prebuilt_libraries.md
@@ -1,4 +1,5 @@
 English | [中文](../../cn/build_and_install/download_prebuilt_libraries.md)
+
 # How to Install Prebuilt Library

 FastDeploy provides pre-built libraries for developers to download and install directly. Meanwhile, FastDeploy also offers easy access to compile so that developers can compile FastDeploy according to their own needs.
@@ -92,7 +93,7 @@ Install the released version（Latest 1.0.1 for now, Android is 1.0.1）
 | Mac OSX x64 | [fastdeploy-osx-x86_64-1.0.1.tgz](https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-osx-x86_64-1.0.1.tgz) | clang++ 10.0.0|
 | Mac OSX arm64 | [fastdeploy-osx-arm64-1.0.1.tgz](https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-osx-arm64-1.0.1.tgz) | clang++ 13.0.0 |
 | Linux aarch64 | [fastdeploy-osx-arm64-1.0.1.tgz](https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-aarch64-1.0.1.tgz) | gcc 6.3 |  
-| Android armv7&v8 | [fastdeploy-android-1.0.0-shared.tgz](https://bj.bcebos.com/fastdeploy/release/android/fastdeploy-android-1.0.0-shared.tgz)| NDK 25, clang++, support arm64-v8a及armeabi-v7a |
+| Android armv7&v8 | [fastdeploy-android-1.0.0-shared.tgz](https://bj.bcebos.com/fastdeploy/release/android/fastdeploy-android-1.0.0-shared.tgz)| NDK 25, clang++, support arm64-v8a and armeabi-v7a |

 ## Java SDK

@@ -109,6 +110,6 @@ Install the Develop version（Nightly build）
 | Linux x64 | [fastdeploy-linux-x64-0.0.0.tgz](https://fastdeploy.bj.bcebos.com/dev/cpp/fastdeploy-linux-x64-0.0.0.tgz) | g++ 8.2 |
 | Windows x64 | [fastdeploy-win-x64-0.0.0.zip](https://fastdeploy.bj.bcebos.com/dev/cpp/fastdeploy-win-x64-0.0.0.zip) | Visual Studio 16 2019 |
 | Mac OSX x64 | [fastdeploy-osx-arm64-0.0.0.tgz](https://bj.bcebos.com/fastdeploy/dev/cpp/fastdeploy-osx-arm64-0.0.0.tgz) | - |
-| Mac OSX arm64 | [fastdeploy-osx-arm64-0.0.0.tgz](https://fastdeploy.bj.bcebos.com/dev/cpp/fastdeploy-osx-arm64-0.0.0.tgz) | clang++ 13.0.0编译产出 |
+| Mac OSX arm64 | [fastdeploy-osx-arm64-0.0.0.tgz](https://fastdeploy.bj.bcebos.com/dev/cpp/fastdeploy-osx-arm64-0.0.0.tgz) | clang++ 13.0.0 to compile |
 | Linux aarch64 | - | - |  
 | Android armv7&v8 | - | - |
--- a/docs/en/build_and_install/gpu.md
+++ b/docs/en/build_and_install/gpu.md
@@ -1,3 +1,4 @@
+English | [中文](../../cn/build_and_install/gpu.md)

 # How to Build GPU Deployment Environment

--- a/docs/en/build_and_install/ipu.md
+++ b/docs/en/build_and_install/ipu.md
@@ -1,3 +1,4 @@
+English | [中文](../../cn/build_and_install/ipu.md)

 # How to Build IPU Deployment Environment

--- a/docs/en/build_and_install/jetson.md
+++ b/docs/en/build_and_install/jetson.md
@@ -1,3 +1,4 @@
+English | [中文](../../cn/build_and_install/jetson.md)

 # How to Build FastDeploy Library on Nvidia Jetson Platform

--- a/docs/en/build_and_install/rknpu2.md
+++ b/docs/en/build_and_install/rknpu2.md
@@ -0,0 +1,106 @@
+English | [中文](../../cn/build_and_install/rknpu2.md)
+
+# How to Build RKNPU2 Deployment Environment
+
+## Notes
+FastDeploy has initial support for RKNPU2 deployments. If you find bugs while using, please report an issue to give us feedback.
+
+## Introduction
+Currently, the following backend engines on the RK platform are supported:
+
+| Backend                | Platform                   | Model format supported | Description                                         |
+|:------------------|:---------------------|:-------|:-------------------------------------------|
+| ONNX&nbsp;Runtime | RK356X   <br> RK3588 | ONNX   | Compile switch is controlled by setting `ENABLE_ORT_BACKEND` ON or OFF(default)    |
+| RKNPU2            | RK356X   <br> RK3588 | RKNN   | Compile switch is controlled by setting `ENABLE_RKNPU2_BACKEND` ON or OFF(default) |
+
+
+## How to Build and Install C++ SDK
+
+RKNPU2 only supports compiling on linux, the following steps are done on linux.
+
+### Update the driver and install the compiling environment
+
+
+Before running the program, we need to install the latest RKNPU driver, which is currently updated to 1.4.0. To simplify the installation, here is a quick install script.
+
+**Method 1: Install via script**
+```bash
+# Download and unzip rknpu2_device_install_1.4.0
+wget https://bj.bcebos.com/fastdeploy/third_libs/rknpu2_device_install_1.4.0.zip
+unzip rknpu2_device_install_1.4.0.zip
+
+cd rknpu2_device_install_1.4.0
+# For RK3588
+sudo rknn_install_rk3588.sh
+# For RK356X
+sudo rknn_install_rk356X.sh
+```
+
+**Method 2: Install via gitee**
+```bash
+# Install necessary packages
+sudo apt update -y
+sudo apt install -y python3 
+sudo apt install -y python3-dev 
+sudo apt install -y python3-pip 
+sudo apt install -y gcc
+sudo apt install -y python3-opencv
+sudo apt install -y python3-numpy
+sudo apt install -y cmake
+
+# download rknpu2
+# For RK3588
+git clone https://gitee.com/mirrors_rockchip-linux/rknpu2.git
+sudo cp ./rknpu2/runtime/RK3588/Linux/librknn_api/aarch64/* /usr/lib
+sudo cp ./rknpu2/runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/
+
+# For RK356X
+git clone https://gitee.com/mirrors_rockchip-linux/rknpu2.git
+sudo cp ./rknpu2/runtime/RK356X/Linux/librknn_api/aarch64/* /usr/lib
+sudo cp ./rknpu2/runtime/RK356X/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/
+```
+
+### Compile C++ SDK
+
+```bash
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd FastDeploy
+mkdir build && cd build
+
+# Only a few key configurations are introduced here, see README.md for details.
+# -DENABLE_ORT_BACKEND:     Whether to enable ONNX model, default OFF
+# -DENABLE_RKNPU2_BACKEND:  Whether to enable RKNPU model, default OFF
+# -RKNN2_TARGET_SOC:        Compile the SDK board model. Enter RK356X or RK3588 with case sensitive required.
+cmake ..  -DENABLE_ORT_BACKEND=ON \
+	      -DENABLE_RKNPU2_BACKEND=ON \
+	      -DENABLE_VISION=ON \
+	      -DRKNN2_TARGET_SOC=RK3588 \
+          -DCMAKE_INSTALL_PREFIX=${PWD}/fastdeploy-0.0.3
+make -j8
+make install
+```
+
+### Compile Python SDK
+
+Python packages depend on `wheel`, please run `pip install wheel` before compiling.
+
+```bash
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd FastDeploy
+cd python
+
+export ENABLE_ORT_BACKEND=ON
+export ENABLE_RKNPU2_BACKEND=ON
+export ENABLE_VISION=ON
+export RKNN2_TARGET_SOC=RK3588
+python3 setup.py build
+python3 setup.py bdist_wheel
+
+cd dist
+
+pip3 install fastdeploy_python-0.0.0-cp39-cp39-linux_aarch64.whl
+```
+
+## Model Deployment
+
+Please refer to [RKNPU2 Model Deployment](../faq/rknpu2/rknpu2.md).
--- a/docs/en/build_and_install/rv1126.md
+++ b/docs/en/build_and_install/rv1126.md
@@ -1,3 +1,5 @@
+English | [中文](../../cn/build_and_install/rv1126.md)
+
 # How to Build RV1126 Deployment Environment

 FastDeploy supports AI deployment on Rockchip Soc based on Paddle Lite backend. For more detailed information, please refer to: [Paddle Lite Deployment Example](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html).
--- a/docs/en/build_and_install/third_libraries.md
+++ b/docs/en/build_and_install/third_libraries.md
@@ -0,0 +1,16 @@
+English | [中文](../../cn/build_and_install/third_libraries.md)
+
+# Third Library Dependency
+
+FastDeploy will depend on the following third libraries according to compile options.
+
+- OpenCV: OpenCV 3.4.16 library will be downloaded and pre-compiled automatically while ENABLE_VISION=ON.
+- ONNX Runimte: ONNX Runtime library will be downloaded automatically while ENABLE_ORT_BACKEND=ON.
+- OpenVINO: OpenVINO library will be downloaded automatically while ENABLE_OPENVINO_BACKEND=ON.
+
+You can decide your own third libraries that exist in the environment by setting the following switches.
+
+
+- OPENCV_DIRECTORY: Specify the OpenCV path in your environment, e.g. `-DOPENCV_DIRECTORY=/usr/lib/aarch64-linux-gnu/cmake/opencv4/`
+- ORT_DIRECTORY: Specify the ONNX Runtime path in your environment, e.g.`-DORT_DIRECTORY=/download/onnxruntime-linux-x64-1.0.0`
+- OPENVINO_DIRECTORY: Specify the OpenVINO path in your environment, e.g.`-DOPENVINO_DIRECTORY=//download/openvino`
--- a/docs/en/build_and_install/xpu.md
+++ b/docs/en/build_and_install/xpu.md
@@ -1,3 +1,5 @@
+English | [中文](../../cn/build_and_install/xpu.md)
+
 # How to Build KunlunXin XPU Deployment Environment

 FastDeploy supports deployment AI on KunlunXin XPU based on Paddle Lite backend. For more detailed information, please refer to: [Paddle Lite Deployment Example](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/kunlunxin_xpu.html#xpu)。