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[Doc] Change all PaddleLite or Paddle-Lite to Paddle Lite (#929)

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* [FlyCV] Bump up FlyCV -> official release 1.0.0

* change PaddleLite or Paddle-Lite to Paddle lite

* fix docs

* fix doc

Co-authored-by: DefTruth <qiustudent_r@163.com>
Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
This commit is contained in:
yeliang2258
2022-12-21 14:15:50 +08:00
committed by GitHub
parent 725fe52df3
commit b42ec302e6
21 changed files with 104 additions and 86 deletions
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12
docs/en/build_and_install/a311d.md
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@@ -1,8 +1,8 @@
# 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: [PaddleLite Deployment Example](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html).
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).
This document describes how to compile the PaddleLite-based C++ FastDeploy cross-compilation library.
This document describes how to compile the Paddle Lite based C++ FastDeploy cross-compilation library.
The relevant compilation options are described as follows:
|Compile Options|Default Values|Description|Remarks|
@@ -46,7 +46,7 @@ wget -c https://mms-res.cdn.bcebos.com/cmake-3.10.3-Linux-x86_64.tar.gz && \
ln -s /opt/cmake-3.10/bin/ccmake /usr/bin/ccmake
```
## FastDeploy cross-compilation library compilation based on PaddleLite
## FastDeploy cross-compilation library compilation based on Paddle Lite
After setting up the cross-compilation environment, the compilation command is as follows:
```bash
# Download the latest source code
@@ -66,7 +66,7 @@ cmake -DCMAKE_TOOLCHAIN_FILE=./../cmake/toolchain.cmake \
make -j8
make install
```
After the compilation is complete, the fastdeploy-tmivx directory will be generated, indicating that the FastDeploy library based on PadddleLite TIM-VX has been compiled.
After the compilation is complete, the fastdeploy-tmivx directory will be generated, indicating that the FastDeploy library based on Paddle Lite TIM-VX has been compiled.
## Prepare the Soc environment
Before deployment, ensure that the version of the driver galcore.so of the Verisilicon Linux Kernel NPU meets the requirements. Before deployment, please log in to the development board, and enter the following command through the command line to query the NPU driver version. The recommended version of the Rockchip driver is: 6.4.4.3
@@ -80,7 +80,7 @@ There are two ways to modify the current NPU driver version:
2. flash the machine, and flash the firmware that meets the requirements of the NPU driver version.
### Manually replace the NPU driver version
1. Use the following command to download and decompress the PaddleLite demo, which provides ready-made driver files
1. Use the following command to download and decompress the Paddle Lite demo, which provides ready-made driver files
```bash
wget https://paddlelite-demo.bj.bcebos.com/devices/generic/PaddleLite-generic-demo.tar.gz
tar -xf PaddleLite-generic-demo.tar.gz
@@ -93,7 +93,7 @@ tar -xf PaddleLite-generic-demo.tar.gz
### flash
According to the specific development board model, ask the development board seller or the official website customer service for the firmware and flashing method corresponding to the 6.4.4.3 version of the NPU driver.
For more details, please refer to: [PaddleLite prepares the device environment](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html#zhunbeishebeihuanjing)
For more details, please refer to: [Paddle Lite prepares the device environment](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html#zhunbeishebeihuanjing)
## Deployment example based on FastDeploy on A311D
1. For deploying the PaddleClas classification model on A311D, please refer to: [C++ deployment example of PaddleClas classification model on A311D](../../../examples/vision/classification/paddleclas/a311d/README.md)

4
docs/en/build_and_install/android.md Normal file → Executable file
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@@ -1,12 +1,12 @@
# 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:
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:
|Option|Default|Description|Remark|
|:---|:---|:---|:---|
|ENABLE_LITE_BACKEND|OFF|It needs to be set to ON when compiling the Android library| - |
|WITH_OPENCV_STATIC|OFF|Whether to use the OpenCV static library| - |
|WITH_LITE_STATIC|OFF|Whether to use the Paddle-Lite static library| NOT Support now |
|WITH_LITE_STATIC|OFF|Whether to use the Paddle Lite static library| NOT Support now |
Please reference [FastDeploy Compile Options](./README.md) for more details.

12
docs/en/build_and_install/rv1126.md
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@@ -1,8 +1,8 @@
# 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: [PaddleLite Deployment Example](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html).
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).
This document describes how to compile the PaddleLite-based C++ FastDeploy cross-compilation library.
This document describes how to compile the Paddle Lite based C++ FastDeploy cross-compilation library.
The relevant compilation options are described as follows:
|Compile Options|Default Values|Description|Remarks|
@@ -46,7 +46,7 @@ wget -c https://mms-res.cdn.bcebos.com/cmake-3.10.3-Linux-x86_64.tar.gz && \
ln -s /opt/cmake-3.10/bin/ccmake /usr/bin/ccmake
```
## FastDeploy cross-compilation library compilation based on PaddleLite
## FastDeploy cross-compilation library compilation based on Paddle Lite
After setting up the cross-compilation environment, the compilation command is as follows:
```bash
# Download the latest source code
@@ -66,7 +66,7 @@ cmake -DCMAKE_TOOLCHAIN_FILE=./../cmake/toolchain.cmake \
make -j8
make install
```
After the compilation is complete, the fastdeploy-tmivx directory will be generated, indicating that the FastDeploy library based on PadddleLite TIM-VX has been compiled.
After the compilation is complete, the fastdeploy-tmivx directory will be generated, indicating that the FastDeploy library based on Paddle Lite TIM-VX has been compiled.
## Prepare the Soc environment
Before deployment, ensure that the version of the driver galcore.so of the Verisilicon Linux Kernel NPU meets the requirements. Before deployment, please log in to the development board, and enter the following command through the command line to query the NPU driver version. The recommended version of the Rockchip driver is: 6.4.6.5
@@ -80,7 +80,7 @@ There are two ways to modify the current NPU driver version:
2. flash the machine, and flash the firmware that meets the requirements of the NPU driver version.
### Manually replace the NPU driver version
1. Use the following command to download and decompress the PaddleLite demo, which provides ready-made driver files
1. Use the following command to download and decompress the Paddle Lite demo, which provides ready-made driver files
```bash
wget https://paddlelite-demo.bj.bcebos.com/devices/generic/PaddleLite-generic-demo.tar.gz
tar -xf PaddleLite-generic-demo.tar.gz
@@ -93,7 +93,7 @@ tar -xf PaddleLite-generic-demo.tar.gz
### flash
According to the specific development board model, ask the development board seller or the official website customer service for the firmware and flashing method corresponding to the 6.4.6.5 version of the NPU driver.
For more details, please refer to: [PaddleLite prepares the device environment](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html#zhunbeishebeihuanjing)
For more details, please refer to: [Paddle Lite prepares the device environment](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/verisilicon_timvx.html#zhunbeishebeihuanjing)
## Deployment example based on FastDeploy on RV1126
1. For deploying the PaddleClas classification model on RV1126, please refer to: [C++ deployment example of PaddleClas classification model on RV1126](../../../examples/vision/classification/paddleclas/rv1126/README.md)

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docs/en/build_and_install/xpu.md
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@@ -1,8 +1,8 @@
# 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: [PaddleLite Deployment Example](https://www.paddlepaddle.org.cn/lite/develop/demo_guides/kunlunxin_xpu.html#xpu)。
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)。
This document describes how to compile the C++ FastDeploy library based on PaddleLite.
This document describes how to compile the C++ FastDeploy library based on Paddle Lite.
The relevant compilation options are described as follows:
|Compile Options|Default Values|Description|Remarks|
@@ -24,7 +24,7 @@ The configuration for third libraries(Optional, if the following option is not d
For more compilation options, please refer to [Description of FastDeploy compilation options](./README.md)
## C++ FastDeploy library compilation based on PaddleLite
## C++ FastDeploy library compilation based on Paddle Lite
- OS: Linux
- gcc/g++: version >= 8.2
- cmake: version >= 3.15
@@ -55,7 +55,7 @@ cmake -DWITH_XPU=ON \
make -j8
make install
```
After the compilation is complete, the fastdeploy-xpu directory will be generated, indicating that the PadddleLite-based FastDeploy library has been compiled.
After the compilation is complete, the fastdeploy-xpu directory will be generated, indicating that the Padddle Lite based FastDeploy library has been compiled.
## Python compile
The compilation command is as follows: