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93 lines
3.4 KiB
Markdown
93 lines
3.4 KiB
Markdown
English | [中文](../../../cn/faq/rknpu2/environment.md)
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# FastDeploy RKNPU2 inference environment setup
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## Introduction
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We need to set up the development environment before deploying models on FastDeploy. The environment setup of FastDeploy is divided into two parts: the board-side inference environment setup and the PC-side model conversion environment setup.
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## Board-side inference environment setup
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Based on the feedback from developers, we provide two ways to set up the inference environment on the board: one-click script installation script and command line installation of development board dirver.
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### Install via script
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Most developers don't like complex command lines for installation, so FastDeploy provides a one-click way for developers to install stable RKNN. Refer to the following command to set up the board side environment
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```bash
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# Download and unzip rknpu2_device_install_1.4.0
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wget https://bj.bcebos.com/fastdeploy/third_libs/rknpu2_device_install_1.4.0.zip
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unzip rknpu2_device_install_1.4.0.zip
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cd rknpu2_device_install_1.4.0
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# RK3588 runs the following code
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sudo rknn_install_rk3588.sh
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# RK356X runs the following code
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sudo rknn_install_rk356X.sh
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```
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### Install via the command line
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For developers who want to try out the latest RK drivers, we provide a method to install them from scratch using the following command line.
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```bash
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# Install the required packages
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sudo apt update -y
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sudo apt install -y python3
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sudo apt install -y python3-dev
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sudo apt install -y python3-pip
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sudo apt install -y gcc
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sudo apt install -y python3-opencv
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sudo apt install -y python3-numpy
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sudo apt install -y cmake
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# Download rknpu2
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# RK3588 runs the following code
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git clone https://gitee.com/mirrors_rockchip-linux/rknpu2.git
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sudo cp ./rknpu2/runtime/RK3588/Linux/librknn_api/aarch64/* /usr/lib
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sudo cp ./rknpu2/runtime/RK3588/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/
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# RK356X runs the following code
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git clone https://gitee.com/mirrors_rockchip-linux/rknpu2.git
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sudo cp ./rknpu2/runtime/RK356X/Linux/librknn_api/aarch64/* /usr/lib
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sudo cp ./rknpu2/runtime/RK356X/Linux/rknn_server/aarch64/usr/bin/* /usr/bin/
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```
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## Install rknn_toolkit2
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There are dependency issues when installing the rknn_toolkit2. Here are the installation tutorial.
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rknn_toolkit2 depends on a few specific packages, so it is recommended to create a virtual environment using conda. The way to install conda is omitted and we mainly introduce how to install rknn_toolkit2.
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### Download rknn_toolkit2
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rknn_toolkit2 can usually be downloaded from git
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```bash
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git clone https://github.com/rockchip-linux/rknn-toolkit2.git
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```
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### Download and install the required packages
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```bash
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sudo apt-get install libxslt1-dev zlib1g zlib1g-dev libglib2.0-0 \
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libsm6 libgl1-mesa-glx libprotobuf-dev gcc g++
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```
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### Install rknn_toolkit2 environment
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```bash
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# Create virtual environment
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conda create -n rknn2 python=3.6
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conda activate rknn2
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# Install numpy==1.16.6 first because rknn_toolkit2 has a specific numpy dependency
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pip install numpy==1.16.6
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# Install rknn_toolkit2-1.3.0_11912b58-cp38-cp38-linux_x86_64.whl
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cd ~/Download /rknn-toolkit2-master/packages
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pip install rknn_toolkit2-1.3.0_11912b58-cp38-cp38-linux_x86_64.whl
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```
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## Resource links
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* [RKNPU2, rknntoolkit2 development board download Password：rknn](https://eyun.baidu.com/s/3eTDMk6Y)
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## Other documents
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- [RKNN model conversion document](./export.md)
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