This document provides a detailed introduction for beginners on how to quickly use RKNN-Toolkit2 on a computer to perform model conversion and deploy it to a edg2l board using RKNPU2. The examples used in this document are integrated into the RKNN Model Zoo.

The version information we are using is as follows:
python: 3.8
rknn-toolkit2: 2.3.2
rknn model zoo: 2.3.2

It is recommended to create a new directory to store the RKNN repositories. For example, create a folder named “Projects” and place the RKNN-Toolkit2 and RKNN Model Zoo repositories in that directory. Refer to the following commands

$ mkdir Projects && cd Projects 

Download the RKNN-Toolkit2 repository

$ git clone -b v2.3.2 https://github.com/airockchip/rknn-toolkit2.git --depth 1

Download the RKNN Model Zoo repository

$ git clone -b v2.3.2 https://github.com/airockchip/rknn_model_zoo.git --depth 1

If the Python 3.8 environment is not installed on your system, or if there are multiple versions of Python installed, it is recommended to use Miniforge Conda to create a new Python 3.8 environment.

Download the Miniforge Conda installer from the following link:

$ wget -c https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh

Then, install Miniforge Conda using the following command:

$ chmod 777 Miniforge3-Linux-x86_64.sh 
$ bash Miniforge3-Linux-x86_64.sh

$ source ~/miniforge3/bin/activate

$ conda create -n py38Toolkit2.3.2 python=3.8

$ conda activate py38Toolkit2.3.2