This document describes rv1109 vm and its tools.  
## Tools
### `VirtualBox-7.2.6a-172322-Win.zip`
- virtual box version 7.2.6
- vm : ubuntu 18.04, username: server, password: TNK#$104
### `python-3.9.13-amd64.zip` 
python installer which can be used to train `yolov5-master`  
### `wheels_win64_py39_cu117.zip`  
python wheel files which are yolov5 dependencies. cuda version is 11.7.  
### `yolov5-master.zip`  
ultralytics yolov5 repository. The models trained by this repository can be converted to rknn which can inference on RV1109 board. 


## VM Overview  
- All source code and toolchain exists in `home/server/Work` dirctory
- RV1109 and RV1126 has the same spec except for its NPU capacity is different. 

### 深圳RV1126开发资料   
This is a toolchain of `深圳RV1126开发板` and it might mismatched with the actual RV1109 board. 
The toolchain is exactly installed in `/home/thomas/rv1126/repo_new` directory and verified for compile succed. 
This toolchain is used as reference purpose.  

### RKNN-TOOLKIT
- the last version of rknn-toolkit for RV1109 is 1.7.1. see `rknn-toolkit17.tar.gz`.  
It contains sample code to convert and test several CNN models on RV1109 and RV1126 including onnx and darknet. 
I provided the another sample code to convert ultralytics yolov5 into rknn.  
- `rknn-toolkit-v1.7.1-packages`: It contains python packages of RKNN-toolkit, and it is already installed on system python env(3.6.9). 
So no need to install again.  
- `yolov5`
This is a repository to convert the ultralytics yolo model into rknn.  
The source code which can train ultralytics on windows11-GPU env will be shared in either way. `yolov5` folder only can be used to convert to rknn model. 
The dedicated conda env(`conda activate yolov5`) is installed to convert the model. 
To reference details steps for model conversion, see `~/Work/yolov5/ultralytics/yolov5-master/script/convert.md` file. 
This repository contains the python code to inference yolov5 rknn model on RV1109. C++ inferencing code should be modified based on yolov3 inference code.