该项目是运行在RK3588平台上的Yolo多线程推理demo，已适配读取视频文件和摄像头信号，demo采用Yolov8n模型进行...

# Yolov8/v10 Demo for RK3588 The project is a multi-threaded inference demo of Yolov8 running on the RK3588 platform, which has been adapted for reading video files and camera feeds. The demo uses the Yolov8n model for file inference, with a maximum inference frame rate of up to 100 frames per second. > If you want to test yolov8n with ros2 for yourself kit, click the [link](./yolov8n-ros2.md) # Model ## Download Model File you can find the model file in the 'src/yolov8/model', and some large files: Link: https://pan.baidu.com/s/1zfSVzR1G7mb-EQvs6A6ZYw?pwd=gmcs Password: gmcs Google Drive: https://drive.google.com/drive/folders/1FYluJpdaL-680pipgIQ1zsqqRvNbruEp?usp=sharing ## Model pt --> onnx ### For Yolov8 go to my blog --> [blog.kaylordut.com](https://blog.kaylordut.com/2024/02/09/rk3588's-yolov8-model-conversion-from-pt-to-rknn/#more) ### For Yolov10 go to my another repository --> [yolov10](https://github.com/kaylorchen/yolov10) download pt model and export: ```bash # End-to-End ONNX yolo export model=yolov10n/s/m/b/l/x.pt format=onnx opset=13 simplify ``` ## Model onnx --> rknn go to my blog --> [blog.kaylordut.com](https://blog.kaylordut.com/2024/02/09/rk3588's-yolov8-model-conversion-from-pt-to-rknn/#more) > TIPS: (Yolov10) > - rknn-toolkit2(release:1.6.0) does not support some operators about attention, so it runs attention steps with CPU, leading to increased inference time. > - rknn-toolkit2(beta:2.0.0b12) has the attention operators for 3588, so I build a docker image, you can pull it from __**kaylor/rknn_onnx2rknn:beta**__ ## Inference Time Please refer to the spreadsheet '[8vs10.xlsx](./8vs10.xlsx)' for details. |V8l-2.0.0| V8l-1.6.0| V10l-2.0.0| V10l-1.6.0| V8n-2.0.0 |V8n-1.6.0 |V10n-2.0.0| V10n-1.6.0| |:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:|:-------:| |133.07572815534| 133.834951456311| 122.992233009709| 204.471844660194| 17.8990291262136| 18.3300970873786| 21.3009708737864| 49.9883495145631| # Demo Video and Guideline https://space.bilibili.com/327258623?spm_id_from=333.999.0.0 QQ group: 957577822 # Prepare ## Build the Cross-Compilation Environment Set up a cross-compilation environment based on the following [link](https://github.com/kaylorchen/rk3588_dev_rootfs). ## Install Runtime Libraries in Your RK3588 Target Board ```bash cat << 'EOF' | sudo tee /etc/apt/sources.list.d/kaylordut.list deb [signed-by=/etc/apt/keyrings/kaylor-keyring.gpg] http://apt.kaylordut.cn/kaylordut/ kaylordut main EOF sudo mkdir /etc/apt/keyrings -pv sudo wget -O /etc/apt/keyrings/kaylor-keyring.gpg http://apt.kaylordut.cn/kaylor-keyring.gpg sudo apt update sudo apt install kaylordut-dev libbytetrack ``` > If your OS is not Ubuntu22.04, and find [kaylordut-dev](https://github.com/kaylorchen/kaylordut) and [libbytetrack](https://github.com/kaylorchen/ByteTrack) sources in my github. ## Build the Project for Your RK3588 - Compile ```bash git clone https://github.com/kaylorchen/rk3588-yolo-demo.git cd rk3588-yolo-demo/src/yolov8 mkdir build cd build cmake -DCMAKE_TOOLCHAIN_FILE=/path/to/toolchain-aarch64.cmake -DCMAKE_EXPORT_COMPILE_COMMANDS=ON .. make ``` > /path/to/toolchain-aarch64.cmake is .cmake file absolute path - Run ``` bash Usage: ./videofile_demo [--model_path|-m model_path] [--input_filename|-i input_filename] [--threads|-t thread_count] [--framerate|-f framerate] [--label_path|-l label_path] Usage: ./camera_demo [--model_path|-m model_path] [--camera_index|-i index] [--width|-w width] [--height|-h height][--threads|-t thread_count] [--fps|-f framerate] [--label_path|-l label_path] Usage: ./imagefile_demo [--model_path|-m model_path] [--input_filename|-i input_filename] [--label_path|-l label_path] ``` > you can run the above command in your rk3588