# YOLO_RKNN_Acceleration_Program

**Repository Path**: lrf1125962926/yolo_rknn_acceleration_program

## Basic Information

- **Project Name**: YOLO_RKNN_Acceleration_Program
- **Description**: YOLO multi-threaded and hardware-accelerated inference framework based on RKNN
- **Primary Language**: C++
- **License**: Apache-2.0
- **Default Branch**: master
- **Homepage**: https://blog.csdn.net/plmm__/article/details/146542002?spm=1001.2014.3001.5501
- **GVP Project**: No

## Statistics

- **Stars**: 3
- **Forks**: 3
- **Created**: 2025-03-31
- **Last Updated**: 2025-08-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: RKNN, RK3588, Yolo, multi-threaded, hardware-acceleration

## README

# 🚀 YOLO RKNN Acceleration Program 
**基于 RK3588 的 YOLO 多线程推理多级硬件加速引擎框架设计** 

*YOLO multi-threaded and hardware-accelerated inference framework based on RKNN* 

---

## 📌 基线 / Baseline 
Forked from [leafqycc/rknn-cpp-Multithreading](https://github.com/leafqycc/rknn-cpp-Multithreading)

## 🏆 性能总结 / Performance Summary
- **141 FPS → 151 FPS** 超越基线  
  在作者的最高帧数141帧（C++）的基础上，使用 **RKmpp** 硬件解码和 **RGA** 硬件图像前处理，将推理帧数提高至 **151** 帧，还在优化中。
- 关键技术优化 / Key optimizations:
  - **RKmpp** 硬件解码 / *RKmpp hardware decoding*
  - **RGA** 硬件图像预处理 / *RGA hardware image preprocessing*

## 🛠 技术增强 / Technical Enhancements
- 🎭 多态视频加载器（OpenCV/FFmpeg动态切换）  
  *Polymorphic video loader (OpenCV/FFmpeg dynamic switching)*
- 🖥️ 命令行参数控制 / *Command-line parameter control*
- 🧠 优化内存管理 / *Optimized memory management*

---

## 📚 Project Analysis
### CSDN Articles:
- **Overview**: [![CSDN](https://img.shields.io/badge/CSDN-Overview-blue)](https://blog.csdn.net/plmm__/article/details/146542002)
- **Technical Analysis**: [![CSDN](https://img.shields.io/badge/CSDN-Analysis-blue)](https://blog.csdn.net/plmm__/article/details/146556955)

---

## 📋 快速开始指南 / Quick Start Guide
### 1️⃣ 环境准备 / Prerequisites 
- 开发板需要预装 OpenCV，一般出厂系统都有

    *OpenCV pre-installed (usually included in factory systems)*

### 2️⃣ 测试视频 / Test Video
- 下载 [Baseline](https://github.com/leafqycc/rknn-cpp-Multithreading) Releases 中的测试视频，放项目的根目录

    *Download test video from Baseline Releases and place in project root*

### 3️⃣ (可选) 定频 / (Optional) Frequency Locking
- 可切换至 root 用户运行 `performance.sh` 定频提高性能和稳定性  
    *Run as root: `./performance.sh`*

### 4️⃣ 板端编译 / Board-side Compilation
- 运行 `build.sh`，该脚本会配置并编译 `CMakeLists.txt` 

    *Run `build.sh` to configure and compile `CMakeLists.txt`*

- 没有使用 `install` 进行安装，而是直接执行编译后的程序，节约空间 

    *No `install` used, directly execute the compiled program to save space*

### 5️⃣ 执行推理 / Run Inference
```bash
./detect.sh
```
- 使用 `detect.sh` 进行推理，脚本会根据项目预定的命令行参数进行填写，然后执行编译后的可执行文件

    *Run `detect.sh` to perform inference, the script will fill in the command-line parameters as per the project's predefined parameters, and then execute the compiled executable.*

- 可以根据自己的实际情况修改脚本参数，例如模型路径和视频路径

    *You can modify the script parameters according to your actual situation, such as the model path and video path.*
    

- 也可以直接执行可执行程序，会打印命令行参数提示

    *You can also directly execute the executable program, which will print the command-line parameter prompts.*

---

## 📂 项目结构 / Project Structure
- `reference` 目录是官方的 demo
- `clean.sh` 用于清除编译生成的文件
- ffmpeg 已经移植到项目中
- `librga` 和 `librknnrt` 已更新至目前的最新版本
- `performance.sh` 是官方的定频脚本

```bash
├── 📜 build.sh
├── 📜 clean.sh
├── 📜 CMakeLists.txt
├── 📜 detect.sh
├── 📂 include/
│   ├── 🖼️ drm_func.h
│   ├── 📹 ffmpeg/
│   ├── ⚙️ parse_config.hpp
│   ├── 🔍 postprocess.h
│   ├── ✨ preprocess.h
│   ├── 📖 reader/
│   ├── 🖥️ rga/
│   ├── 🧠 rknn/
│   ├── 🏊 rknnPool.hpp
│   ├── 🎯 rkYolo.hpp
│   ├── 🔗 SharedTypes.hpp
│   └── 🧵 ThreadPool.hpp
├── 📂 lib/
│   ├── 📹 ffmpeg/
│   ├── 🖥️ librga.so
│   ├── 🔗 librknn_api.so -> librknnrt.so
│   └── 🧠 librknnrt.so
├── 📂 model/
│   ├── 🏷️ coco_80_labels_list.txt
│   └── 🖥️ RK3588/
├── 📜 performance.sh
├── 📂 reference/
│   ├── 📹 ffmpeg_mpp_test.cpp
│   ├── 🖥️ ffmpeg_rga_test.cpp
│   ├── 🎥 main_video.cc
│   └── 🖼️ rga_*.cpp
└── 📂 src/
    ├── 🎯 main.cpp
    ├── ⚙️ parse_config.cpp
    ├── 🔍 postprocess.cpp
    ├── ✨ preprocess.cpp
    ├── 📖 reader/
    └── 🎯 rkYolo.cpp
```

## 联系方式 / Contact
### 开发者 / Developer​​:
✉️ Email / QQ: 1125962926@qq.com

💬 欢迎合作优化RKNN加速方案！

*Let's collaborate on optimizing RKNN acceleration!*