Radar-Camera Fusion Object Detection System

This project implements a real-time radar-camera fusion system for robust object detection in complex environments. It leverages YOLOv8 for visual inference, with CUDA-accelerated pre- and post-processing and TensorRT-based deployment for high-performance execution. By fusing complementary data from radar and camera sensors, the system significantly improves perception accuracy and reliability under diverse conditions.

✨ Key Features

Radar-Camera Sensor Fusion
YOLOv8-Based Detection
C++17 Implementation
Modular Design
Visual Output Support

📁 Project Structure

radar_image/
├── config/              
├── include/             
├── msgs/                
├── src/                 
├── ultralytics-8.0.40/  
├── workspace/              
├── CMakeLists.txt       
└── README.md

🔧 Build Dependencies

C++ compiler with C++17 support (e.g., g++ >= 7)
CMake ≥ 3.10
OpenCV ≥ 4.0
jsoncpp
Protobuf ≥ 3.0

⚙️ Build & Run

mkdir build
cd build
cmake .. -DCMAKE_CXX_STANDARD=17
make -j$(nproc)
./yolo_refactor

🧪 Filtering Visualization

The following visual examples show detection results before and after the radar-camera fusion filtering process:

Before Filtering

After Filtering

🙏 Acknowledgements

This project makes use of the following open-source resources:

Phoenix8215/Radar-Camera-Fusion-Object-Detection