This project is an improved version of rknn-cpp-Multithreading, utilizing a thread pool to accelerate the processing and adding detailed comments to help beginners learn and use it more effectively.
- Thread Pool Acceleration: Uses thread pool technology to enhance model processing speed.
- Educational Comments: Adds detailed comments to key parts of the code to facilitate understanding and learning for beginners.(The comments are in Chinese)
- Open Source Foundation: Based on an open-source project, inheriting and extending its functionality.
To successfully build and run this project, you need to meet the following requirements:
- System Dependencies: OpenCV must be installed on your system.
- Build Tools: Use CMake to build the project.
This project uses the official model and converts it using the following tools:
- Model Conversion Tool: Uses the official rknn-toolkit2 for model conversion.
- Ensure OpenCV and CMake are installed.
- Clone the repository to your local machine:
git clone https://github.com/wzxzhuxi/rknn-3588-npu-yolo-accelerate
- Navigate to the project directory and create a build directory:
cd rknn-3588-npu-yolo-accelerate-master mkdir build && cd build
- Build the project using CMake:
cmake .. make
- Run the project:
./yolov5_detect <model> <video_source> <num_threads>