1.1 NPU Usage

Platforms such as RK3588 come with a built-in NPU module; the RK3588 NPU offers processing performance of up to 6 TOPS.To use this NPU,you need to download the RKNN SDK.The RKNN SDK provides C++/Python programming interfaces, which help users deploy RKNN models exported by RKNN-Toolkit2,accelerating the deployment of AI applications. The overall development steps for RKNN are divided into three main parts: model conversion, model evaluation, board-side deployment and execution.

• Model Conversion
  converting models from Caffe、TensorFlow、TensorFlow Lite、ONNX、DarkNet、PyTorch etc.,to RKNN models.It also supports importing and exporting RKNN models, which can be used on the Rockchip NPU platform.
  
• Model Evaluation
  model evaluation phase helps users quantify and analyze model performance, including key metrics such as accuracy, on-board inference performance, and memory usage.
  
• Board-Side Deployment and Execution
  loading the RKNN model onto the RKNPU platform, and performing model preprocessing, inference, post-processing, and release.