RKNN API

Rockchip provides a set of RKNN API SDK, which is a set of acceleration scheme for NPU hardware of neural network based on RK1808 Linux, and can provide general acceleration support for AI-related applications developed with RKNN API.

For the introduction of RKNN API SDK related APIs, please refer to Rockchip_RK1808_Developer_Guide_Linux_RKNN_EN.pdf in the SDK directory docs/Linux/NPU. The following is the introduction of RKNN API configuration and usage. For details, please refer to the examples in RKNN API.

1. Linux

The application only needs to include the header file and the dynamic library to write the relevant AI application.

Buildroot

The SDK provides MobileNet image classification, MobileNet SSD target detection, and Yolo v3 target detection demo for Linux platform. These demos can provide a reference for customers to develop their own AI applications based on the RKNN SDK. Demo code is located at <rk1808-linux-sdk>/external/rknpu/rknn/rknn_api/examples/rknn_mobilenet_demo as an example to explain how to get started quickly.

Demo use

1. Compile Demo

   cd examples / rknn_mobilenet_demo
   mkdir build && cd build
   cmake ..
   make && make install
   cd –

2. Deploy to RK1808 device

   adb push install / rknn_mobilenet_demo / userdata /

3. Run Demo

   adb shell
   cd / userdata / rknn_mobilenet_demo
   ./rknn_mobilenet_demo mobilenet_v1.rknn dog_224x224.jpg

Configuration

For details on how to configure rknn_api to compile the application, refer to the CMakeLists.txt file under the Demo.

The rknn_api header files and dynamic libraries are in the <rk1808-linux-sdk>/external/rknpu/rknn/rknn_api/examples/libs/librknn_api directory in the SDK.

├── include
│ └── rknn_api.h
└── lib64
  └── librknn_api.so

• Reference the dynamic library

LDFLAGS + = -lrknn_api

• Reference the rknn_api header file

#include "rknn_api.h"