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

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

Deploy to RK1808 device  adb push install / rknn_mobilenet_demo /
userdata /

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"