Nanopi M4 RK3399 base minimal image for development (mali fbdev / gbm) - Camera support

Library for modelling performance costs of different Neural Network workloads on NPU devices

Website for Eclipse ioFog, a distributed Edge Compute Network (ECN) platform

YOLO multi-threaded and hardware-accelerated inference framework based on RKNN

The Rockchip VPU driver module code for Linux, taken from rockchip-forwardports. I'm still hesitating between rockchip-vcodec and literate-octo-guacamole though...

mainline Kodi for rk35xx hwaccel Rockchip's MPP and RGA via ffmpeg-rockchip, via boogie/nyanmisaka/joshua/amazingfate magic; rk bsp/vendor/legacy kernel required.

Rockchip low latency video decoding

Single Shot MultiBox Detector deployed on a OAK-D Lite cam via DepthAI

A ROS package for offloading inference to the Intel Movidius VPU Neural Compute Stick. Also, Evaluation of the Intel Movidius VPU Neural Compute Stick for Real-Time Inference.

This repository contains detailed notes of all chapters and all three projects completed in Intel-Edge-AI NanoDegree.

Simple video player for NanoPi M3

The main focus area of this project is to propose a possible hardware solution for each scenario. Build out the application and test its performance on the DevCloud using multiple hardware types. Compare the performance to see which hardware performed best.

This projects takes features included in https://github.com/rockchip-linux/kernel and makes them buildable out-of-tree, on mainline kernel

Given real-world scenarios to build a queuing system and the hardware specifications, the user can identify which hardware types work best. The application tested using the Intel® DevCloud.

basic,intermidate,advanced levels of devlopment's