myriad

Mirror of Apache Myriad (Incubating)

F# computational expressions to reduce boilerplate in Pulumi code

A ROS package to wrap openvino inference engine and get it working with Myriad and GPU

Advanced driver-assistance system with Google Coral Edge TPU Dev Board / USB Accelerator, Intel Movidius NCS (neural compute stick), Myriad 2/X VPU, Gyrfalcon 2801 Neural Accelerator, NVIDIA Jetson Nano and Khadas VIM3

Wrapper package for OpenCV with Inference Engine python bindings.

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

Multiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.

Provides a conversion flow for YOLACT_Edge to models compatible with ONNX, TensorRT, OpenVINO and Myriad (OAK). My own implementation of post-processing allows for e2e inference. Support for Multi-Class NonMaximumSuppression, CombinedNonMaxSuppression.

Uses Myriad to generate type safe reflection calls to internal functions/properties/methods.

Web application for creating training plans, UW ECE FYDP

A Myriad plugin to generate test classes from behaviors.

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

Myriad RPC wrapper written in java.

DepthAI SPI Library

An overview of the alwaysAI applications available on GitHub.

📙 Source code for "A Design Space Exploration Framework for Convolutional Neural Networks Implemented on Edge Devices", CODES+ISSS '18.

Intel NCS2 device plugin for Kubernetes

Jekyll blog demo for Myriad Creative Services, creators of Gemini Station

Trabajo Fin de Máster: Estudio comparativo de un clasificador de imágenes en Raspberry Pi, de forma que se compara el tiempo de la inferencia en la Raspberry Pi con y sin el Neural Compute Stick (NCS). También se estudia como la complejidad de una red neuronal repercute en el tiempo de inferencia y se analiza si los tiempos obtenidos con el NCS en la Raspberry Pi se igualan a los conseguidos por la CPU del portátil y a los de una GPU de Google Colab.

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.