OpenVINO DL Streamer with GStreamer - Azure Marketplace app

Deep Learning (DL) Streamer is a component of OpenVINO™ Toolkit that offers a streaming analytics framework based on GStreamer* multimedia framework for creating complex media analytics pipelines using OpenVINO Inference Engine. It provides optimal pipeline interoperability and optimized inferencing across Intel® architecture, CPU, iGPU and Intel® Movidius™ VPU.

This container provides Intel® distribution of OpenVINO™ Toolkit with DL Streamer and OvdlStreamer app that provides a configurable pipeline for object detection, tracking and classification. The app can take multiple input streams, perform object detection, tracking and classification using pre-trained models required by the OpenVINO™ toolkit Inference Engine, and send the results to Azure IoT Cloud and/as RTSP out.

Click Here to Download OpenVINO DL Streamer - Azure IoT Edge Module

Image Semantic Segmentation with OpenVINO 2020.R2

The One Hundred Layers Tiramisu:Fully Convolutional DenseNets for Semantic Segmentation


Github (OpenVINO app code) to accelerate inference of FC-DenseNet-103 on Intel HW. Best performance can be seen on Cascade Lake Xeon CPU

OpenVINO Application code
OpenVINO FC-DenseNet-103 IR model files (FP32/FP16): IR Files

Note: IR files are generated from pre-trained TF FC-DenseNet-103 model file (with accuracy ~.60)

If you want to re-train: You can use Keras train.py