GstInference

A GStreamer deep learning inference framework.

GstInference is an open-source project from RidgeRun Engineering that provides a framework for integrating deep learning inference into GStreamer. Either use one of the included elements to do out of the box inference using the most popular deep learning architectures or leverage the base classes and utilities to support your own custom architecture.

Checkout the GstInference proposal presentation that RidgeRun gave at the GStreamer 2018 conference, at Edinburgh, Scotland, UK.

GstInference Benchmarks Overview

By using GstInference as the interface between Google’s Coral board and GStreamer, users can:

Easily prototype GStreamer pipelines with common and basic GStreamer tools such as gst-launch and GStreamer Daemon.
Easily test and benchmark TFLite models using GStreamer with Google's Coral board.
Enable a world of possibilities to use Google’s Coral board with video feeds from cameras, video files, and network streams, and process the prediction information (detection, classification, estimation, segmentation) to monitor events and trigger actions.
Develop intelligent media servers with recording, streaming, capture, playback, and display features.
Abstract GStreamer complexity in terms of buffers and events handling.
Abstract TensorFlow Lite complexity and configuration.
Make use of GstInference helper elements and API to visualize and easily extract readable prediction information.

GstInference can also be used in other platforms (Jetson, Desktop).

For further information you can check: Benchmarks page.

Framerate

CPU Usage

GstInference Videos

Promo video:

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