Symisc Systems is pleased to release the first major version of the SOD library! SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices.
SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.
Notable SOD features
- Built for real world and real-time applications.
- State-of-the-art, CPU optimized deep-neural networks including the brand new, exclusive RealNets architecture.
- Patent-free, advanced computer vision algorithms.
- Support major image format.
- Simple, clean and easy to use API.
- Brings deep learning on limited computational resource, embedded systems and IoT devices.
- Easy interpolatable with OpenCV or any other proprietary API.
- Pre-trained models available for most architectures.
- CPU capable, RealNets model training.
- Production ready, cross-platform, high quality source code.
- SOD is dependency free, written in C, compile and run unmodified on virtually any platform & architecture with a decent C compiler.
- Amalgamated - All SOD source files are combined into a single C file (sod.c) for easy deployment.
- Open-source, actively developed & maintained product.
- Developer friendly support channels.
Programming Interfaces
The documentation works both as an API reference and a programming tutorial. It describes the internal structure of the library and guides one in creating applications with a few lines of code. Note that SOD is straightforward to learn, even for new programmer.
SOD in 5 minutes or less
A quick introduction to programming with the SOD Embedded C/C++ API with real-world code samples implemented in C.
C/C++ API Reference Guide
This document describes each API function in details. This is the reference document you should rely on.
SOD Github Repository
The official Github repository.
C/C++ Code Samples
Real world code samples on how to embed, load models and start experimenting with SOD.
