# SOD - An Embedded Computer Vision & Machine Learning Library - [sod.pixlab.io](https://sod.pixlab.io) ![Output](https://i.imgur.com/YIbb8wr.jpg) 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. Designed for computational efficiency and with a strong focus on real-time applications. SOD includes a comprehensive set of both classic and state-of-the-art deep-neural networks with their pre-trained models. Built with SOD: * Convolutional Neural Networks (CNN) for multi-class (20 and 80) object detection & classification. * Recurrent Neural Networks (RNN) for text generation (i.e. Shakespeare, 4chan, Kant, Python code, etc.). * Decision trees for single class, real-time object detection. * A brand new architecture written specifically for SOD named RealNets. ![Multi-class object detection](https://i.imgur.com/Mq98uTv.png) Cross platform, dependency free, amalgamated (single C file) and heavily optimized. Real world use cases includes: * Detect & recognize objects (faces included) at Real-time. * License plate detection. * Intrusion detection. * Mimic Snapchat filters. * Classify human actions. * Object identification. * Eye & Pupil tracking. * Facial & Body shape extraction. * Image/Frame segmentation. #### 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. ![face detection using RealNets](https://i.imgur.com/ZLno8Lz.jpg)