# 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)