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82 lines
6.3 KiB
82 lines
6.3 KiB
<h1 align="center">SOD<br/><br/>An Embedded Computer Vision & Machine Learning Library<br/><a href="https://sod.pixlab.io">sod.pixlab.io</a></h1>
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[](https://travis-ci.org/symisc/sod)
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[](https://sod.pixlab.io/api.html)
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[](https://pixlab.io/downloads)
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[](https://sod.pixlab.io/intro.html)
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[](https://pixlab.io/downloads)
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[](https://groups.google.com/d/forum/sod-embedded)
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[](https://gitter.im/sodcv/Lobby)
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* [Introduction](#sod-embedded).
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* [Features](#notable-sod-features).
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* [Programming with SOD](#programming-interfaces).
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* [Useful Links](#other-useful-links).
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## SOD Embedded
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[Release 1.1.8](https://pixlab.io/downloads)
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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.
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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.
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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 <a href="https://pixlab.io/downloads">pre-trained models</a>. Built with SOD:
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* <a href="https://sod.pixlab.io/intro.html#cnn">Convolutional Neural Networks (CNN)</a> for multi-class (20 and 80) object detection & classification.
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* <a href="https://sod.pixlab.io/api.html#cnn">Recurrent Neural Networks (RNN)</a> for text generation (i.e. Shakespeare, 4chan, Kant, Python code, etc.).
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* <a href="https://sod.pixlab.io/samples.html">Decision trees</a> for single class, real-time object detection.
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* A brand new architecture written specifically for SOD named <a href="https://sod.pixlab.io/intro.html#realnets">RealNets</a>.
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Cross platform, dependency free, amalgamated (single C file) and heavily optimized. Real world use cases includes:
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* Detect & recognize objects (faces included) at Real-time.
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* License plate extraction.
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* Intrusion detection.
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* Mimic Snapchat filters.
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* Classify human actions.
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* Object identification.
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* Eye & Pupil tracking.
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* Facial & Body shape extraction.
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* Image/Frame segmentation.
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## Notable SOD features
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* Built for real world and real-time applications.
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* State-of-the-art, CPU optimized deep-neural networks including the brand new, exclusive <a href="https://sod.pixlab.io/intro.html#realnets">RealNets architecture</a>.
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* Patent-free, advanced computer vision <a href="https://sod.pixlab.io/samples.html">algorithms</a>.
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* Support major <a href="https://sod.pixlab.io/api.html#imgproc">image format</a>.
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* Simple, clean and easy to use <a href="https://sod.pixlab.io/api.html">API</a>.
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* Brings deep learning on limited computational resource, embedded systems and IoT devices.
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* Easy interpolatable with <a href="https://sod.pixlab.io/api.html#cvinter">OpenCV</a> or any other proprietary API.
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* <a href="https://pixlab.io/downloads">Pre-trained models</a> available for most architectures.</li>
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* CPU capable, <a href="https://sod.pixlab.io/c_api/sod_realnet_train_start.html">RealNets model training</a>.
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* Production ready, cross-platform, high quality source code.
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* SOD is dependency free, written in C, compile and run unmodified on virtually any platform & architecture with a decent C compiler.
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* <a href="https://pixlab.io/downloads">Amalgamated</a> - All SOD source files are combined into a single C file (*sod.c*) for easy deployment.
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* Open-source, actively developed & maintained product.
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* Developer friendly <a href="https://sod.pixlab.io/support.html">support channels.</a>
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## Programming Interfaces
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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.
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Resources | Description
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------------ | -------------
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<a href="https://sod.pixlab.io/intro.html">SOD in 5 minutes or less</a> | A quick introduction to programming with the SOD Embedded C/C++ API with real-world code samples implemented in C.
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<a href="https://sod.pixlab.io/api.html">C/C++ API Reference Guide</a> | This document describes each API function in details. This is the reference document you should rely on.
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<a href="https://sod.pixlab.io/samples.html">C/C++ Code Samples</a> | Real world code samples on how to embed, load models and start experimenting with SOD.
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<a href="https://sod.pixlab.io/articles/license-plate-detection.html">License Plate Detection</a> | Learn how to detect vehicles license plates without heavy Machine Learning techniques, just standard image processing routines already implemented in SOD.
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<a href="https://sod.pixlab.io/articles/porting-c-face-detector-webassembly.html">Porting our Face Detector to WebAssembly</a> | Learn how we ported the <a href="https://sod.pixlab.io/c_api/sod_realnet_detect.html">SOD Realnets face detector</a> into WebAssembly to achieve Real-time performance in the browser.
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## Other useful links
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Resources | Description
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------------ | -------------
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<a href="https://pixlab.io/downloads">Downloads</a> | Get a copy of the last public release of SOD, pre-trained models, extensions and more. Start embedding and enjoy programming with.
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<a href="https://pixlab.io/sod">Copyright/Licensing</a> | SOD is an open-source, dual-licensed product. Find out more about the licensing situation there.
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<a href="https://sod.pixlab.io/support.html">Online Support Channels</a> | Having some trouble integrating SOD? Take a look at our numerous support channels.
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