Update README.md

README.md

@@ -4,20 +4,39 @@ SOD is an embedded, modern cross-platform computer vision and machine learning s
 
 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 <a href="https://pixlab.io/downloads" target="_blank">pre-trained models</a>. Built with SOD:
+* <a href="https://sod.pixlab.io/intro.html#cnn">Convolutional Neural Networks (CNN)</a> for multi-class (20 and 80) object detection & classification.
+* <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.).
+* <a href="https://sod.pixlab.io/samples.html">Decision trees</a> for single class, real-time object detection.
+* A brand new architecture written specifically for SOD named <a href="https://sod.pixlab.io/intro.html#realnets">RealNets</a>.
+
+![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.
+* 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>.
+* Patent-free, advanced computer vision <a href="https://sod.pixlab.io/samples.html">algorithms</a>.
+* Support major <a href="https://sod.pixlab.io/api.html#imgproc">image format</a>.
+* Simple, clean and easy to use <a href="https://sod.pixlab.io/api.html">API</a>.
 * 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.
+* Easy interpolatable with <a href="https://sod.pixlab.io/api.html#cvinter">OpenCV</a> or any other proprietary API.
+* <a href="https://pixlab.io/downloads" target="_blank">Pre-trained models</a> available for most architectures.</li>
+* CPU capable, <a href="https://sod.pixlab.io/c_api/sod_realnet_train_start.html">RealNets model training</a>.
 * 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.
+* SOD is dependency free, written in C, compile and run unmodified on virtually any platform &amp; architecture with a decent C compiler.
+* <a href="https://pixlab.io/downloads">Amalgamated</a> - 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.
+* Developer friendly <a href="https://sod.pixlab.io/support.html">support channels.</a>
 
 ![face detection using RealNets](https://i.imgur.com/ZLno8Lz.jpg)