Articles

Posting of projects sources by Microsoft is a good reason to perform their analysis. This time is no exception, and today, we will look at suspicious places found in Infer.NET code.

Briefly About the Project and the Analyzer

Infer.NET is a Machine Learning system developed by Microsoft specialists. Project source code has become recently available on GitHub, which gave rise to its check. More details about the project can be found here.


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Introduction

The goal of this article is to explain how you can detect a drowsy person using facial landmarks as an input of a neural network, a 3D convolutional neural network, in this case, to sound an alarm to awake the user and to prevent some kind of accident.

The idea is to extract a group of frames from a webcam and then extract from them the facial landmarks, specifically the position of both eyes, then pass these coordinates to the neural model to get a final classification which will tell us if the user is awake, or falling sleep.


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In preparation for my talk at the Philadelphia Open Source Conference, Apache Deep Learning 201, I wanted to have some good images for running various Apache MXNet Deep Learning Algorithms for Computer Vision. 

Using Apache open source tools – Apache NiFi 1.8 and Apache MXNet 1.3 with GluonCV I can easily ingest live traffic camera images and run Object Detection, Semantic Segmentation and Instance Segmentation.


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Features of Tensorflow

Below, we are discussing some important TensorFlow Features.

Responsive Construct

With TensorFlow, we can easily visualize each and every part of the graph, which is not an option while using Numpy or SciKit.


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