In this tutorial, you will learn how to implement a simple scene boundary/shot transition detector with OpenCV.
In this tutorial, you will learn how to automatically find learning rates using Keras. This guide provides a Keras implementation of fast.ai’s popular “lr_find” method.
This article describes how to to use Microsoft Azure’s Cognitive Services Face API and python to identify, count and classify people in a picture. In addition, it will show how to use the service to compare two face images and tell if they are the same person. We will try it out with several celebrity look-alikes to see if the algorithm can tell the difference between two similar Hollywood actors. By the end of the article, you should be able to use these examples to further explore Azure’s Cognitive Services with python and incorporate them in your own projects.
For roughly $100 USD, you can add deep learning to an embedded system or your next internet-of-things project.
Are you just getting started with machine/deep learning, TensorFlow, or Raspberry Pi? Perfect, this blog series is for you!
But like in most cities, finding a parking space here is always frustrating. Spots get snapped up quickly and even if you have a dedicated parking space for yourself, it’s hard for friends to drop by since they can’t find a place to park.
My solution was to point a camera out the window and use deep learning to have my computer text me when a new parking spot opens up.