The alwaysAI Blog

Lila Mullany

Lila Mullany
Intern with alwaysAI with a background in biomedical informatics and an interest in computer vision.

Recent Posts

Computer Vision on the Edge

Overcoming Challenges in Bringing CV Applications to Production

Developing a Computer Vision (CV) application and bringing it to production requires  integrating several pieces of hardware and software. How can we ensure the pieces work seamlessly together? With the right methodologies, we can expedite development and deployment of CV applications. It is essential to find a platform with the goal of helping developers create computer vision applications from scratch quickly and easily with...

Using alwaysAI's Model Training Tool to Build a License Plate Tracker

In this tutorial, we’ll cover how to create your own license plate tracker using the new license plate detection model, which was created using alwaysAI’s model training tool.

Using alwaysAI to Build Your Own License Plate Detection Model

In this tutorial, we’ll walk through the steps and decision points involved in the creation of the ‘alwaysai/vehicle_license_mobilenet_ssd’ model, an object detection model for identifying vehicles and license plates. 

Build Your Own Posture Corrector with Pose Estimation

Many of us spend most of our days hunched over a desk, leaning forward looking at a computer screen, or slumped down in our chair. If you’re like me, you’re only reminded of your bad posture when your neck or shoulders hurt hours later, or you have a splitting migraine. Wouldn’t it be great if someone could remind you to sit up straight? The good news is, you can remind yourself! In this tutorial, we’ll build a posture corrector app using a pose estimation model available from alwaysAI.

Using Pose Estimation on the Jetson Nano with alwaysAI

Many models, including those for pose estimation, may have much better performance when run on a GPU rather than a CPU. In this tutorial, we’ll cover how to run pose estimation on the Jetson Nano B01 and cover some nuances of running starter apps on this edge device.

Building and Deploying Apps on alwaysAI

Building and running your app on alwaysAI can be done a few different ways, depending on the platform you want to develop on and the device you want to deploy on. We’ve concentrated these options in one place for your convenience and we’ll update this document as the platform evolves!

Introduction to Computer Vision Model Training

Training a computer vision model is one component of a complex and iterative undertaking, which can often seem daunting. At alwaysAI we want to make the process simple and approachable. To get you started, we have compiled a general overview of the training process of Deep Neural Networks (DNNs) for use in computer vision applications. We will focus on supervised learning in this overview, which uses labeled training data to teach the model what the desired output is. This article provides...

Create Your Own Contraband Detector

Many people are now working or learning from home, introducing the new issue of enforcing professionalism and academic honesty by remote. Whether you are trying to prevent students from cheating on tests, want to double check that your kids aren’t just playing on their phones, or maybe you want to stop yourself from checking social media while you’re supposed to be working, computer vision can help. In this tutorial, I’ll show how you can create your own contraband object alert system using...

Create Your Own Virtual Green Screen

As you most likely noticed in the image above, the edges generated by this model are fairly large. In a subsequent tutorial, I’ll cover how to smooth these edges for a less blocky look!

Using Multiple Object Detection Models

In this article I will demonstrate how to easily modify existing apps offered with alwaysAI to use two object detection models simultaneously, and to display the output in side-by-side frames.