How I Built a Production-Ready AI Computer Vision Dashboard?

Imagine a traffic dashboard that prevents jams before they start.

Sounds impossible right?

Well, it is very possible and in this email, I will reveal how I did it.

The first step before you can do any sort of prediction is to start monitoring.

And this is fairly simple to do. You'll see tons of demos on LinkedIn of people doing simple vehicle detection with popular models like YOLOv5 or YOLOv8.

I mean you could simply use a pre-trained model which works fairly well, right?

Well yeah, but not quite.

There's another model that is required to ensure that you can make the most accurate predictions.

I'm of course talking about Object Tracking. 

Tracking enables you to not only count vehicles already detected but also enables you to monitor the speed of that specific vehicle.

So while you can easily count all the vehicles in a frame at any given time to say "Okay if we reach over 20 vehicles at any given time, it means we have a traffic jam."

That may not work always in solving the traffic jams and I'll tell you in a bit, but first, we need to look at some of the object tracking models available.

What are the optimal models for Object Tracking?

While there are several tracking models to use, here are some that are quite popular:

• NorFair
• DeepSORT
• StrongSORT
• FairMOT
• ByteTrack, amongst many others

Once you have selected a tracker, you can use the information to predict where vehicles are flowing to. If you have access to traffic lights or robots as they call them in some places, you'll be able to channel the flow of vehicles autonomously to alleviate traffic congestion.

How do you select the best model for Object Tracking?

Testing one tracker is easy but adapting your code to test all the other trackers is a huge challenge. We developed a special tool that we use in our YOLO courses, to easily switch between various YOLO models as well as various trackers.

The best part is...that you can benchmark all detectors and trackers in just 1 line of code!! Amazing right?

When you enroll in this course or even join Augmented AI University, you will get instant access to this tool.

Now on to the dashboard. Why did you develop it?

Now I could have just run the code and called it a day. But I wanted to go beyond.

The dashboard needed to look great, user-friendly and display all of the key information that one would need for monitoring traffic.

With the power of Flask, Bootstrap, and Computer Vision, I had my first prototype and it looked beautiful... and functional of course.

This is a dashboard that you can take into production, start monitoring and even predict traffic flow.

But why stop there?

What you will learn in this course can be applied to just about any other monitoring system that you can think of.

By using our code as your template, you could use this to monitor, animals, manufacturing line items, defects in materials, and even people (with their consent of course. 😁)

Great! I want to get started, how do I get this course?

You could purchase this course once off for $299, but for only today you can get it as part of Augmented AI University for only $20 per month.

What is Augmented AI University?

Augmented AI University is a brand new membership of $20 per month (only if you order today), in which you can get this course along with our other cutting-edge AI courses and every new course that we develop thereafter.

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