Model Selection and Benchmarking with Modelplace.AI

Model Selection and Benchmarking with Modelplace.AI

Model Selection and Benchmarking with Modelplace.AI

“Let’s say you are a programmer who is new to AI. You want to use a person detector for your camera application for a client. Now, you are not an expert in AI, but a bit of googling informs you about the numerous options you have.

The most popular among them is probably YOLO which stands for You Only Look Once. The name is ironic because you actually do not look just once!

You look at YOLO v1, v2, v3, v4, v5, v6 – ok, we got a bit carried away. There is no v6 yet, but boy there are so many options! Which one do you pick?

Confused, you take a chance on YOLO v4.

You spend your blood, sweat, and tears for the next 4 hours checking out the GitHub repo, compiling with necessary prerequisites, downloading the model, and making everything work on a Raspberry Pi only to find the model is slow.

There was a Tiny version of YOLO you missed!

So, you do this all over again for Tiny YOLO v4. It works great, and you are happy…”

Source: learnopencv.com/model-selection-and-benchmarking-with-modelplace-ai