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DeepStack_USPS

This repository provides a custom DeepStack model that has been trained detecting ONLY the USPS logo. This was created after I discovered that the Deepstack OpenLogo custom model I was using did not contain USPS. The owner of that repo suggested that we create our own, so I decided to give it a shot!

In my use case, I have a Blue Iris clone of my main house cameras that is setup to NOT record. It's only set up to alert if it sees a car, truck, van or bus. The alert image is then sent over MQTT to node-red. It's then read in, and thrown against OpenLogo to see if it matches fedex, ups, amazon or dhl. If nothing is reported back, then I'll throw it against this USPS custom object end point. Essentially it's scanning each alert image multiple times, but its quick enough in processing that it should alert me when it sees the logo.

The main goal? My wife mails back her empty soda stream cannisters and then new ones are sent to us. Instead of having to head to a post office, its easier for us to catch our mail carrier and hand them the package when they're outside. Happy wife...

Create API and Detect Logos

The only logo in the model is "USPS". So this is a unique custom object endpoint that is only used for USPS detection. The way I understand it (which honestly, I just followed the directions), the AI training is based off of the images provided and the portion of the images that I tag with class names. So I could have done "truck" or "van" or "trailer" along with the USPS logo, but I wanted to keep things simple.

To start detecting, follow the steps below

Discover more Custom Models

Please visit the OpenLogo repository that started this whole thing. Almost all of this readme and code was copied from there. https://github.com/OlafenwaMoses/DeepStack_OpenLogo .

For more custom DeepStack models that has been trained and ready to use, visit the Custom Models sample page on DeepStack's documentation https://docs.deepstack.cc/custom-models-samples/ .

Train your own Model

If you will like to train a custom model yourself (this is what I did!), follow the instructions below.