Real-time Shake Shack line counter using machine learning

Count is a machine learning company looking to quantify the organic data inside photos, video, and sound. Anybody that has lived in Manhattan understands the dynamics of the Shake Shack line in Madison Square Park. We thought it would be fun to practice our craft quantifying the Shake Shack line in real-time as our first experiment.

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same logo as Station
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@ohyesohyes I should have looked through the comments to see this before I wrote my own lol
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@ohyesohyes Ah yup very close. I didn't see that logo before but the space for using 1's and 0's is very crowded. Since we are counting - the logo is incrementing numbers up from 0 and also happens to look like a little face with the camera as the eye.
I love applications of AI to ordinary problems like how long the line to my fave restaurant is 😄 this is so cool @dimroc @thoughtmerchant, could you tell us more about your work and other use cases in future?
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Thanks @abadesi! We’re eager to expand to more retail locations and are excited to integrate into AWS DeepLens to provide an off the shelf solution. Right now we are creating experiments to display the insights we are able to glean from a camera. The Shake Shack line needs to deal with weather, heavy jackets, hats, shade, and a diversity of crowds. We would love to talk to companies looking to quantify interest in their storefront windows, understand pathfinding at large venues, calculate attention to advertising, and automate surf condition reporting. Honestly, if you have an interesting image problem, we would love to chat! /cc @dimroc
Great job!! 😊
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Looks like the same logo as station...are they related?