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A classy example of using Akida's One-Shot Learning to determine if the object is a hotdog or not a hotdog.

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Not Hotdog powered by Akida One-Shot Learning

A classy example of using Akida's One-Shot Learning to determine if the object is a hotdog or not a hotdog.

This is an extremely loose example that takes only two images. One hotdog and one not hotdog. There is a training dataset out there specifically for the not hotdog app but I just wanted to experiment with a single image of a hotdog.

Setting up the Akida development evironment

  1. Go to https://www.anaconda.com/download/ and download installer
  2. Install anaconda bash Anaconda-latest-Linux-x86_64.sh
  3. Create conda environment conda create --name akida_env python=3.6
  4. Activate conda environement conda activate akida_env
  5. Install python dependencies pip install -r requirements.txt

Running and using the example

  1. python3 akida_not_hotdog.py
  2. Point webcam at object and press space to determine if it is a hotdog or not a hotdog
  3. If you want to teach it more hotdogs or not hotdogs, point webcam at something and press y if its a hotdog or n if its not hotdog

As seen in the hilarious TV Show Silicon Valley

The concept is taken from the TV show

Not Hotdog

Read More

Read all the documentation at https://doc.brainchipinc.com

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A classy example of using Akida's One-Shot Learning to determine if the object is a hotdog or not a hotdog.

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