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README.md

Background

Recently while taking Practical Deep Learning for Coders I hatched a plan to get my nieces curious about machine learning. They’re obsessed with the movie “Frozen” and love puzzles, so I created an image classifier that could identify the friendly snowman Olaf, and the abominable snowman. I hosted it on the web so they could upload their own images and try to “trick” the deep learning classifier into labeling an image of Olaf as the abominable snowman.

Goal

Using the fast.ai library, select & fine tune a convolutional neural network (CNN) architecture to identify 2 classes of images. Host the model on the web so others can try it out & upload their own images for it to classify. Use a simple hosting service like Binder (binder.org) to minimize time spent setting up hosting.

Approach

I selected resnet18 because it’s one of the smallest CNN architectures. I sourced training data from 300 images, 150 for each class, from the Bing search API. The model detects Olaf with x% precision and y% recall and detects the abominable snowman with x% precision and y% recall on the top 150 images of each class on Bing.

Outcome

The project was a success. The classifier is live online at https://mybinder.org/v2/gh/megano/snowpeopleApp/master?urlpath=%2Fvoila%2Frender%2Fsnowpeople_voila.ipynb. To try out the model, visit the URL and follow the instructions you’ll see on the page.

Limitations & Repo Navitation

The model is trained on 2 classes. It does work on permutations of features, recognizing Olaf when his features appear on a toilet paper roll for example, but won't likely generalize beyond these 2 very specific classes of snowman that it was trained on. This repo contains code for the model, and a simple front-end hosted on mybinder.org. Details on the files, and data used for training below.

  • export.pkl - Reduced model size under 50MB. Built with resnet18, image size reduced to 64px for training, and same 300 images, but lower resolution. Reduced to work within Binder app hosting constraints.

  • export-81MB.pkl - Original sized model export here for reference. Built with resnet18, and 300 images from Bing search API: 150 images of abominable snowman, 150 of Olaf.

  • requirements.txt - Lists dependencies.

  • snowpeople_voila.ipynb - Notebook with basic python widgets for UI, and path to the model file that Binder uses to generate the production UI.

About

Interactive deep learning CNN image classifier that identifies the friendly snowman Olaf and the abominable snowman.

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