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Private Edge – Shoe Image Classifier Challenge

June 11 @ 8:00 am - June 19 @ 5:00 pm EDT

Challenge Overview


The objective of this challenge is to train a machine learning or deep learning model (and wrap it into a function and a CLI) that can classify shoe images by type.

The primary requirements are:

  • Train a ML/DL model to classify images of shoesThe ML/DL model should be able to take as input an image and classify them in one of the following categories: sneakers, boots, loafers, sandals, flip_flops, soccer_shoes, no_shoe_found. A Jupyter notebook of the training steps needs to be shared in the submission.
  • Assemble your own datasetThe contestants are free to assemble their own image dataset to train their models. (Note that while acquiring the images or building the dataset, no licensing agreements should be violated such that it does not allow commercial use of the final trained model).
  • The model should be wrapped into a function named classify_imagesA function called classify_images should be created, which should be able to receive a set of images as input and should return their categories as output.


The goal of the project is to build a demo image classification application for our client Private Edge that can take as input an image, classify it and then perform some additional operations based on the classification.

Note that in this particular challenge, we are NOT building the application or the API, and will also NOT build the functionality in this challenge to perform the additional operations based on the classification. These requirements will be covered in the next challenge.

In the current challenge, the tasks are limited to building the classification model and wrapping it into a function, such that it is very easy to invoke this function by the additional API and web components that will be built in the future.

More information: https://www.topcoder.com/challenges/ea6839ca-fa82-4ac9-9665-65ca738a1d46

This is a virtual event.


June 11 @ 8:00 am EDT
June 19 @ 5:00 pm EDT


AlefEdge & Topcoder


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