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This is an image classification project developed for #SchoolofAIVancouver Coding Challenge 2. It classifies video game genres.

Jupyter Notebook 100.00%

video_game_classify's Introduction

Classify This Video Game!

This project was created for #SchoolofAIVancouver Image Classification Code Challenge 2. This image classification code tries to classify video games into 3 classes:

  • First Person Shooter(FPS)

FPS

  • Real Time Strategy(RTS)

RTS

  • Sports(SPT)

SPT

Getting Started

You can clone the repo to retrain and test the model. However please not that there arent any 'train', 'validate' or 'test' data in this repo. It has been removed to avoid uploading all the images to git.

Look at the 'ytvid-to-jpg' script to help with the data scraping

The video_game_classify.ipynb model training and classfiying screenshot

  • Model Training and Classifying modeltrain

Prerequisites

You will need the data which you can get using the video_game_classify.ipynb

Built With

  • Google Colaboratory- Free Jupyter notebook enviroment hosted in the cloud. Developed by Google.

  • Python3 - The programming language used

  • Keras - Keras: A high-level neural networks API running TensorFlow

  • ytvid-to-jpg - YTVID-TO-JPG: A custom python script that downloads Youtube video based on queries and converts it images.

Known Bugs

There are No known bugs in the video_game_classify.ipynb at this moment.

Disclaimer

The trained model in this image classifier is not perfect! The data used in this project was scraped from the Internet(Youtube). The dataset has not gone through rigorous data cleaning or parameter tuning techniques and there maybe some false positives during the labelling test. Feel free to retrain the model with a more accurate dataset.

Authors

  • Guru Shiva - Initial work

License

This project is licensed under the MIT License

Acknowledgments

video_game_classify's People

Contributors

gurushiva avatar

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