AI-Maharaj

The only Maharaj(Cook) you need to Classify your Indian Dishes. Try It!
Dataset and notebook here.

What it does

It is an Image Classifier that can classifiy images into 12 different Indian Dishes, which includes Chole Bhature, Pav Bhaji, Paneer Sabzi, Momos, Biryani, Butter Naan, Dhokla, Samosa, Chai, Jalebi, Gulab Jamun, Rasgulla.

More Info

• Built using PyTorch
• Used EfficientNet-B2 for Transfer Learning
• Manually Scraped 4739 Images of 12 different classes
• Achieved an accuracy of 93.4%
• Used LR scheduler
• Used Data Augmention to synthesise new data

Challenges I ran into

• Couldn't find a Indian Dishes Dataset, So had to create the dataset manually
• Couldn't find a Google Image Scraper, So I made a custom Google Image scraper script which can scrape multiple classes of images at a single time.
• The Dataset had only around 4000 images, So I used Data Augmentation to Augment Data.
• The training cost was not decreasing even in the initial stage, So I had to start from a different random point with larger learning rate.
• First I used ResNet101 model for transfer learning, but the model was too heavy to be run on heroku, So I changed the model and used EfficientNet-b2 as it a mobile model.

What I learned

• Transfer Learning Using PyTorch
• Deployment of model using Flask and Heroku
• Using LR Scheduler to decrease Learning Rate with epochs

MIT License

Copyright (c) 2021 Deep Rodge

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