Food Vision

Food Vision using the EfficientNetB2 model and the Food-101 dataset

Related Fields: Deep Learning, Machine Learning, Programming

Project Overview

As I delved into the realms of deep learning through the “PyTorch for Deep Learning Bootcamp 2023-6” course on Udemy (52 hours and 14 minutes), I ended up building an amazing model. What if a model could decipher the mysteries behind our culinary delights with just a glance at a picture? 🍔📸 Thus, my journey began, crafting a neural network to discern the essence of every dish captured through the lens. Join me to see the flavors hidden within pixels.

Project Steps :

  1. Downloading the Food101 Dataset from the provided link.
  2. Prepare the data, ensuring that transforms and augmentations are ready.
  3. Utilize transfer learning techniques to prepare the model of EfficientNetB2.
  4. Train the model and deploy it into Hugging Face using the provided link.

Code Sources :

This model was built with PyTorch.

Here you can find all the code and results :

Github-Food-Vision 
HuggingFace-Space-Food-Vision

 

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