Food-Vision-Project

This Project gives the name of the Food item from the picture we give it as input. (Only from 101 options)

Dataset

• We will get the data from Tensorflow Datasets (TFDS)

What is TensorFlow Datasets?

• A place for prepared and ready-to-use machine learning datasets.

Why use TensorFlow Datasets?

• Load data already in Tensors
• Practice on well established datasets
• Experiment with differet data loading techniques (like we're going to use in this notebook)
• Experiment with new TensorFlow features quickly (such as mixed precision training)

Why not use TensorFlow Datasets?

• The datasets are static (they don't change, like your real-world datasets would)
• Might not be suited for your particular problem (but great for experimenting)

Dataset we are going to use -> https://www.tensorflow.org/datasets/catalog/food101

Modelling

• We will be using Transfer Learning technique(EfficientNetB0).
• We will build 2 Models
  1. Feature Extraction Model
  2. Fine Tuning Model

Accuracy

Our Goal is to beat DeepFood, a 2016 paper which used a Convolutional Neural Network trained for 2-3 days to achieve 77.4% top-1 accuracy.