Food Image Classification

Context:

Image classification has become less complicated with deep learning and the availability of larger datasets and computational assets. The convolution neural network is the most popular and extensively used image classification technique in recent days.

Clicks is a stock photography company and is an online source of images available for people and companies to download. Photographers from all over the world upload food-related images to the stock photography agency every day. Since the volume of the images that get uploaded daily will be high, it will be difficult for anyone to label the images manually.

Clicks have decided to use only three categories of food (Bread, Soup, and Vegetables-Fruits) for now, you as a data scientist at Clicks, need to build a classification model using a dataset consisting of images that would help to label the images into different categories.

Dataset Information:

The dataset folder contains different food images. The images are already split into Training and Testing folders. Each folder has three more subfolders named Bread, Soup, and Vegetables-Fruits. These folders have images of the respective classes.