Collecting photos of pizzas and labeling them by their constituent ingredients. The dataset is suitable for automating quality control of dishes in a restaurant network using machine learning

Semantic
Food Segmentation

Ability of a machine to interpret, analyze, and understand visual data

Dividing an image into semantically independent segments to determine object boundaries

Highlighting objects in photos to train systems to recognize and interpret them

Gathering data for subsequent annotation

The use of machine learning in the process of cooking and quality control of dishes, serving customers

Segmentation

Data Labeling

Data collection

Computer Vision

Restaurant business

2 500

images

> 10

labeling classes

4 weeks

project duration

Data Collection

We collected photos using parsing and crowdsourcing techniques

Qualified validators verified each image

You receive high-quality data with a one-year guarantee on our services

Collection parameters are customized to fit your task

Image Annotation

We determine the required labeling classes for your task, such as the ingredients of pizza that you are interested in

The annotation tool used is CVAT

Each class is accurately outlined with a polygon of a specific color

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