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

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
Data Labeling
Data collection
Computer Vision
Restaurant business
2 500
> 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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