Dark Mode
Food Vision Pizza Elements
Food & Beverage Consumption
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
Pizza photographs and their corresponding segmentation masks are provided in this collection, designed for advanced food image analysis. The data aims to identify and delineate individual ingredients within pizza images, making it highly suitable for tasks such as object detection and semantic segmentation. The images feature pizzas captured from various angles and under diverse lighting conditions, while the mask segmentations precisely highlight ingredients by assigning each a distinct colour.
Columns
The dataset includes a
masks_info.csv file, which details the segmented elements and their assigned colours.- Element: This column lists the specific pizza component that has been segmented, such as pizza crust boundaries, slightly burnt crust edges, pepperoni or sausage, ham, ground beef, tomato, olives, and mushrooms. There are eight distinct values within this category.
- Colour: This column provides the unique hexadecimal colour code assigned to each element for its representation in the segmentation masks. There are eight distinct colour codes, each corresponding to an element.
Distribution
The dataset is organised into pizza photos, stored in an "Images" folder, and their associated mask segmentations. The
masks_info.csv file, which is 188 bytes in size and contains two columns, supports the segmentation masks by providing the mapping between elements and their colours. The exact quantity of pizza photos and masks is not specified, but the dataset is structured to facilitate computer vision applications.Usage
This dataset serves as an ideal resource for developing and training computer vision models. It can be applied to tasks such as food image segmentation, object detection within food items, semantic segmentation of culinary elements, food instance segmentation, food recognition systems, and food classification. Potential applications include automated ingredient recognition in food production or quality control in the restaurant industry.
Coverage
The dataset's focus is on pizza ingredients, offering detailed segmentation masks for common components found on pizzas. No specific geographic, time range, or demographic scope is detailed within the provided information. It is primarily an image-based resource for visual analysis of food.
License
the Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Who Can Use It
This dataset is particularly valuable for researchers and developers in the fields of computer vision and artificial intelligence, particularly those working on food technology, automated culinary systems, or dietary analysis. Machine learning engineers, academic institutions, and companies involved in image recognition for food products would find it highly useful for training and validating their models.
Dataset Name Suggestions
- Pizza Ingredient Segmenter
- Food Vision Pizza Elements
- Segmented Pizza Components
- Pizza Anatomy Dataset
Attributes
Original Data Source: Food Vision Pizza Elements
QUALITY