Laboro Tomato Dataset

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Laboro Tomato Dataset

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Laboro Tomato

Use Case

Laboro Tomato

Description

Explore the Laboro Tomato Dataset, featuring high-quality annotated images of tomatoes at various ripening stages. Perfect for agricultural research

Description:

The Laboro Tomato Dataset is an extensive and highly detailed collection of annotated images designed to aid in the study of tomato growth, ripeness detection, and agricultural monitoring. It is specifically curated for use in object detection and instance segmentation tasks, providing a valuable resource for researchers and developers working on agricultural automation, AI-driven quality control, and crop management systems. The dataset captures tomatoes at various stages of ripeness, from green to fully ripe, across different environmental conditions such as lighting, weather, and time of day. Images are carefully collected from a local farm over an extended period, ensuring diversity in the dataset by reflecting real-world agricultural scenarios.

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Key Features

Stages of Ripening: Detailed images capturing tomatoes at different growth stages.
Size-Based Subsets: Includes two subsets categorized by the size of tomatoes, enabling specific size-based analysis.
High-Quality Annotations: Each image is annotated to assist in precise object detection and segmentation tasks.
Versatile Data Collection: Utilized dual-camera setup to ensure diversity in resolution and image quality.

Applications

Agricultural Research: Helps in monitoring and studying the growth patterns of tomatoes.
AI and Machine Learning: Ideal for training models focused on agricultural automation, including ripeness detection and quality assessment.
Supply Chain Optimization: Assists in developing systems for better sorting, grading, and packaging of tomatoes based on their ripeness and size.