Tracking Plant Growth Using Image Sequence Analysis- Dataset

Published: 10 January 2025| Version 1 | DOI: 10.17632/zhc7z5xtg5.1
Contributors:
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Description

This dataset consists of five subsets with annotated images in COCO format, designed for object detection and tracking plant growth: 1. Cucumber_Train Dataset (for Faster R-CNN) - Includes training, validation, and test images of cucumbers from different angles. - Annotations: Bounding boxes in COCO format for object detection tasks. 2. Tomato Dataset - Contains images of tomato plants for 24 hours at hourly intervals from a fixed angle. - Annotations: Bounding boxes in COCO format. 3. Pepper Dataset - Contains images of pepper plants for 24 hours at hourly intervals from a fixed angle. - Annotations: Bounding boxes in COCO format. 4. Cannabis Dataset - Contains images of cannabis plants for 24 hours at hourly intervals from a fixed angle. - Annotations: Bounding boxes in COCO format. 5. Cucumber Dataset - Contains images of cucumber plants for 24 hours at hourly intervals from a fixed angle. - Annotations: Bounding boxes in COCO format. This dataset supports training and evaluation of object detection models across diverse crops.

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Institutions

Ben-Gurion University of the Negev

Categories

Object Detection, Agriculture

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