Plant Segmentation Dataset
In collaboration with Aarhus University
Humans in the Loop is happy to publish open access segmentation masks for a dataset provided by the Computer Vision and Biosystems Signal Processing Group at the Department of Electrical and Computer Engineering at Aarhus University.
The dataset contains 144 images of plant seedlings from 3 containers shot at different time intervals within the span of 2 months. Each container contains up to 40 single plants, each one of which has been marked with a bounding box for better visibility.
Humans in the Loop has performed full semantic segmentation using masks on the images in 2 classes: plant and background (soil, container). The masks are ultra-precise and follow each plant’s leaf structure.
The images were kindly annotated by the trainees of the Preemptive Love Coalition’s WorkWell program in Iraq.
This object detection dataset is dedicated to the public domain by Humans in the Loop under CC0 1.0 license 
Dataset size
The dataset includes 114 images from 3 containers.
Classes
The images are segmented in two classes:
- #000000⬛- background
- #78C814🟩 – plant
