K1702 - Kura Clover (Trifolium ambiguum) USDA Accession Image Dataset

Images This dataset consists of 1135 images of Kura clover (Trifolium ambiguum) USDA accessions grown at The Land Institute in Salina, Kansas over the 2017 growing season. Each image contains a single Kura clover plant framed by a 1/2" PVC sampling quadrat with internal dimensions of 16"x16" (internal area of 0.165 m2). Kura clover plots were hand weeded to remove all other vegetation except Kura clover. Some images may contain dead clover accessions that are either brown and dried up, or missing entirely. The images were acquired with a Canon EOS Rebel T6 DSLR camera under the following settings: ISO: 200 Exposure: Auto Focal Length: Variable (33-40mm) Format: JPEG Size: 5184x3456 Metering Mode: Multi-segment Images were acquired on two different dates: 2017-06-08 and 2017-07-03 and were named using the following convention "<IMG_ID>_<yyyymmdd>.jpg". All image can be found in processed/images folder. No image preprocessing was performed. Annotations The annotations consist of segmentation masks and bounding boxes. Each segmentation mask is saved as a png image and named using the convention "IMG_ID>_<yyyymmdd>.png". The segmentation class labels ('segmentation_class_map.json') are as follows: 0: 'soil' background class containing all soil and non-target materials 1: 'quadrat' 2: 'clover' We drew bounding boxes for the quadrat, each quadrat corner, and the entire clover plant. The class labels ('obj_det_class_map.json') are as follows: 1: 'clover' 2: 'quadrat' 3: 'quadrat_corner' Bounding boxes are in (xmin, ymin, xmax, ymax) format and can be found in 'bboxes.csv'. All images are annotated using Labelbox software. Masks were generated by point prompts using Meta's Segment Anything model (SAM). The point prompts used to generate the masks can be found in 'SAM_points.csv' Additionally, some kura clover plants died or are not present in the plots where they were planted. We included the file 'plant_status.csv' to indicate which images include a living plant or a dead one. Train/Val/Test Split All 1035 images were randomly split with an 80/20 split on 1000 of the images (n=880, n=220) with the final 35 images reserved for the test holdout set. The file 'data_split.csv' holds the split class for each image. This dataset is released under a Creative Commons Attribution 4.0 International license which allows redistribution and re-use of the data herein as long as all authors are appropriately credited.