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

Images

This dataset consists of 1135 images of Kura clover (Trifolium ambiguum) USDA accessions grown in Salina, Kansas over the 2017 growing season. Each image contains a single Kura clover plant framed by a PVC sampling quadrat that has an internal area of 0.25 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 are separated into three folders: train, val, and test. The train/val split is 80/20 (n=880, n=220), randomly selected. The test set contains 35 images. Images are named in the format ".jpg".

Annotations

All images are annotated using Labelbox software. Masks were generated by point prompts using Meta's Segment Anything model (SAM). PVC quadrat, quadrat corners, and Kura clover objects were annotated with bounding boxes. 

Segmentation masks are in .mat format with the name "_mask.mat" with the following keys:

data: A 2d Numpy with data type np.uint8 corresponding to the class for each pixel.

project: A text field with the name of the project.

The segmentation mapping can be found in the file "segmentation_classes.json". The class mapping is as follows:

0: 'background' class containing all soil and non target materials.

1: 'quadrat' class.

2: 'clover' class for all clover related vegetation whether alive or dead.

Bounding boxes are in the file "bounding_boxes.csv". bbox coordinates are in the format (y1, x1, height, width). Column names are the following:

img_id: The name of the image file.

class: Class of the bbox annotation ∈ ['quadrat', 'quadrat_corner', 'kura_clover'].

y1: The y coordinate of the top of the bbox.

x1: The x coordinate of the left side of the bbox.

height: The height of the bbox (y2 = y1 + height).

width: The width of the bbox (x2 = x1 + width).

No image preprocessing was performed.