The dataset could not be loaded because the splits use different data file formats, which is not supported. Read more about the splits configuration. Click for more details.

Couldn't infer the same data file format for all splits. Got {NamedSplit('train'): ('text', {}), NamedSplit('validation'): ('text', {}), NamedSplit('test'): ('imagefolder', {})}

Error code:   FileFormatMismatchBetweenSplitsError

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

MSDD: Maize Seedling Dataset for Stand Counting

Overview

The MSDD (Maize Seedling Dataset) is designed for plant detection and stand counting tasks in agricultural environments.
It contains aerial imagery of maize genetic nurseries with annotations for early-stage seedling detection and classification.

The dataset is provided in YOLO format and supports training with modern object detection frameworks such as YOLOv9, YOLOv10, and YOLOv11/12.

Directory Structure

yolo_format/
├── training/
│   ├── images/
│   └── labels/
├── validation/
│   ├── images/
│   └── labels/
├── test/
│   ├── images/
│   └── labels/
├── yolov9_data.yaml
├── yolov11-v12_data.yaml
└── README.md

Description

training/images/ — training images
training/labels/ — YOLO annotations for training images
validation/images/ — validation images
validation/labels/ — YOLO annotations for validation images
test/images/ — test images
test/labels/ — YOLO annotations for test images
yolov9_data.yaml — configuration file for YOLOv9 training
yolov11-v12_data.yaml — configuration file for YOLOv11/YOLOv12 training

Annotation Format

Annotations follow the standard YOLO format.

Each label file contains one object per line:

<class_id> <x_center> <y_center> <width> <height>

Coordinates are normalized to the range [0, 1]
Each .txt file corresponds to one image with the same filename

Classes

Class ID	Description
0	single
1	double
2	triple

Dataset Usage

Example (YOLOv9)

yolo task=detect mode=train model=yolov9-c.pt data=yolov9_data.yaml

Example (YOLOv11 / YOLOv12)

yolo task=detect mode=train model=yolo11.pt data=yolov11-v12_data.yaml

YAML Configuration Files

yolov9_data.yaml

train: <path_to_dataset>/training/images
val: <path_to_dataset>/test/oblique/images
test: <path_to_dataset>//test/all/images

nc: 3
names: 
  0: Single
  1: Double
  2: Triple

yolov11-v12_data.yaml

path: <path_to_dataset>/

train: training/images
val: test/shadow/long/images
test: test/all/images

names: 
  0: Single
  1: Double
  2: Triple

Citation

This dataset is associated with a manuscript under review and is currently available as a preprint.

If you use this dataset, please cite:

Dewi Endah Kharismawati and Toni Kazic.
Maize Seedling Detection Dataset (MSDD): A Curated High-Resolution RGB Dataset for Seedling Maize Detection and Benchmarking with YOLOv9, YOLO11, YOLOv12 and Faster-RCNN.
arXiv preprint arXiv:2509.15181, 2025.
DOI: 10.48550/arXiv.2509.15181

BibTeX

@article{kharismawati2025msdd,
  title={Maize Seedling Detection Dataset (MSDD): A Curated High-Resolution RGB Dataset for Seedling Maize Detection and Benchmarking with YOLOv9, YOLO11, YOLOv12 and Faster-RCNN},
  author={Kharismawati, Dewi Endah and Kazic, Toni},
  journal={arXiv preprint arXiv:2509.15181},
  year={2025},
  doi={10.48550/arXiv.2509.15181}
}

License

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

https://creativecommons.org/licenses/by-nc-sa/4.0/

Contact

Dewi Endah Kharismawati, Ph.D kharismawati.2@osu.edu

Downloads last month: 19

Paper for dek8v5/MaizeSeedlingDetectionDataset_MSDD

Maize Seedling Detection Dataset (MSDD): A Curated High-Resolution RGB Dataset for Seedling Maize Detection and Benchmarking with YOLOv9, YOLO11, YOLOv12 and Faster-RCNN

Paper • 2509.15181 • Published Sep 18, 2025