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YOLO Object Detection Dataset
SPSCD + SMD buoy only
Dataset Information
- Number of Classes: 13
- Format: YOLO (ultralytics)
- Splits: train, validation, test
Classes
- Small Craft
- Small Fishing Boat
- Small Passenger Ship
- Fishing Trawler
- Large Passenger Ship
- Sailing Boat
- Speed Craft
- Motorboat
- Pleasure Yacht
- Medium Ferry
- Large Ferry
- High Speed Craft
- Buoy
Dataset Structure
dataset/
├── dataset.yaml # Dataset configuration
├── train/
│ ├── images/ # Training images
│ └── labels/ # Training labels (YOLO format)
├── validation/
│ ├── images/ # Validation images
│ └── labels/ # Validation labels
└── test/
├── images/ # Test images
└── labels/ # Test labels
YOLO Label Format
Each .txt file contains annotations in YOLO format:
<class_id> <x_center> <y_center> <width> <height>
All values are normalized to [0, 1] relative to image dimensions.
Usage
With Ultralytics
from ultralytics import RTDETR
# Train
model = RTDETR('rtdetr-l.pt')
model.train(data='dataset.yaml', epochs=100)
# Validate
model.val()
With Hugging Face Datasets
from datasets import load_dataset
# Load dataset
dataset = load_dataset('your-username/your-dataset')
# Access splits
train = dataset['train']
val = dataset['validation']
test = dataset['test']
Citation
If you use this dataset, please cite:
@dataset{your_dataset,
title={Your Dataset Name},
author={Your Name},
year={2025}
}
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