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Wall Damage

This dataset is part of the Roboflow 100 benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains.

Dataset Statistics

Split Images
Train 325
Validation 96
Test 40
Total 461

Classes (3)

  • Minorrotation
  • Moderaterotation
  • Severerotation

Usage

With LibreYOLO

from libreyolo import LIBREYOLO

# Load a model
model = LIBREYOLO(model_path="libreyoloXnano.pt")

# Train on this dataset
model.train(data='path/to/data.yaml', epochs=100)

Download from HuggingFace

from huggingface_hub import snapshot_download

# Download the dataset
snapshot_download(
    repo_id="Libre-YOLO/wall-damage",
    repo_type="dataset",
    local_dir="./wall-damage"
)

Directory Structure

wall-damage/
β”œβ”€β”€ data.yaml           # Dataset configuration
β”œβ”€β”€ README.md           # This file
β”œβ”€β”€ train/
β”‚   β”œβ”€β”€ images/         # Training images
β”‚   └── labels/         # Training labels (YOLO format)
β”œβ”€β”€ valid/
β”‚   β”œβ”€β”€ images/         # Validation images
β”‚   └── labels/         # Validation labels
└── test/
    β”œβ”€β”€ images/         # Test images (if available)
    └── labels/         # Test labels

Label Format

Labels are in YOLO format (one .txt file per image):

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

All coordinates are normalized to [0, 1].

Citation

If you use this dataset, please cite the Roboflow 100 benchmark:

@misc{rf100_2022,
    Author = {Floriana Ciaglia and Francesco Saverio Zuppichini and Paul Guerrie and Mark McQuade and Jacob Solawetz},
    Title = {Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark},
    Year = {2022},
    Eprint = {arXiv:2211.13523},
}

License

This dataset is released under the CC-BY-4.0 license. Please check the original source for any additional terms.

Acknowledgments

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Paper for Libre-YOLO/wall-damage