YOLOv8-Historical-Document-Detection

🏛️ YOLOv8 — Historical Document Ornament Detector

Automatic detection of typographic ornaments in 16th–18th century printed documents. Developed as part of the TypoRef project at PolyTech Tours.

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📌 Model Summary

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🧠 What This Model Does

This model detects and localizes typographic ornaments and decorative graphic elements in scanned pages of early modern European printed books.

It was built to replace a slow, fully manual cataloguing process for the TypoRef digital humanities project, enabling automated analysis of thousands of document pages that would otherwise require extensive expert annotation.

Detected classes: typographic ornaments, decorative initials, vignettes, and other graphic elements typical of 16th–18th century printing.

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📈 Performance

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🚀 How to Use

from ultralytics import YOLO

# Load the model
model = YOLO("best.pt")

# Run inference on a document scan
results = model("your_document_scan.jpg", conf=0.35)

# Show results
results[0].show()

# Save annotated image
results[0].save("output.jpg")

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🗂️ Training Data

• Source: Historical printed books from the TypoRef corpus (16th–18th century)
• Annotations: Expert-annotated by digital humanities researchers at PolyTech Tours
• Volume: 50+ annotated document pages
• Augmentation: Standard YOLOv8 augmentation pipeline

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⚠️ Limitations

• Optimized for black-and-white or greyscale document scans
• Performance may degrade on very low-resolution scans (< 150 DPI)
• Trained on Western European printing conventions — may generalize poorly to other traditions

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🔗 Related Resources

• 🤗 Live Demo Space
• 💻 GitHub Repository

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👤 Author

Martin Badrous — Computer Vision & Deep Learning Engineer