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license: apache-2.0
tags:
- object-detection
- yolo
- ultralytics
- manuscript
- jawi
- arabic-script
- text-line-segmentation
- document-ai
pipeline_tag: object-detection
---
# Jawi Manuscript YOLO Text Line Detector
This model is a specialized **YOLO-based Text Line Detector** fine-tuned for high-precision bounding box extraction from historical and verified **Jawi (Arabic script)** manuscripts and document folios.
## Model Highlights
- **Architecture**: Ultralytics YOLO trained with document layout inductive biases.
- **Task**: Single-class dense text line detection and bounding box localization (`line`).
- **Target Script**: Jawi (Malay written in Arabic script).
- **Post-Processing Support**: Compatible with Right-to-Left (RTL) baseline reading order sorting and Horizontal Projection Profile (HPP) line splitting.
## Usage with Ultralytics
```python
from ultralytics import YOLO
from huggingface_hub import hf_hub_download
# Download best weights from Hugging Face Hub
weights_path = hf_hub_download(
repo_id="Shadowzer0/Jawi_YOLO_Line_Detector",
filename="best.pt"
)
# Load model and run inference
model = YOLO(weights_path)
results = model.predict("path/to/manuscript_page.jpg", conf=0.25, iou=0.45)
for box in results[0].boxes.xyxy:
x1, y1, x2, y2 = box.tolist()
print(f"Detected line: ({x1}, {y1}) -> ({x2}, {y2})")
```
## Integration with Karya Agung Pipeline
This model serves as the primary line segmenter for the **Karya Agung Jawi OCR & Transliteration Studio**.
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