Athar Segmentation v4
Athar Segmentation v4 is the Kraken/BLLA line-segmentation model deployed
with the Athar Arabic manuscript transcription system. It detects line regions
and baselines before the separate exp9 recognition model transcribes each crop.
ملخص عربي
هذا نموذج القص واكتشاف أسطر المخطوطات العربية المستعمل في منظومة «أثر».
النموذج لا يقرأ النص؛ بل يحدد مناطق الأسطر وخطوط الأساس، ثم يمرر القصاصات إلى
نموذج التفريغ المستقل. دُرّب على 319 صفحة PAGE-XML من RASAM، وبلغ متوسط
IoU=0.452 في سجل التدريب المحلي.
Evidence
| Measurement | Result |
|---|---|
| Training pages | 319 RASAM pages |
| Recorded mean IoU | 0.452 |
| 30-page full-pipeline CER with the older segmenter | 10.06% |
| 30-page full-pipeline CER with v4 | 8.43% |
The CER comparison measures the complete page pipeline, not segmentation alone. It shows the downstream impact of better crops, while IoU is the direct geometric segmentation metric. Dense or framed layouts can still require human PAGE-XML polygons.
Model file
| Field | Value |
|---|---|
| File | model.mlmodel |
| Framework | Kraken / BLLA |
| SHA-256 | dc07cdeefe17598535ea3f5b187f7ddd2463baed909138c9ffd274c88b0e9a24 |
| Intended input | Full Arabic manuscript page image |
| Intended output | Line polygons and baselines |
Usage
Install a Kraken version compatible with the model and provide the model to Kraken's segmentation command. The Athar application loads it through:
SEG_MODEL_FILE=model.mlmodel
For scholarly work, inspect and correct the resulting line polygons before accepting a final transcription. Layout segmentation and recognition are separate sources of error.
Training data and license note
The recorded training source is RASAM, whose local dataset repository carries
an Apache-2.0 license. This repository is initially kept private while the
upstream warm-start model provenance and release terms are reviewed. The
license: other metadata is deliberate; do not infer a permissive weight
license until that review is complete.
Limitations
- Framed, multi-column, marginal, and heavily overlapping layouts may fail.
- The model is specialized for historical Arabic manuscript pages.
- IoU does not measure reading order or transcription accuracy.
- Human correction of PAGE-XML remains the safest path for complex pages.
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