Create README.md

README.md

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+AraMS-Restore restores degraded lines from historical Arabic manuscripts. A U-Net takes a damaged handwritten line and returns a readable one, trained on synthetic damage (tears, ink blots, erasure, bleed-through, worm holes) calibrated against real manuscript decay.
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+The contribution is the ablation between two objectives on the same generator: Level 1 optimizes visual fidelity (L1 + perceptual + optional PatchGAN), while Level 2 adds a frozen HATFormer OCR critic that reads the restored image and scores it against the true transcription — so gradients flow into the pixels that matter for reading. Both are evaluated on held-out manuscripts by CER before vs. after restoration, including on real damaged scans rather than only synthetic damage.
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+Trained on AraMS-28k-HTR (28,595 lines, 14 manuscripts, book-level disjoint splits). Includes the damage engine, evaluation scripts, and a drag-and-drop before/after web demo