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docs: update model card

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+ ---
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+ license: mit
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+ tags:
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+ - ocr
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+ - receipt
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+ - object-detection
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+ - yolov8
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+ - tensorflow
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+ - keras
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+ - text-recognition
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+ - expense-classification
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+ language:
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+ - id
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+ ---
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+
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+ # NotePay — Receipt OCR Models
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+
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+ Model AI untuk pipeline OCR struk belanja otomatis.
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+ Bagian dari project **NotePay** (Coding Camp 2026 — DBS Foundation).
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+
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+ ## Pipeline
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+
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+ ```
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+ Foto Struk
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+ → [1] YOLOv8n-OBB : deteksi 4 region (nama_toko, line_item, tanggal_waktu, total_belanja)
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+ → [2] CRNN + CTC : text recognition per crop (TensorFlow/Keras)
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+ → [3] Classifier : klasifikasi kategori pengeluaran tiap line item
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+ → JSON terstruktur
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+ ```
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+
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+ ## Model Files
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+
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+ | File | Deskripsi |
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+ |---|---|
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+ | `yolo/best.pt` | YOLOv8n-OBB — deteksi region struk |
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+ | `crnn/inference_model.keras` | CRNN+CTC — baca teks dari crop |
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+ | `classifier/classifier_model.keras` | Text classifier — kategori pengeluaran |
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+
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+ ## Expense Categories (Classifier)
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+
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+ | ID | Kategori |
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+ |---|---|
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+ | 0 | Makanan & Minuman |
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+ | 1 | Kebersihan & Perawatan |
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+ | 2 | Rumah Tangga |
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+ | 3 | Kesehatan & Farmasi |
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+ | 4 | Elektronik & Pulsa |
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+ | 5 | Pakaian & Aksesori |
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+ | 6 | Lain-lain |
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+
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+ ## Usage
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+
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+ ```python
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+ from huggingface_hub import hf_hub_download
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+
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+ # Download semua model
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+ yolo_path = hf_hub_download("NeoCode77/notepay-models", "yolo/best.pt")
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+ crnn_path = hf_hub_download("NeoCode77/notepay-models", "crnn/inference_model.keras")
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+ classifier_path = hf_hub_download("NeoCode77/notepay-models", "classifier/classifier_model.keras")
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+
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+ # Load
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+ from ultralytics import YOLO
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+ import keras
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+
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+ yolo = YOLO(yolo_path)
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+ crnn = keras.models.load_model(crnn_path, compile=False, safe_mode=False)
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+ classifier = keras.models.load_model(classifier_path, compile=False)
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+ ```
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+
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+ Atau gunakan `ai/model_loader.py` dari repo ini yang sudah handle caching & GPU setup.