Object Detection
Keras
Indonesian
ocr
receipt
yolov8
tensorflow
text-recognition
expense-classification
Instructions to use NeoCode77/notepay-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use NeoCode77/notepay-models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://NeoCode77/notepay-models") - Notebooks
- Google Colab
- Kaggle
NotePay β Receipt OCR Models
Model AI untuk pipeline OCR struk belanja otomatis. Bagian dari project NotePay (Coding Camp 2026 β DBS Foundation).
Pipeline
Foto Struk
β [1] YOLOv8n-OBB : deteksi 4 region (nama_toko, line_item, tanggal_waktu, total_belanja)
β [2] CRNN + CTC : text recognition per crop (TensorFlow/Keras)
β [3] Classifier : klasifikasi kategori pengeluaran tiap line item
β JSON terstruktur
Model Files
| File | Deskripsi |
|---|---|
yolo/best.pt |
YOLOv8n-OBB β deteksi region struk |
crnn/inference_model.keras |
CRNN+CTC β baca teks dari crop |
classifier/classifier_model.keras |
Text classifier β kategori pengeluaran |
Expense Categories (Classifier)
| ID | Kategori |
|---|---|
| 0 | Makanan & Minuman |
| 1 | Kebersihan & Perawatan |
| 2 | Rumah Tangga |
| 3 | Kesehatan & Farmasi |
| 4 | Elektronik & Pulsa |
| 5 | Pakaian & Aksesori |
| 6 | Lain-lain |
Usage
from huggingface_hub import hf_hub_download
# Download semua model
yolo_path = hf_hub_download("NeoCode77/notepay-models", "yolo/best.pt")
crnn_path = hf_hub_download("NeoCode77/notepay-models", "crnn/inference_model.keras")
classifier_path = hf_hub_download("NeoCode77/notepay-models", "classifier/classifier_model.keras")
# Load
from ultralytics import YOLO
import keras
yolo = YOLO(yolo_path)
crnn = keras.models.load_model(crnn_path, compile=False, safe_mode=False)
classifier = keras.models.load_model(classifier_path, compile=False)
Atau gunakan ai/model_loader.py dari repo ini yang sudah handle caching & GPU setup.
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