metadata
license: cc-by-nc-3.0
pipeline_tag: image-to-image
tags:
- vision
- document-processing
- binarization
- segmentation
Tzefa Binarization Model (mit_b5 HighResMAnet)
Custom-trained document binarization model for the Tzefa OCR pipeline.
Architecture
- Encoder: MiT-B5 (Mix Transformer)
- Decoder: MAnet with custom High-Resolution Stem + Fusion Head
- Framework: segmentation-models-pytorch
- Input: RGB image tiles (640x640)
- Output: Binary mask (ink=0, paper=255)
Usage
from huggingface_hub import hf_hub_download
import torch
# Download weights
ckpt_path = hf_hub_download("WARAJA/b5_model", "b5_model.pth")
# Load model (see Tzefa Binarization Space for full architecture code)
checkpoint = torch.load(ckpt_path, map_location="cpu")