metadata
license: cc-by-nc-3.0
task_categories:
- image-segmentation
tags:
- vision
- document-processing
- binarization
- ocr-preprocessing
size_categories:
- 10K<n<100K
Tzefa Binarization Dataset
Training dataset for the Tzefa document binarization model.
Structure
images/ # 40,085 input RGB document images (.jpg)
masks/ # 40,085 binary ground-truth masks (.png)
Each image has a corresponding mask where:
- Black (0) = ink / text
- White (255) = paper / background
Statistics
| Split | Images | Masks |
|---|---|---|
| Unified | 40,085 | 40,085 |
Images are collected from multiple batches (Batch 1-14) and unified into a single training set. Tiles are cropped at 640x640 during training with ImageNet normalization.
Usage
from datasets import load_dataset
dataset = load_dataset("WARAJA/Tzefa-Binarization-Dataset")
Or load images directly:
from PIL import Image
img = Image.open("images/BATCH_10_copy_000003.jpg")
mask = Image.open("masks/BATCH_10_copy_000003.png")