README.md

---
license: cc-by-4.0
task_categories:
- visual-question-answering
- image-to-text
tags:
- optical-character-recognition
- visual-question-answering
- robustness
- watermark
- numerical
- multimodal
pretty_name: FADE
size_categories:
- 1K<n<10K
---

# FADE Watermark OCR Dataset

## Overview
This dataset contains watermarked images, their corresponding masks, the alpha values used for watermarking, and the actual text embedded (as a 9-digit number). It is designed to train and evaluate OCR models in the presence of watermarks.

**Paper:** [FADE: Probing the Limits of VLMs on fine-grained OCR](https://openreview.net/forum?id=JOZS2gZOYU)

### Data Fields

| Column Name            | Data Type | Description |
| :---                   | :---      | :--- |
| `Image with watermark` | `binary`  | The raw binary bytes of the watermarked image (JPEG). When loaded with Hugging Face `datasets`, this can be cast to a PIL Image. |
| `Masked image`         | `binary`  | The raw binary bytes of the corresponding mask image. |
| `alpha value`          | `float`   | The blending factor used to apply the watermark (e.g., 0.05, 0.1, 0.5, 1.0). |
| `Actual answer`        | `string`  | The ground truth 9-digit watermark text embedded in the image. |

## Usage
```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("deep9539/FADE-watermark-ocr")

# View the structure
print(dataset)
```