---
license: apache-2.0
task_categories:
- image-to-text
language:
- en
tags:
- document
- image
- open-pdf
- 250+
size_categories:
- n<1K
---
# Openpdf-Blank-v2.0-Sample

**Openpdf-Blank-v2.0-Sample** is a sample dataset of blank or near-blank invoice and receipt documents. It contains 255 high-resolution scanned images extracted and cleaned from document PDFs. This dataset is intended to support training and evaluation of OCR, document classification, and layout-based filtering models where blank or structurally minimal pages must be identified and processed.

## Dataset Summary

* **Format**: Parquet (auto-converted)
* **Modality**: Image
* **Size**: 84.8 MB
* **Number of Samples**: 255
* **Split**:

  * `train`: 255 images
* **Image Dimensions**: Approximately 1690 x 1690 px
* **License**: Apache 2.0

## Features

* Contains scanned images of documents with minimal content or structural layout only.
* Suitable for:

  * Blank page detection
  * Document filtering
  * Pre-processing pipeline validation
  * Background noise training for OCR tasks

## How to Use

You can load the dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Openpdf-Blank-v2.0-Sample")

# Access the first image
image = dataset["train"][0]["image"]
image.show()
```

Each record in the dataset contains:

* `image`: A PIL.Image object of the scanned blank/near-blank page.

## Use Cases

* Training models to detect and discard blank or non-informative pages in document workflows.
* Evaluating the robustness of OCR pipelines to blank document noise.
* Dataset balancing for invoice or receipt classifiers.