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---
tags:
- ocr
- text-extraction
- rolmocr
- uv-script
- generated
---
# OCR Text Extraction using RolmOCR
This dataset contains extracted text from images in [davanstrien/playbills-pdf-images-text](https://huggingface.co/datasets/davanstrien/playbills-pdf-images-text) using RolmOCR.
## Processing Details
- **Source Dataset**: [davanstrien/playbills-pdf-images-text](https://huggingface.co/datasets/davanstrien/playbills-pdf-images-text)
- **Model**: [reducto/RolmOCR](https://huggingface.co/reducto/RolmOCR)
- **Number of Samples**: 10
- **Processing Time**: 5.8 minutes
- **Processing Date**: 2025-08-04 17:08 UTC
### Configuration
- **Image Column**: `image`
- **Output Column**: `rolmocr_text`
- **Dataset Split**: `train`
- **Batch Size**: 16
- **Max Model Length**: 24,000 tokens
- **Max Output Tokens**: 16,000
- **GPU Memory Utilization**: 80.0%
## Model Information
RolmOCR is a fast, general-purpose OCR model based on Qwen2.5-VL-7B architecture. It extracts plain text from document images with high accuracy and efficiency.
## Dataset Structure
The dataset contains all original columns plus:
- `rolmocr_text`: The extracted text from each image
- `inference_info`: JSON list tracking all OCR models applied to this dataset
## Usage
```python
from datasets import load_dataset
import json
# Load the dataset
dataset = load_dataset("{output_dataset_id}", split="train")
# Access the extracted text
for example in dataset:
print(example["rolmocr_text"])
break
# View all OCR models applied to this dataset
inference_info = json.loads(dataset[0]["inference_info"])
for info in inference_info:
print(f"Column: {info['column_name']} - Model: {info['model_id']}")
```
## Reproduction
This dataset was generated using the [uv-scripts/ocr](https://huggingface.co/datasets/uv-scripts/ocr) RolmOCR script:
```bash
uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/rolm-ocr.py \
davanstrien/playbills-pdf-images-text \
<output-dataset> \
--image-column image \
--batch-size 16 \
--max-model-len 24000 \
--max-tokens 16000 \
--gpu-memory-utilization 0.8
```
## Performance
- **Processing Speed**: ~0.0 images/second
- **GPU Configuration**: vLLM with 80% GPU memory utilization
Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts)
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