CaptchaOCR-500K

Dataset Summary

CaptchaOCR-500K is a large-scale CAPTCHA recognition dataset containing 500,000 CAPTCHA images with corresponding text labels.

The dataset is designed for training and evaluating Optical Character Recognition (OCR), CAPTCHA solving systems, image-to-text models, and computer vision models focused on text recognition.

Tasks

• Optical Character Recognition (OCR)
• CAPTCHA Recognition
• Image-to-Text
• Computer Vision
• Text Recognition

Languages

English (alphanumeric CAPTCHA characters)

Dataset Structure

Splits

Split	Samples
Train	450,000
Validation	25,000
Test	25,000
Total	500,000

Features

Feature	Type	Description
image	Image	CAPTCHA image
text	string	Ground-truth CAPTCHA text

Example

{
    "image": <PIL.Image>,
    "text": "n89nf"
}

Dataset Creation

The dataset consists of synthetically generated CAPTCHA images with corresponding text labels. Images contain distorted alphanumeric characters, noise patterns, background lines, and transformations commonly used in CAPTCHA systems.

Characteristics

• Fixed image size: 200×80 pixels
• Alphanumeric text
• Distortion and rotation effects
• Noise and interference lines
• Suitable for OCR and sequence recognition tasks

Usage

Load with Hugging Face Datasets

from datasets import load_dataset

dataset = load_dataset("AvinashRicky/CaptchaOCR-500K")

Example

sample = dataset["train"][0]

image = sample["image"]
text = sample["text"]

print(text)

Applications

• OCR model training
• CAPTCHA recognition research
• Vision-language model pretraining
• Text recognition benchmarks
• Computer vision education and experimentation

License

MIT License

Citation

If you use this dataset in your research or projects, please cite:

@dataset{captchaocr500k,
  title={CaptchaOCR-500K},
  author={AvinashRicky},
  year={2026},
  publisher={Hugging Face}
}

Acknowledgements

Created and maintained by AvinashRicky for OCR and CAPTCHA recognition research.