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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- en |
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size_categories: |
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- 1M<n<10M |
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--- |
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# Synthetic CAPTCHA OCR Dataset (1M) |
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## Overview |
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This dataset contains **synthetically generated CAPTCHA images** designed for training and benchmarking Optical Character Recognition (OCR) models. Each image contains a randomly generated alphanumeric string rendered in CAPTCHA style with noise, distortions, and visual artifacts to simulate real-world conditions. |
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The dataset is created entirely using automated rendering pipelines and therefore contains perfectly accurate ground-truth labels. |
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--- |
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## Dataset Characteristics |
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- **Dataset size:** 1,000,000 images |
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- **Image format:** PNG |
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- **Image resolution:** 160 × 60 pixels |
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- **Text length:** 5–10 characters |
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- **Character set:** |
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- Uppercase letters (A–Z) |
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- Lowercase letters (a–z) |
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- Digits (0–9) |
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Each file is named using the ground-truth label: |
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``` |
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<text>.png |
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``` |
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Example: |
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``` |
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A7kD3.png |
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pQ82Lm.png |
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``` |
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Thus, labels can be directly extracted from filenames without requiring an additional annotation file. |
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## Generation Methodology |
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Images were generated using a synthetic rendering pipeline that includes: |
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- Random font selection |
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- Character position perturbations |
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- Random background noise |
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- Random line interference |
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- Gaussian pixel noise |
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This process improves robustness and helps OCR models generalize to real-world CAPTCHA images. |
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## Intended Use |
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This dataset is suitable for: |
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- Training deep learning OCR systems |
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- CAPTCHA recognition research |
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- Sequence recognition benchmarking |
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- Synthetic data pretraining for document OCR systems |
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- Curriculum learning before fine-tuning on real-world datasets |
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## Limitations |
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- Images are synthetically generated and may not capture every real-world CAPTCHA style. |
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- Domain adaptation may still be required for specific CAPTCHA systems. |
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- Distribution of character sequences is random rather than language-based. |
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## Citation |
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If you use this dataset in academic work, please cite: |
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``` |
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Synthetic CAPTCHA OCR Dataset (1M), 2026 |
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``` |
