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Datasets:
Titlehhhh
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captchaocr-dataset

Tasks:
Image-to-Text
Modalities:
Image
Tabular
Text
Formats:
parquet
Languages:
English
Russian
Size:
100K - 1M
Tags:
captcha
ocr
minecraft
anti-bot
Synthetic
parquet
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---
license: other
license_name: mixed-per-plugin-licences
license_link: https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/blob/main/LICENSE
pretty_name: CaptchaOCR — Minecraft anti-bot captchas
task_categories: [image-to-text]
language: [en, ru]
tags: [captcha, ocr, minecraft, anti-bot, synthetic, parquet, image]
size_categories: 100K<n<1M
configs:
- config_name: default
data_files: data/*.parquet
---
<img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/hero.png" alt="Six captcha styles from Minecraft anti-bot plugins: map codes, a chat code, Cyrillic symbols and a web captcha" width="100%">
# CaptchaOCR — Minecraft anti-bot captchas as training data
Minecraft anti-bot captchas, re-rendered by this project's Java 21 generators and packed one image per Parquet row: image, answer, drawn text and answer band.
![samples](https://img.shields.io/badge/samples-200%2C000-blue)
![types](https://img.shields.io/badge/captcha_types-20-blueviolet)
![plugins](https://img.shields.io/badge/upstream_plugins-13-informational)
![size](https://img.shields.io/badge/size-1.9_GiB-lightgrey)
![format](https://img.shields.io/badge/format-Parquet-150458)
![task](https://img.shields.io/badge/task-image--to--text-success)
![license](https://img.shields.io/badge/license-mixed_per_plugin-orange)
## What's inside
- **20 captcha types** from **13 upstream names** — 6 pixel-faithful ports, 10 clean-room reimplementations, 4 reconstructions with no upstream plugin.
- **200,000 images**, 10,000 per type, one Parquet row each, with every label field from `labels.jsonl` in the same row.
- **9 Parquet shards, 1.9 GiB** — 30–248 MiB each, no loading script, no remote code.
- **`roi` in 12 of 20 types** — 119,984 answer bands; the other 80,016 rows need the whole frame.
## Gallery
Six examples of these types, answer under each image.
| <img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/gallery/01.png" width="170" alt="Krypton map captcha with a five-letter code"><br><sub>`Krypton/map` — `Wu43b`</sub> | <img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/gallery/02.png" width="170" alt="mapcha map captcha with a four-letter code"><br><sub>`mapcha/map` — `ly8r`</sub> | <img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/gallery/03.png" width="170" alt="XProtect chat code captcha"><br><sub>`XProtect/code` — `5dqnZ9`</sub> |
|---|---|---|
| <img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/gallery/04.png" width="170" alt="LimboFilter Cyrillic symbol captcha"><br><sub>`LimboFilter/symbols` — `БЬ5`</sub> | <img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/gallery/05.png" width="170" alt="Reconstructed web captcha, 150 by 90 pixels"><br><sub>`GalleryCaptcha/ru-web` — `cVejm`</sub> | <img src="https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/resolve/main/assets/gallery/06.png" width="170" alt="CaptchaVerifyZ map captcha in capital letters"><br><sub>`CaptchaVerifyZ/map` — `AYKZB`</sub> |
## Quickstart
```python
import io
from datasets import load_dataset
from PIL import Image
ds = load_dataset("Titlehhhh/captchaocr-dataset", split="train")
row = ds[0]
image = Image.open(io.BytesIO(row["image"])); print(row["answer"], row["roi"])
```
<details>
<summary>Filter one type, or read a shard with pyarrow</summary>
```python
ds = load_dataset("Titlehhhh/captchaocr-dataset", split="train")
subset = ds.filter(lambda row: row["type_id"] == "out/haq/mapcha/map")
import pyarrow.parquet as pq
table = pq.read_table("data/train-00000-of-00009.parquet",
columns=["type_id", "answer"])
```
`train-00000-of-00009.parquet` is the first of 9 shards; the row order is
deterministic (tree, type, `labels.jsonl` order).
</details>
## Fields
| column | type | meaning |
|---|---|---|
| `image` | `binary` | raw PNG bytes; decode with `PIL.Image.open(io.BytesIO(...))` |
| `file` | `string` | file name inside the type directory (`001.png` …) |
| `type_id` | `string` | type path, e.g. `out/Archy-X/Krypton/map` |
| `plugin` | `string` | upstream plugin, e.g. `haq/mapcha` |
| `captcha` | `string` | captcha style inside the plugin, e.g. `map` |
| `answer` | `string` | what the player types into the answer field |
| `text` | `string`, nullable | what is drawn on the image |
| `prompt` | `string`, nullable | task text the plugin shows |
| `roi` | `list<int32>`, nullable | answer band `[x, y, w, h]` |
| `width` | `int32` | PNG width in pixels |
| `height` | `int32` | PNG height in pixels |
| `source` | `string` | upstream class and method that produced the style |
| `tree` | `string` | `out` (Latin) or `out_ru` (Cyrillic) |
`text` is what is drawn; `answer` is what the player types. They differ in 3 types, where a solver step converts one to the other — train a recogniser on `text`, evaluate a solver on `answer`. `roi` is the answer band; when the band does not fit the frame, `roi` is `null`, so pass the whole image and never crop those rows.
## Types
20 types from 13 upstream names. `roi` rows count rows with the band present; `text ≠ answer` counts rows where the drawn string differs from the typed answer.
<details>
<summary>All 20 types</summary>
| type_id | plugin | captcha | samples | roi rows | text ≠ answer | mode | license |
|---|---|---|---:|---:|---:|---|---|
| `out/Archy-X/Krypton/map` | `Archy-X/Krypton` | `map` | 10,000 | 10,000 | 0 | clean-room | No licence — all rights reserved |
| `out/InstantlyMoist/Captcha/textcaptcha` | `InstantlyMoist/Captcha` | `textcaptcha` | 10,000 | 0 | 0 | faithful | MIT |
| `out/JSH32/Minecaptcha/map` | `JSH32/Minecaptcha` | `map` | 10,000 | 10,000 | 0 | faithful | MIT |
| `out/LagBug/XProtect/code` | `LagBug/XProtect` | `code` | 10,000 | 0 | 0 | faithful | MIT |
| `out/LagBug/XProtect/map` | `LagBug/XProtect` | `map` | 10,000 | 0 | 0 | faithful | MIT |
| `out/haq/mapcha/map` | `haq/mapcha` | `map` | 10,000 | 9,984 | 0 | faithful | MIT |
| `out/irootdev/AnBot/captcha` | `irootdev/AnBot` | `captcha` | 10,000 | 0 | 0 | clean-room | GPL-3.0 |
| `out/jonesdevelopment/sonar/complex` | `jonesdevelopment/sonar` | `complex` | 10,000 | 0 | 0 | clean-room | GPL-3.0 |
| `out/jonesdevelopment/sonar/legacy` | `jonesdevelopment/sonar` | `legacy` | 10,000 | 0 | 0 | clean-room | GPL-3.0 |
| `out/jonesdevelopment/sonar/standard` | `jonesdevelopment/sonar` | `standard` | 10,000 | 0 | 0 | clean-room | GPL-3.0 |
| `out/just-captcha/ProstoCaptcha/map` | `just-captcha/ProstoCaptcha` | `map` | 10,000 | 10,000 | 0 | faithful | MIT |
| `out/ringoame196-s-mcPlugin/ReproductionCAPTCHA/map` | `ringoame196-s-mcPlugin/ReproductionCAPTCHA` | `map` | 10,000 | 10,000 | 0 | clean-room | No licence file — all rights reserved |
| `out_ru/BotFilter/map` | `BotFilter` | `map` | 10,000 | 0 | 0 | clean-room | BSD-2-Clause, no commercial hosting |
| `out_ru/CaptchaVerifyZ/map` | `CaptchaVerifyZ` | `map` | 10,000 | 10,000 | 0 | clean-room | All rights reserved (Modrinth) |
| `out_ru/GalleryCaptcha/ru-numberword` | `GalleryCaptcha` | `ru-numberword` | 10,000 | 10,000 | 10,000 | reconstructed | Not established (see `source`) |
| `out_ru/GalleryCaptcha/ru-numberword-caption` | `GalleryCaptcha` | `ru-numberword-caption` | 10,000 | 10,000 | 10,000 | reconstructed | Not established (see `source`) |
| `out_ru/GalleryCaptcha/ru-symbols` | `GalleryCaptcha` | `ru-symbols` | 10,000 | 10,000 | 0 | reconstructed | Not established (see `source`) |
| `out_ru/GalleryCaptcha/ru-web` | `GalleryCaptcha` | `ru-web` | 10,000 | 10,000 | 0 | reconstructed | Not established (see `source`) |
| `out_ru/LimboFilter/map` | `LimboFilter` | `map` | 10,000 | 10,000 | 10,000 | clean-room | AGPL-3.0 |
| `out_ru/LimboFilter/symbols` | `LimboFilter` | `symbols` | 10,000 | 10,000 | 0 | clean-room | AGPL-3.0 |
This snapshot holds 20 of the 21 types in the generator tree. `out_ru/LimboFilter/digits` was rendered after the snapshot and is not published here.
</details>
## License
Each row carries the license of the upstream plugin it came from, so the dataset as a whole is mixed (`license_name: mixed-per-plugin-licences`). Several upstream licenses forbid commercial hosting or reserve all rights, so check the table before you ship anything. Full text: [LICENSE](https://huggingface.co/datasets/Titlehhhh/captchaocr-dataset/blob/main/LICENSE).
<details>
<summary>Licenses by upstream plugin</summary>
| plugin | types | samples | license | mode |
|---|---|---:|---|---|
| `Archy-X/Krypton` | 1 | 10,000 | No licence — all rights reserved | clean-room |
| `BotFilter` | 1 | 10,000 | BSD-2-Clause, no commercial hosting | clean-room |
| `CaptchaVerifyZ` | 1 | 10,000 | All rights reserved (Modrinth) | clean-room |
| `GalleryCaptcha` | 4 | 40,000 | Not established (see `source`) | reconstructed |
| `InstantlyMoist/Captcha` | 1 | 10,000 | MIT | faithful |
| `JSH32/Minecaptcha` | 1 | 10,000 | MIT | faithful |
| `LagBug/XProtect` | 2 | 20,000 | MIT | faithful |
| `LimboFilter` | 2 | 20,000 | AGPL-3.0 | clean-room |
| `haq/mapcha` | 1 | 10,000 | MIT | faithful |
| `irootdev/AnBot` | 1 | 10,000 | GPL-3.0 | clean-room |
| `jonesdevelopment/sonar` | 3 | 30,000 | GPL-3.0 | clean-room |
| `just-captcha/ProstoCaptcha` | 1 | 10,000 | MIT | faithful |
| `ringoame196-s-mcPlugin/ReproductionCAPTCHA` | 1 | 10,000 | No licence file — all rights reserved | clean-room |
`mode` says how close the pixels are to the upstream plugin: **faithful** is a port of the upstream drawing code, **clean-room** is a reimplementation from the algorithm, **reconstructed** means no upstream plugin was available.
</details>
## Provenance
- Every image is a re-render by the Java 21 generators in this repository, not a screenshot and not a copy.
- 6 types are pixel-faithful ports, 10 are clean-room reimplementations, 4 are reconstructed from reference screenshots.
- The generators are not seeded: this is one random render (2026-10-24). The labels and the generator code are the reproducible part.
- The upstream reference screenshots that guided the reconstructions are not published; they are other people's images.
- No image, page or answer from a third-party commercial service is included.
## Limitations
- Synthetic images: fonts, noise and layout follow the plugin algorithms, not a live server, so expect a gap on real screenshots.
- 8 types have no `roi`; there the answer band is not in the frame, so feed the whole image.
- 3 types put a solver step between the drawn string and the answer; OCR alone does not solve them.
- Other anti-bot plugins are not represented: the snapshot stops at the types listed above.