| --- |
| license: apache-2.0 |
| task_categories: |
| - other |
| language: |
| - en |
| tags: |
| - mouse-movement |
| - captcha |
| - biometrics |
| - human-behavior |
| - gaming |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # CaptchaSolve30k - Human Mouse Movement Dataset |
|
|
| **The largest open-source dataset of human task-specific mouse trajectories by session count and unique participants, with 30,000 discrete sessions from thousands of users. The first and only open dataset of complete human captcha-solving interactions with full behavioral replays.** |
|
|
| Each session captures mouse/touch trajectories, timing data, and puzzle state at physics-tick resolution. Suitable for bot detection research, human-computer interaction studies, and ML model training. |
|
|
| **IF YOU WANT TO USE THIS DATASET IN A PAPER, PLEASE LET ME KNOW at tc3416@columbia.edu! I AM AN UNDERGRAD STUDENT AND WOULD LOVE THE CITATION AND I WILL MAKE A DOI! :)** |
|
|
| ## Dataset Overview |
|
|
| | Metric | Value | |
| |--------|-------| |
| | Total Sessions | 30,000 | |
| | Game Types | 3 | |
| | Physics Sample Rate | 240 Hz | |
| | Raw Input Sample Rate | 1000 Hz | |
| | Average Session Duration | 8-15 seconds | |
|
|
| ### Privacy & Anonymization |
|
|
| Data was collected by Capycap, Inc. under a privacy policy disclosing collection practices, anonymization methods, and intended use for AI research. Users had the option to opt out of data storage. |
|
|
| - All coordinates are normalized to a 200×200 logical grid—raw screen coordinates were never stored |
| - Render size was randomized per session, removing device-specific signatures |
| - Sessions cannot be linked to individuals or correlated with each other |
| - No IP addresses, cookies, browser fingerprints, or persistent identifiers were collected |
|
|
| ### Terms of Use |
|
|
| By downloading this dataset, you agree to the following: |
|
|
| 1. **No re-identification**: Do not attempt to identify individuals, link sessions to specific users, or combine this data with other sources for identification purposes. |
|
|
| 2. **No biometric profiling**: Do not use this data to build biometric identification systems, behavioral authentication, surveillance tools, or any system designed to identify or track individuals based on interaction patterns. |
|
|
| 3. **Permitted uses**: This dataset is intended for AI research, bot detection, human-computer interaction studies, and training machine learning models (including generative models and automation agents). |
|
|
| 4. **Redistribution**: If you redistribute this data or derivatives, you must include these same restrictions. |
|
|
| Violation of these terms may constitute a breach of contract and could result in legal liability. |
|
|
| ## Game Types |
|
|
| ### Sheep Herding |
| Guide sheep into a pen by drawing paths with your mouse. Tests continuous cursor control and path planning. |
|
|
| ### Thread the Needle |
| Navigate through gaps without touching walls. Tests precision movement and spatial awareness. |
|
|
| ### Polygon Stacking |
| Drag and stack polygon shapes on a platform. Tests click-drag interactions and placement accuracy. |
|
|
| ## Data Format |
|
|
| Each session is a JSON object with the following fields: |
|
|
| | Field | Type | Description | |
| |-------|------|-------------| |
| | `index` | int | Session index in the dataset | |
| | `gameType` | string | One of: `sheep-herding`, `thread-the-needle`, `polygon-stacking` | |
| | `puzzleSeed` | int | Seed used to generate the puzzle (for reproducibility) | |
| | `duration` | int | Session duration in milliseconds | |
| | `physicsTickCount` | int | Number of physics ticks (at 240 Hz) | |
| | `tickInputs` | array | Input state at each physics tick | |
| | `inputStream` | string | Base64-encoded raw 1000 Hz mouse samples | |
| | `inputSampleCount` | int | Number of raw input samples | |
| | `touchscreen` | bool | Whether input was from a touchscreen | |
|
|
| ### tickInputs Format |
|
|
| Array of objects representing input state at each 240 Hz physics tick: |
|
|
| ```json |
| { |
| "x": 150.5, // X position in grid coordinates (0-200) |
| "y": 100.2, // Y position in grid coordinates (0-200) |
| "isDown": true, // Mouse button / touch pressed |
| "sampleIndex": 42 // Index into inputStream for this tick |
| } |
| ``` |
|
|
| ### inputStream Format |
|
|
| Base64-encoded binary stream of raw 1000 Hz mouse samples. Each sample is 9 bytes: |
| - 4 bytes: X position (float32, little-endian) |
| - 4 bytes: Y position (float32, little-endian) |
| - 1 byte: Button state (0 = up, 1 = down) |
|
|
| ## Usage |
|
|
| ### Loading with Datasets Library |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("Capycap-AI/CaptchaSolve30k") |
| |
| # Access a sample |
| sample = dataset['train'][0] |
| print(f"Game: {sample['gameType']}, Duration: {sample['duration']}ms") |
| ``` |
|
|
| ### Decoding inputStream |
|
|
| ```python |
| import base64 |
| import struct |
| |
| def decode_input_stream(b64_stream, sample_count): |
| data = base64.b64decode(b64_stream) |
| samples = [] |
| for i in range(sample_count): |
| offset = i * 9 |
| x, y = struct.unpack('<ff', data[offset:offset+8]) |
| is_down = data[offset+8] == 1 |
| samples.append({'x': x, 'y': y, 'isDown': is_down}) |
| return samples |
| ``` |
|
|
| ## Demo & Replay |
|
|
| Explore the dataset interactively with our demo space: |
|
|
| - **Visualize sessions**: Watch recorded mouse movements replay in real-time over the actual game |
| - **Inspect trajectories**: See exactly how humans navigate each puzzle type |
| - **Load samples**: Paste JSON from the dataset or load random samples directly |
| - **Play the games**: Try the puzzles yourself and export your own session data in the same format |
|
|
| [Open Demo Space](https://huggingface.co/spaces/Capycap-AI/CaptchaSolve-Demo) |
|
|
| ## License |
|
|
| Apache License 2.0 - free for research and commercial use. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @dataset{captchasolve30k, |
| title={CaptchaSolve30k: Human Mouse Movement Dataset}, |
| author={Capycap Inc.}, |
| year={2026}, |
| url={https://huggingface.co/datasets/Capycap-AI/CaptchaSolve30k} |
| } |
| ``` |
|
|
| ## Authors |
|
|
| This dataset was created by: |
|
|
| - **Tony Chen** - [GitHub](https://github.com/TonyChen06) | [LinkedIn](https://www.linkedin.com/in/tonychen06/) |
| - **James Gu** - [GitHub](https://github.com/jamesgu888) | [LinkedIn](https://www.linkedin.com/in/jamesgu888/) |
| - **Christopher He** - [LinkedIn](https://www.linkedin.com/in/chrismhe/) |
| - **Kevin Zhou** - [GitHub](https://github.com/zhoism) | [LinkedIn](https://www.linkedin.com/in/kevinzhou3/) |
|
|
| Published by Capycap Inc. |
|
|
| ## Links |
|
|
| - [Demo Space](https://huggingface.co/spaces/Capycap-AI/CaptchaSolve-Demo) |
|
|
