| | --- |
| | 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. |
| |
|
| | ## 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) |
| |
|