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Datasets:
RekaAI
/
CS2-10k

Tasks:
Other
Modalities:
Video
Size:
100K<n<1M
Tags:
counter-strike
cs2
gaming
egocentric
first-person
video
Libraries:
WebDataset
License:
Dataset card Data Studio Files
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CS2-10k full WebDataset release (660,535 clips, 30,723 shards)

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+ # Video files - compressed
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+ ---
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+ license: cc-by-nc-4.0
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+ pretty_name: CS2-10k
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+ task_categories:
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+ - other
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+ tags:
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+ - counter-strike
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+ - cs2
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+ - gaming
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+ - egocentric
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+ - first-person
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+ - video
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+ - world-models
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+ - imitation-learning
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+ - action-prediction
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+ - webdataset
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+ size_categories:
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+ - 100K<n<1M
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/*/*.tar
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+ ---
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+
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+ # CS2-10k: A Large-Scale Egocentric Counter-Strike 2 Dataset
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+
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+ <p align="center">
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+ <a href="https://huggingface.co/spaces/RekaAI/CS2-10k-viewer"><img src="https://huggingface.co/datasets/RekaAI/CS2-10k/resolve/main/viewer-banner.png" alt="Dataset Interactive Viewer"></a>
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+ </p>
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+
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+ ![CS2-10k preview](preview.avif)
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+
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+ **CS2-10k** is a large-scale egocentric gameplay dataset built from professional CS2 matches. It contains **600,000+ player-round videos** spanning **10,000+ hours** of **first-person footage**, paired with **per-frame annotations** covering **keyboard state, mouse movement, and 3D player trajectory**.
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+
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+ CS2-10k is built from public professional match demos sourced from [HLTV](https://www.hltv.org/). For each demo, we render first-person video at **720p, 48 fps** using the demo replay tool inside CS2, producing one video per player per round. Alongside each video, we store a `.parquet` file containing per-frame annotations synchronized to the video timeline.
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+
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+ The dataset is published in [WebDataset](https://github.com/webdataset/webdataset) format: `~2 GB` tar shards under `data/<map>/`, where each sample is a `<uuid>.mp4` video paired with its `<uuid>.parquet` annotations. A top-level `index.parquet` lists every clip with its `shard` location for lookup and filtering.
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+
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+ ### Annotation schema
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+
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+ Every video clip has its corresponding annotations stored in a `.parquet` file:
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+
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+ | Field | Type | Description |
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+ |---|---|---|
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+ | `map` | string | Map name (e.g. "mirage", "dust2") |
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+ | `round_number` | int | Round within the match |
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+ | `team` | int | 0 = Terrorist, 1 = Counter-Terrorist |
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+ | `num_frames` | int | Total frames in the clip |
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+ | `fps` | float | Video frame rate (48.0) |
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+ | `total_time` | float | Clip duration in seconds |
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+ | `fov` | float | Camera field of view (90.0°) |
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+ | `frame_data` | list[dict] | Per-frame annotation array (see below) |
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+
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+ ### Per-frame annotations
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+
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+ Each entry in `frame_data` contains:
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+
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+ | Field | Description |
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+ |---|---|
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+ | `actions` | Concatenated active keys: **W/A/S/D** (movement), **J** (jump), **C** (crouch), **R** (walk), **V** (freefall), **[** (fire), **]** (scope/secondary), **-** (no input) |
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+ | `mouse_x_delta` | Horizontal camera delta — proxy for mouse X movement |
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+ | `mouse_y_delta` | Vertical camera delta — proxy for mouse Y movement |
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+ | `position_x / y / z` | Player world position in game units |
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+ | `rotation_yaw` | Camera yaw angle (−180° to 180°) |
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+ | `rotation_pitch` | Camera pitch angle (−90° to 90°) |
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+
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+ ## License
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+
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+ Released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) (attribution, non-commercial). The underlying match demos are the property of their respective rights holders; this dataset is provided for research purposes.
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @misc{cs2-10k,
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+ title = {CS2-10k: A Large-Scale Egocentric Counter-Strike 2 Dataset},
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+ author = {Reka AI},
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+ year = {2026},
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+ url = {https://huggingface.co/datasets/RekaAI/CS2-10k}
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+ }
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+ ```
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