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Diogenes Gameplay Raw Sample v01

Formerly DiogenesLab/Diogenes_Gameplay_raw_sample_v01 — old links redirect here.

A sample dataset. PC gameplay recordings with frame-aligned keyboard/mouse action annotations, in two batches:

batch	recorded	video	audio
batch 1	2026-07-25/26	1920×1080 @ 30 fps, H.264	none
batch 2	2026-07-31	1920×1080 @ 60 fps, H.264	process-loopback system audio, 48 kHz stereo s16le (zstd-compressed PCM)

This is a sample — the recording output available at the time of publication, a small early slice of an ongoing capture effort, not a complete or representative corpus. It exists so collaborators can evaluate recording quality, annotation schema, and time-alignment fidelity. Expect the shape of the data to change in later versions.

⚠️ Not for model training

Every record carries non_trainable: true and production_certified: false, copied verbatim from the source metadata. The originating catalog runs in dev_non_trainable mode and the source game profile is named "Call of Duty® Steam（release 测试，禁止训练）" — "release test, training prohibited".

本数据集不可用于任何模型训练。 所有记录的 non_trainable 标记均为 true， production_certified 均为 false，与源元数据逐字一致。数据来源为 release 测试录制，未取得可训练所需的 consent grant、catalog 认证与 QA 流程。

Constraints that apply:

No training, fine-tuning, or evaluation of models on this data.
The video depicts Call of Duty®, copyright Activision Publishing, Inc. Diogenes Lab claims no rights to the depicted game content. Redistribution outside approved collaborators is not permitted.
These runs predate the consent-grant pipeline; there is no consent_id attached.

Permitted: inspecting recording quality, validating the annotation schema, and reviewing time-alignment between video frames and input events.

	total	batch 1 (30 fps)	batch 2 (60 fps + audio)
Sessions	35	19	16
Runs	36	20	16
Segments (10 s each)	1,787	857	930
Duration	4.92 h	2.36 h	2.56 h
Frames	807,309	254,587	552,722
Input events	858,161	402,692	455,469
Video	32.7 GiB	15.7 GiB	17.0 GiB
Audio segments	865	—	865 (1.37 GiB compressed PCM)

Frames carrying at least one input signal: 540,849 / 807,309 (67.0%). Duplicate frames: 6,295 (0.78% — 0.13% in batch 1, 1.08% in batch 2; at 60 fps WGC re-serves a frame whenever the game renders below 60). Every video and audio object verifies against its recorded SHA-256. Run termination: foreground_lost × 36 (all runs).

Dataset structure

Three parquet tables plus the media, joinable on (session_id, run_id, segment_id):

data/segments.parquet      1,787 rows   one row per 10-second segment (index table)
data/frames.parquet      807,309 rows   one row per video frame, with action labels
data/events.parquet      858,161 rows   one row per raw input event
videos/<session_id>/<run_id>/<segment_id>.mp4
audio/<session_id>/<run_id>/<segment_id>.pcm.zst    (batch 2 only; verbatim capture bytes)
metadata/                catalog and profile documents for batch 1, verbatim (kept in place)
metadata/catalog-2026-07-30.0/   batch-2 pre-audio catalog documents, verbatim
metadata/catalog-2026-07-31.0/   batch-2 audio catalog documents, verbatim
metadata/sessions/       per-session session.json

Audio decodes to exactly audio_frames × 4 bytes of interleaved stereo s16le PCM at 48 kHz (zstd -d < seg.pcm.zst). Segment audio SHA-256, byte counts and health metadata live in the segments table (audio_* columns, null for batch 1).

`segments` fields

Batch-1 fields are unchanged from the original release. Added (nullable, batch 2 only):

field	type	description
`audio_path`	string	repo-relative path to the `.pcm.zst` object
`audio_bytes`	int64	compressed size (bytes)
`audio_sha256`	string	SHA-256 of the compressed object
`audio_frames`	int64	PCM frames (samples per channel)
`audio_sample_rate`, `audio_channels`	int32	48000 / 2
`audio_state`	string	`ready` for all shipped segments

All other fields as before: join key, video_path/video_bytes/video_sha256, num_frames/num_events/duration_s, geometry (width/height/fps — 30.0 or 60.0), provenance (game_id, catalog_id, catalog_version, catalog_mode, mapping_id, mapping_version), mean_bitrate_bps, run outcome, compliance flags, and the time model (qpc_start/qpc_end/run_anchor_qpc/qpc_frequency/run_t_us/t_utc_est).

Time model

Unchanged for batch 1. Batch 2 improvement: the capture client now records the run's wall-clock anchor (anchorAtUtc) next to its QPC anchor, so batch-2 t_utc_est is anchored on a recorded timestamp rather than reconstructed from the session-id epoch. The constant bias caveat from batch 1 does not apply to batch 2; sub-millisecond alignment within a run is still governed by the QPC timebase, which is authoritative in both batches.

Frame windows tile each segment with no gaps (output_qpc_start/output_qpc_end, half-open). Event-to-frame attribution and the precomputed frame_events_json state-change view work exactly as in the original release; keyboard auto-repeat is collapsed there because keys carries held state.

`frames` fields

Unchanged schema. At 60 fps, full segments hold 600 frames instead of 300.

Semantic actions, by frame count (whole corpus; batches differ in fps, so frame counts are not comparable across batches without normalising):

move.forward 320,963 · camera.yaw 302,276 · camera.pitch 255,844 · combat.aim 165,921 · move.right 75,080 · move.left 69,920 · combat.primary_attack 31,334 · move.sprint 29,720

Most frequent virtual-key codes: 87 W (318,572) · 68 D (72,667) · 65 A (67,738) · 16 Shift (28,893) · 81 Q (15,778) · 69 E (11,709) · 83 S (7,006) · 32 Space (4,397).

`events` fields

Unchanged schema, plus one added nullable field:

field	type	description
`repeat`	bool	batch 2 only: the client explicitly marks OS keyboard auto-repeat `key_down` events (`true` on 36,871 events). Null in batch 1 — collapse auto-repeat there by tracking held state, as before.

Event mix (whole corpus): mouse_move 760,361 · key_down 80,085 · key_up 10,102 · mouse_down 3,777 · mouse_up 3,776 · wheel 60.

Usage

from datasets import load_dataset

segments = load_dataset("DiogenesLab/Diogenes_Gameplay_raw_sample_v01", "segments", split="sample")
frames   = load_dataset("DiogenesLab/Diogenes_Gameplay_raw_sample_v01", "frames",   split="sample")
events   = load_dataset("DiogenesLab/Diogenes_Gameplay_raw_sample_v01", "events",   split="sample")

audio_segs = segments.filter(lambda r: r["audio_state"] == "ready")
print(len(audio_segs), audio_segs[0]["audio_path"])

Media files are not embedded in the parquet — fetch them by path:

from huggingface_hub import hf_hub_download

path = hf_hub_download("DiogenesLab/Diogenes_Gameplay_raw_sample_v01",
                       segments[0]["video_path"], repo_type="dataset")

Recording methodology

Recording covers the game window only — no desktop, no other windows. Input is captured at full device resolution in relative-pointer mode, restricted to the key and button set declared in the game profile's input contract. Video frames and input events share a single high-resolution timebase, which is what makes per-frame action attribution exact rather than interpolated. Segments are 10 s and independently hashed.

Batch 2 additionally captures process-loopback system audio (the game process's own output, not the microphone): 48 kHz stereo s16le, zstd-compressed per segment, hashed into the same per-segment integrity manifest. Audio health counters (queue overflows, discontinuities, silence fill, timestamp errors) were zero across all shipped segments.

Runs terminate when the game window loses foreground. A run that fails its recording invariants is discarded wholesale rather than repaired.

Known caveats (read before consuming)

Batch-1 frames plane is missing all Ctrl input. The capture-time configuration declared Ctrl a control key while the mapping bound it to move.prone; the projector dropped every Ctrl event from the frames plane. The raw events table is complete — reconstruct held state from events if you need move.prone in batch 1. Batch 2 recorded under the corrected contract and does not have this issue.
Excluded sessions (present in the source mirror, not shipped — recording invariant violations, listed for transparency): one batch-1 session (frame drop detected), and three batch-2 sessions: dev-1785469615445-0002 (GPU-copy exceeded the 60 fps budget), dev-1785470527520-0004 (input arming failed, zero segments), dev-1785470017742-0003 (run declares 50 segments, mirror holds 49 — tail segment absent).
fps differs between batches (30 vs 60): frame-count statistics are not comparable across batches without normalising; join through time (run_t_us / t_utc_est), not frame indices.
Encoder normalisation by the NVIDIA driver (GOP, low-latency flags) is recorded per segment in the source metadata; mean_bitrate_bps in segments reflects the effective encoder.
MP4s are not faststart (moov at tail); remote streaming readers need the tail first.

Privacy

Input device identifiers are salted per-device hashes (e.g. mouse:0b5c…) and are not reversible. No account names, chat, or user interface outside the game window is captured. Batch-2 audio is process-loopback only — it contains game audio, not microphone input.

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