Haosonnn/wan22-incontext-control-data

Wan2.2 In-Context Control — derived training data

Derived metadata/pose NPZs for the in-context camera + audio control fork of DiffSynth-Studio (training Wan2.2-TI2V-5B). This repo holds only the small derived files needed to reproduce the camera and audio (e11h) runs. It does not rehost source videos — those come from the original datasets linked below.

Companion code: the DiffSynth-Studio fork (see its README for the full reproduction walkthrough).

Files

File	Size	Used by
orbit_lr_first49_thr0.97.npz	~102 MB	Camera training (orbit-left/right subset, 5881 clips)
train_data_openhumanvid_monst3r_001-040.npz	~106 MB	Audio (e11h) + joint training (OpenHumanVid, 32,176 clips)
sa5b_200subset/metadata.csv	—	e11h 200-clip subset (long captions)
sa5b_200subset/metadata_generic.csv	—	e11h 200-clip subset (generic prompt — the run used this)

Download (huggingface_hub 1.x CLI is hf):

hf download Haosonnn/wan22-incontext-control-data --repo-type dataset --local-dir data/

This lands data/orbit_lr_first49_thr0.97.npz, data/train_data_openhumanvid_monst3r_001-040.npz, and data/sa5b_200subset/*.csv — the paths the launch scripts expect.

NPZ schema

Both NPZs are a NumPy object array under key arr_0 — a Python list of per-clip dicts.

orbit_lr_first49_thr0.97.npz (camera; derived from RealCam-Vid):

key	shape / type	meaning
dataset_source	str	RealEstate10K / DL3DV-10K / MiraData9K
video_path	str	path relative to the RealCam-Vid video root
short_caption, long_caption	str	captions
camera_intrinsics	(4,)	normalized fx, fy, cx, cy
camera_extrinsics	(F,4,4)	world-to-camera; full length, not truncated
align_factor	float	per-clip translation scale
camera_scale, vtss_score	float	scene scale / quality score

5881 clips = orbit-left ∪ orbit-right, selected by motion-cosine ≥ 0.97 among clips with ≥ 49 frames ("first49" is the ≥49-frame selection filter — extrinsics are kept at full length).

train_data_openhumanvid_monst3r_001-040.npz (audio / joint; OpenHumanVid + monst3r poses):

key	shape / type	meaning
video_path, audio_path	str	same mp4 (audio is in-stream), relative to the OpenHumanVid root
short_caption, long_caption	str	captions
camera_intrinsics	(4,)	normalized fx, fy, cx, cy
camera_extrinsics	(20,4,4)	sparse keyframe world-to-camera (monst3r; no align_factor)
camera_extrinsics_kf_inds	(20,)	keyframe frame indices → interpolate to sampled frames
face_bbox, lip_bbox	(4,)	pixel coords x0,y0,x1,y1 → normalize by video_width/height
face_conf, lip_conf	float	detector confidence
camera_scale, video_width, video_height	—	scene scale / resolution

sa5b_200subset CSVs

Columns video, prompt, sample. sample is the row index into the OpenHumanVid NPZ and prompt is portable; the video column holds the original absolute cluster paths and must be repointed to your local OpenHumanVid video root (or regenerate the metadata with precompute_openhumanvid.py, preserving the sample indices). metadata_generic.csv (the one the e11h run used) replaces captions with a fixed generic prompt.

Provenance & licenses

• Camera NPZ is derived from the official RealCam-Vid dataset (MuteApo/RealCam-Vid) — the subset selection (motion-descriptor cosine similarity vs preset trajectories) is reproducible with the tools/ scripts in the code repo. RealCam-Vid in turn processes RealEstate10K, DL3DV-10K, and MiraData. Respect their licenses. The full RealCam-Vid_train.npz is not rehosted here — get it from the official repo.
• OpenHumanVid NPZ annotations were produced by running monst3r pose reconstruction + face/lip detection over OpenHumanVid clips (the detection/reconstruction pipeline lives outside the code repo). The source talking-head videos are hosted separately at Haosonnn/OpenHumanVid-Talking; this repo holds only the derived annotations/metadata.
• This derived-metadata release inherits the terms of the upstream datasets; use for research.