File size: 2,143 Bytes
ae0175d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | ---
license: other
task_categories:
- text-to-video
- audio-to-audio
language:
- en
tags:
- spatial-audio
- audio-visual
- stereo
- video-editing
- ltx
size_categories:
- 100K<n<1M
---
# SpatialAV2AV — Spatial Audio-Video Editing Dataset
Source→edit pairs for training **spatial (binaural/stereo) audio-video editing** with LTX-2.
Each pair renders the **same clip under a different camera trajectory**; the model learns
`source (pre-edit space) + trajectory instruction → edit (target space)` for both video and
the stereo sound field.
## Contents
Each sample is a triple sharing one basename `<video_id>+<traj>`:
| Path | What |
|------|------|
| `final_json/<clip>.json` | metadata: `video_id`, `traj_name`, `width`, `height`, `fps`, and **relative** paths to `source`/`edit` |
| `final_edit/<clip>.mp4` | **target** video — carries embedded **2-channel / 44.1 kHz stereo** audio |
| `final_source/<clip>.mp4` | **condition** video (same clip, source camera) — also embedded stereo audio |
> Audio is **inside the MP4s** (AAC, real stereo). No separate `.wav` files are needed —
> the trainer reads the audio track directly from each MP4.
`all.list` lists the **116,147-pair training split** (relative json paths). The `final_source`/
`final_edit` folders may contain a larger pool; `all.list` is the authoritative training set.
**Camera trajectories:** `push_in`, `pull_out`, `pan_left`, `pan_right`, `rotate_left`,
`rotate_right`, `fixed_left`, `fixed_right`, `fixed_rot_left`, `fixed_rot_right`.
## Sizes
- Training split: **116,147 pairs**, ~**147 GB** (edit ~0.79 MB + source ~0.50 MB per pair).
- Resolutions: short side ~480; assorted aspect ratios. `fps` = 25.
## Usage
```python
from huggingface_hub import snapshot_download
root = snapshot_download("BingoG/LTX", repo_type="dataset")
# point the trainer's data.json_list at f"{root}/all.list"
# json paths inside are relative to `root`, so they resolve after download.
```
The training loader normalizes each `final_json` entry to `(edit=target video+audio,
source=condition video+audio)` and derives the caption from `traj_name`.
|