Add dataset card, all.list, LFS config

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README.md

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+---
+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`.