# Adapter packages — license-aware regeneration for restricted sources

The four sources here (HM3D, ScanNet++, OB3D, TartanGround) cannot be redistributed as ERP RGB-D frames under their upstream licenses. Instead, each adapter package contains:

1. A `config.yaml` with all curator / re-encoding parameters used in the paper (resolution, grid spacing, fixed-budget K, thresholds, …).
2. A `pipeline.py` (curator adapters) or `reencoding_script.md` (outdoor re-encoders) describing exactly which command to run and which input layout it expects.
3. A `metadata/source_manifest.json` listing the upstream scene / scan / part IDs that the paper's `K=30` evaluation runs over.

Users that want to reproduce the per-source ERP frames acquire the upstream data themselves (after accepting upstream license terms) and run the adapter locally.

## Per-source quick reference

| Source | License gate | Adapter type | Scene count |
| --- | --- | --- | --- |
| **HM3D** | Matterport / HM3D EULA | curator (NavMesh-based room proposal → CM-EVS greedy) | 401 rooms |
| **ScanNet++** | ScanNet++ ToS | curator (mesh / point-cloud modes) | 500 scans |
| **OB3D** | per upstream | re-encoding (cubemap → ERP, pose unification) | 24 instances (12 scenes × 2 viewpoints) |
| **TartanGround** | per upstream (typically CC-BY-NC-SA) | re-encoding (cubemap → ERP, pose unification) | 762 parts (~11 environments) |

## Curator adapters (HM3D, ScanNet++)

These plug into the standard CM-EVS pipeline:

```
scene asset → adapter (load + normalize + propose candidates) → curator greedy selection →
high-res Cycles ERP render → unified output schema
```

The adapter handles three things specific to that source:

- **Asset loading** (HM3D: `.glb`; ScanNet++: `.ply` point cloud or mesh).
- **Candidate proposal** (HM3D: NavMesh / cluster / label-based; ScanNet++: mesh / point-cloud sampling).
- **Source-specific failure modes** (e.g. ScanNet++ point-cloud mode degrades surface tests to `AABB + splat Z-buffer`).

To run an adapter:

```bash
cd ../code
python pipelines/run_hm3d_pipeline.py     --config ../adapters/hm3d/config.yaml
# or
python pipelines/run_ply_pipeline.py      --config ../adapters/scannetpp/config.yaml
```

Both adapters write to `outputs/<source>/<scene_id>/{rgb,depth,pose,metadata}/...` under the same schema as `blender_indoor/scenes/`.

## Re-encoding adapters (OB3D, TartanGround)

These do **not** run the curator. Their job is to take dense RGB-D-pose trajectories already shipped by the upstream source and re-express them in CM-EVS's unified ERP + world-to-camera pose convention:

- Cubemap → ERP at the source's native resolution.
- Pose re-expressed in right-handed `+Y`-up world frame with scalar-first `q_wc`.
- The full re-encoded trajectory is released — outdoor frames are **not** curator-selected subsets and therefore do not carry per-step provenance logs (`per_step_log.jsonl`).

The `reencoding_script.md` inside each package documents the exact command, expected upstream layout, and output schema.

## Source-id metadata

`metadata/source_manifest.json` in each adapter package lists the upstream IDs that the paper's reported numbers are computed over. If you need to reproduce the **exact** numbers in §5.4 (cross-source) or §4.10 (downstream), use only these IDs.

> **Caveat**: depending on each upstream license, simply listing scene IDs may itself be restricted. Before redistributing or quoting these manifests verbatim, check the upstream's terms. See `../LICENSE.md`.

## Anonymous review note

For NeurIPS double-blind review, no upstream credentials are required to inspect this directory: the adapters list IDs and parameters, but no upstream data ships here. To **execute** an adapter, the reviewer must independently obtain the upstream dataset.