Expose aligned multi-view RGB for realtime final graphs

docs/REALTIME_ENV_GRAPH_PIPELINE.md

@@ -332,3 +332,41 @@ gwam_v12_sparse_v2/episodes/<split>/<task>/episode_XXXXXX.zip
 ```
 
 The offline loader reads already exported arrays and does not require RoboCasa/SAM2 at evaluation time. The online final-graph extractor is for users who need to generate the same kind of final graph from a live environment at every simulation step.
+
+## Multi-view RGB / graph alignment contract
+
+For joint training, evaluation, and real-time inference, the model-facing online call is:
+
+```python
+snapshot = extractor.extract_final_graph(visual_backend=visual_backend)
+graph = snapshot["gnn_graph"]          # x [N_real,342], edge_attr [E,8]
+rgb_frames = snapshot["rgb_frames"]             # dict: view_id -> uint8[256,256,3]
+rgb_frame_cameras = snapshot["rgb_frame_cameras"]  # ordered camera names for those view ids
+```
+
+All fields in one `snapshot` are produced from the same current simulator state before the policy/env step advances:
+
+```text
+current qpos/qvel/contact state
++ current segmentation renders from the ordered camera list
++ current RGB renders from the same ordered camera list
++ current visible RLE masks indexed by (node slot n, view id v)
++ SAM2 masked pooling on rgb_frames[v] using that same mask
+= final graph x [N_real,342]
+```
+
+The ordered multi-view camera contract is:
+
+```text
+v=0 robot0_agentview_right
+v=1 robot0_agentview_left
+v=2 robot0_eye_in_hand
+```
+
+Alignment rules for downstream integration:
+
+- `view_visible[n,v]`, `view_centroid[n,v]`, `view_area[n,v]`, `view_bbox[n,v]`, `rle_masks[*]["v"]`, `visual_features_sparse["v"]`, and `rgb_frames[v]` use the same view id.
+- `visual_features_sparse["n"]` uses the original padded node slot id; `gnn_graph["slot_ids"]` maps active GNN rows back to those padded slots.
+- `rgb_frames[v]` is an upright `uint8[256,256,3]` RGB frame rendered with the same vertical flip convention as the segmentation/mask path.
+- `save_realtime_graph_snapshot(snapshot, out_dir)` writes `rgb/view_<v>_<camera>.npy` plus `rgb_manifest.json`, so saved debug/eval snapshots contain graph data first and aligned RGB images alongside it.
+