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README.md

@@ -17,10 +17,6 @@ configs:
   data_files:
   - split: train
     path: data/default/train-*
-- config_name: scene-metadata
-  data_files:
-  - split: train
-    path: metadata/default/train-*
 ---
 
 # SynGallery: A Synthetic Gallery of Real Paintings for Instance-Level Artwork Recognition
@@ -28,8 +24,8 @@ configs:
 A synthetic dataset for **instance-level artwork recognition**: **4,898 real
 paintings** (MET Open Access) hung in a procedurally randomized 3D art-gallery
 scene, each rendered from **5 camera viewpoints** at 512×512 — **24,490
-synthetic RGB images** paired with their source photos. The environment is
-randomized per scene — wall/floor/roof textures, lighting, frame molding and color,
+synthetic RGB images** paired with their source photos and museum metadata
+(title, artist, date, medium, …). The environment is randomized per scene — wall/floor/roof textures, lighting, frame molding and color,
 optional protective glass, placard, painting scale, and camera-pose jitter.
 
 Rendered headlessly with **Blender 5.1.2 / Cycles** by the
@@ -37,24 +33,19 @@ Rendered headlessly with **Blender 5.1.2 / Cycles** by the
 scene variety is driven by Scene-Time-seeded **Geometry Nodes**, so every
 painting gets an independently randomized room.
 
-## Configs
-
-| config | rows | one row per | contents |
-|---|---|---|---|
-| `default` | 4,898 | scene (painting datapoint) | source photo + all 5 rendered views + per-camera poses |
-| `scene-metadata` | 4,898 | scene (painting datapoint) | full Blender scene dump (raw JSON) |
+## Loading
 
 ```python
 from datasets import load_dataset
 
-ds = load_dataset("patryk-bartkowiak/SynGallery", "default", split="train")          # scenes
-meta = load_dataset("patryk-bartkowiak/SynGallery", "scene-metadata", split="train") # scene dumps
+ds = load_dataset("patryk-bartkowiak/SynGallery", split="train")
 ```
 
-### `default` schema
+## Schema
 
-One row bundles everything about one scene: the MET source photo and the five
-camera views rendered from it.
+A single `train` split, **4,898 rows — one row per scene**, bundling
+everything about that scene: the MET source photo, the five camera views
+rendered from it, and the artwork's museum metadata.
 
 | column | type | meaning |
 |---|---|---|
@@ -62,6 +53,15 @@ camera views rendered from it.
 | `met_object_id` | `int32` | MET museum object id of the source painting |
 | `source_image` | `Image` | the MET source photo itself (web-size JPEG) |
 | `image_30` … `image_150` | `Image` ×5 | the 512×512 RGBA PNG renders from cameras `30`, `60`, `90`, `120`, `150` |
+| `title` | `string` | artwork title (MET Open Access) |
+| `artist` / `artist_bio` | `string` | artist display name / bio (may be empty) |
+| `object_date` | `string` | display date, e.g. `ca. 1580–85` |
+| `object_begin_date` / `object_end_date` | `int32` | machine-readable date range (null if unknown) |
+| `medium` | `string` | e.g. `Oil on copper` |
+| `classification` | `string` | MET classification, e.g. `Paintings` |
+| `culture` / `department` | `string` | culture (may be empty) / MET curatorial department |
+| `met_url` | `string` | the object's page at metmuseum.org |
+| *+ 42 more MET columns* | `string` / `bool` | every remaining `MetObjects.csv` field as its own column: `object_number`, `is_highlight` / `is_timeline_work` / `is_public_domain` (bool), `gallery_number`, `accession_year`, `object_name`, `period`, `dynasty`, `reign`, `portfolio`, `constituent_id`, the `artist_*` details (role, nationality, dates, gender, ULAN/Wikidata URLs, …), `dimensions`, `credit_line`, geography (`city` … `river`), `rights_and_reproduction`, `object_wikidata_url`, `metadata_date`, `repository`, `tags` + tag URLs. Sparse fields are empty strings / nulls |
 | `camera_location_30` … `_150` | `float32[3]` ×5 | each camera's world position at render time (after per-datapoint jitter) |
 | `camera_rotation_euler_30` … `_150` | `float32[3]` ×5 | each camera's world rotation (radians) at render time |
 
@@ -70,17 +70,9 @@ and the source painting by `met_object_id`. Rows are ordered by `index`. There i
 split — any row-level split is automatically painting-level, since all 5
 views live in the same row.
 
-### `scene-metadata` schema
-
-| column | type | meaning |
-|---|---|---|
-| `index` | `int32` | join key to `default` |
-| `met_object_id` | `int32` | as in `default` |
-| `scene_json` | `string` | the datapoint's full `metadata.json`: every visible object (incl. jittered camera poses) and material (Principled BSDF values resolved through node links and Geometry-Nodes attributes) |
-
-Factors randomized *inside* Geometry Nodes (frame variant/color, glass
-presence, painting scale, placard) are baked into the renders but not
-individually labeled; `scene_json` records what Blender exposes.
+Scene-randomization factors (wall/floor/roof textures, lighting, frame
+variant/color, glass presence, painting scale, placard) are baked into the
+renders but not individually labeled.
 
 ## Randomization (this config = ladder rung 5, "all variety")
 
@@ -100,9 +92,12 @@ added here later as extra configs.
 Source paintings are photographs of artworks from the
 [MET Open Access](https://www.metmuseum.org/about-the-met/policies-and-documents/open-access)
 collection (CC0). One representative photo per MET object
-(`paintings_train_images_unique.json` manifest, consumed in order). The 3D
-scene uses commercial PBR texture assets, which appear only baked into the
-rendered pixels.
+(`paintings_train_images_unique.json` manifest, consumed in order). Museum
+metadata is joined from the official
+[MET Open Access `MetObjects.csv`](https://github.com/metmuseum/openaccess)
+(also CC0) by object id — the complete record, every field as its own
+column. The 3D scene uses commercial PBR texture assets,
+which appear only baked into the rendered pixels.
 
 ## Reproduction
 

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