Add GSO WebDataset: 1030 objects, 43 shards (trimesh 4.12.2)

LICENSE

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+Google Scanned Objects dataset repackaging
+Copyright 2020 Google LLC.
+
+This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0).
+To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/.
+
+Attribution
+-----------
+Source: Google Scanned Objects (https://goo.gle/scanned-objects)
+Original author: Google LLC <scanned-objects@google.com>
+
+You are free to share and adapt this material for any purpose, even
+commercially, under the following terms:
+  - Attribution: You must give appropriate credit, provide a link to the
+    license, and indicate if changes were made.
+
+Changes made in this repackaging: objects were extracted from their original
+zip archives, converted to a WebDataset layout, and each mesh was normalized
+into a self-contained GLB with trimesh (centered and scaled to a unit cube).
+Original obj/mtl/texture and render thumbnails are preserved.

README.md

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+---
+license: cc-by-4.0
+pretty_name: Google Scanned Objects (WebDataset)
+tags:
+- 3d
+- mesh
+- glb
+- webdataset
+- google-scanned-objects
+- trellis
+task_categories:
+- image-to-3d
+- text-to-3d
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/*.tar
+---
+
+# Google Scanned Objects (WebDataset)
+
+A `load_dataset`-ready [WebDataset](https://github.com/webdataset/webdataset)
+packaging of the **Google Scanned Objects** dataset: high-quality 3D scans of common
+household items. Each object provides the original mesh/material/texture, five
+render thumbnails, structured metadata, and a **normalized GLB** produced with
+[`trimesh`](https://github.com/mikedh/trimesh) for direct use in 3D pipelines
+(e.g. TRELLIS-2 fine-tuning).
+
+- Objects: **1030**
+- Shards: **43** (`data/gso-train-*.tar`)
+- License: **Creative Commons Attribution 4.0 International** (cc-by-4.0)
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("suvadityamuk/google-scanned-objects", split="train")
+sample = ds[0]
+print(sample["json"]["name"], sample["json"]["category"])
+sample["texture.png"]        # PIL.Image (diffuse texture)
+sample["thumbnail_0.jpg"]    # PIL.Image (render)
+glb_bytes = sample["glb"]    # bytes of a self-contained, normalized .glb
+```
+
+Streaming works too (no full download):
+
+```python
+ds = load_dataset("suvadityamuk/google-scanned-objects", split="train", streaming=True)
+sample = next(iter(ds))
+```
+
+> GLB is a recognized mesh extension in the `datasets` WebDataset builder, so
+> `glb` is loaded as a `Mesh` feature and rendered in the dataset viewer.
+> A recent `datasets` version is required for the `Mesh` feature.
+
+## Per-sample fields
+
+| field | type | description |
+|-------|------|-------------|
+| `obj` | bytes | original `model.obj` mesh |
+| `mtl` | bytes | original `model.mtl` material |
+| `texture.png` | Image | diffuse texture |
+| `glb` | Mesh | normalized, self-contained GLB (see below) |
+| `thumbnail_0.jpg` .. `thumbnail_4.jpg` | Image | 5 render thumbnails |
+| `json` | dict | metadata + `glb_processing` stats |
+
+The `json` field contains: `object_id`, `name`, `description`, `version`,
+`category`, `annotations` (e.g. `brand`, `gtin`, `sku`), `author`, `license`,
+`license_id`, `license_url`, `copyright`, `source`, `num_thumbnails_original`,
+and `glb_processing`.
+
+## GLB normalization (trimesh)
+
+Produced deterministically per object with `trimesh==4.12.2`:
+
+1. Copy `materials/textures/texture.png` next to the OBJ so the MTL's
+   `map_Kd texture.png` resolves and the diffuse map binds.
+2. `trimesh.load(obj, process=False, force="mesh")` — preserves UVs, flattens
+   to a single mesh.
+3. Translate the axis-aligned bounding-box center to the origin.
+4. Uniformly scale so the longest AABB edge is `1.0` (fits a unit cube).
+5. Preserve UVs (no vertex merge); recompute normals only if missing.
+6. Export a self-contained `.glb` with the texture embedded.
+
+Every object's exact transform (`applied_translation`, `applied_scale`),
+mesh stats (`vertices`, `faces`, `is_watertight`, `surface_area_normalized`,
+`orig_extents`, `final_extents`, `texture_size`, `glb_size_bytes`) and any
+`warnings` are recorded in `json["glb_processing"]` and aggregated in
+[`stats/processing_log.jsonl`](./stats/processing_log.jsonl).
+
+## License & attribution
+
+This dataset is a repackaging of the Google Scanned Objects dataset by Google LLC,
+licensed under [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0/) (`cc-by-4.0`).
+
+> "Google Scanned Objects", Copyright 2020 Google LLC, licensed under CC BY 4.0.
+
+You must give appropriate credit when using this data. See the `LICENSE` file
+and each object's `json["copyright"]` / `json["license"]` fields.

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