Update dataset documentation

README.md

@@ -15,6 +15,8 @@ A prebuilt asset index and vector library for searching individual 3D objects wi
 
 This bundle contains metadata and description embeddings. Model files can be obtained through the download locations stored in the asset records.
 
+Code and usage examples: [ObjectAtlas on GitHub](https://github.com/embosys/ObjectAtlas).
+
 ## Contents
 
 | File | Purpose | Size |
@@ -46,21 +48,9 @@ artifacts/
       vectors.f32
 ```
 
-## Use with ObjectAtlas
-
-Place this bundle under the ObjectAtlas code directory as `artifacts/`, keeping the layout above. Install the dependencies listed in the code project's `requirements.txt`, then run from that project directory:
-
-```bash
-python scripts/search.py --text "a wooden dining chair" --top-k 10
-```
-
-If the data is stored elsewhere, use `--data` to specify the directory containing `data/`. Search results contain the asset record, similarity score, and best matching caption. The code project's README describes all search parameters.
-
-The first text query may download the encoder. After it is cached, `--local-files-only` enables offline queries.
-
 ## Asset metadata
 
-The `assets` table in `data/index.sqlite` contains five fields:
+The `assets` tables in `data/index.sqlite` and `extra/extra.sqlite` share five fields:
 
 | Field | Description |
 |---|---|
@@ -68,11 +58,11 @@ The `assets` table in `data/index.sqlite` contains five fields:
 | `source_dataset` | Original asset dataset, such as `objaverse`, `objaverse_xl`, or `abo` |
 | `original_id` | Original model ID, stored as a string with leading zeros and case preserved |
 | `captions` | Descriptions grouped under `cap3d`, `marvel_40m_plus`, and `trellis_500k`; each item contains `text` and the original `field` |
-| `download_urls` | Individual asset file locations |
+| `download_urls` | Available asset file locations; an empty list for extra assets awaiting local installation |
 
-`captions` and `download_urls` are stored as JSON text in SQLite. Missing caption sources use empty lists. The search script decodes these fields into objects and arrays.
+`captions` and `download_urls` are stored as JSON text in SQLite. Missing caption sources use empty lists.
 
-Assets are matched by their confirmed original dataset and model identity. Similar captions, names, or categories do not establish asset identity. A single asset can have multiple description vectors, and search returns each asset once using its highest matching score.
+Assets are matched by their confirmed original dataset and model identity. Similar captions, names, or categories do not establish asset identity. A single asset can have multiple description vectors.
 
 ## Vector format
 
@@ -86,13 +76,11 @@ Assets are matched by their confirmed original dataset and model identity. Simil
 | Raw format | Headerless, row-major, little-endian float32 (`<f4`) |
 | Similarity | Cosine similarity |
 
-The SQLite caption table and vector segment metadata link vector IDs to assets and their descriptions. Use the supplied search script to retrieve candidates from FAISS and rerank them with the full precision vectors.
-
-## Optional extra data
+The SQLite `captions` table links vector IDs to assets and their descriptions. The `vector_segments` table records each raw vector segment's path, first ID, and row count. The main FAISS index uses the same caption vector IDs.
 
-The main database can be searched independently. The included extra collection supports Toys4k, OmniObject3D, and selected ShapeNet categories whose models are distributed in archives.
+## Extra collection
 
-To install extra assets, use the code project's `extra/run_extra.py` to download official archives, extract them, verify local assets, and merge passing records and their vectors into the main database. Original extra records are retained. Merged file locations use `file://` URLs computed for the user's machine.
+The extra collection contains Toys4k, OmniObject3D, and selected ShapeNet categories whose models are distributed in archives. It includes original asset metadata, official archive manifests, and precomputed description vectors. Model archives and extracted model files are not included in this bundle.
 
 ## Sources and licenses