Upload README.md

README.md

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+---
+language: en
+license: apache-2.0
+library_name: faiss
+tags:
+- faiss
+- retrieval
+- vector-search
+- marine-images
+- bio-clip
+- oceangpt-x
+---
+# Ocean-FAISS: Marine Image Retrieval Index
+
+High-speed FAISS vector index and metadata for marine image retrieval using BioCLIP embeddings. Core component of the [OceanGPT-X](https://huggingface.co/collections/zjunlp/oceangpt-x) pipeline.
+
+## Repository Contents
+| Path | Description |
+|------|-------------|
+| `faiss/index.faiss` | Pre-built FAISS index containing BioCLIP feature vectors |
+| `faiss/id_map.json` | Mapping between FAISS internal IDs and dataset image IDs |
+| `metadata/metadata.jsonl` | Rich metadata for each indexed image (species, location, capture info) |
+
+## Usage
+Requires `faiss-cpu` or `faiss-gpu`.
+```python
+import faiss
+import json
+import jsonlines
+
+index = faiss.read_index("faiss/index.faiss")
+with open("faiss/id_map.json", "r") as f:
+    id_map = json.load(f)
+
+# Query vector must match the embedding dimension of the index
+query_vector = ...  # Shape: (1, dim), dtype: float32
+D, I = index.search(query_vector, k=5)
+
+# Retrieve metadata
+with jsonlines.open("metadata/metadata.jsonl") as reader:
+    metadata = {obj["id"]: obj for obj in reader}
+
+for idx in I[0]:
+    img_id = id_map[str(idx)]
+    print(metadata.get(img_id, "Not found"))