---
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"))