towhee.hub.builtin.operators.milvus_search.milvus_search

class towhee.hub.builtin.operators.milvus_search.milvus_search(collection, **kwargs)

Bases: object

Search for embedding vectors in Milvus. Note that the Milvus collection has data before searching, refer to DataCollection Mixin to_milvus.

Parameters:

• collection (str or pymilvus.Collection) – The collection name or pymilvus.Collection in Milvus.

• kwargs –

  The kwargs with collection.search, refer to https://milvus.io/docs/v2.0.x/search.md#Prepare-search-parameters. And the anns_field defaults to the vector field name, limit defaults to 10, and metric_type in param defaults to ‘L2’ if there has no index(FLAT), and for default index param:

  IVF_FLAT: {“params”: {“nprobe”: 10}}, IVF_SQ8: {“params”: {“nprobe”: 10}}, IVF_PQ: {“params”: {“nprobe”: 10}}, HNSW: {“params”: {“ef”: 10}}, IVF_HNSW: {“params”: {“nprobe”: 10, “ef”: 10}}, RHNSW_FLAT: {“params”: {“ef”: 10}}, RHNSW_SQ: {“params”: {“ef”: 10}}, RHNSW_PQ: {“params”: {“ef”: 10}}, ANNOY: {“params”: {“search_k”: 10}}.

```python import towhee from pymilvus import connections connections.connect(host=’localhost’, port=’19530’) (

towhee.glob[‘path’](‘./*.jpg’)

.image_decode[‘path’, ‘img’]() .image_embedding.timm[‘img’, ‘vec’](model_name=’resnet50’) .milvus_search[‘vec’, ‘results’](collection=’test’) .to_list()

Methods

Attributes

metainfo

__call__(*args, **kws)

Call self as a function.

__init__(collection, **kwargs)