关于保存特征的一些代码

test/outfit_matcher_milvus/1.create databases.py

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+from pymilvus import connections, db
+
+conn = connections.connect(host="10.1.1.240", port=19530)
+
+database = db.create_database("mixi")

test/outfit_matcher_milvus/2.create collection.py

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+from pymilvus import MilvusClient, DataType
+
+# 创建client ,配置databases
+client = MilvusClient(
+    uri="http://10.1.1.240:19530",
+    token="root:Milvus",
+    db_name="mixi"
+)
+from pymilvus import MilvusClient, DataType
+
+schema = MilvusClient.create_schema(
+    auto_id=True,
+    enable_dynamic_field=False,
+)
+
+schema.add_field(field_name="id", datatype=DataType.INT64, is_primary=True)
+schema.add_field(field_name="image_path", datatype=DataType.VARCHAR, max_length=200)
+schema.add_field(field_name="vector", datatype=DataType.FLOAT_VECTOR, dim=64)
+
+client.create_collection(
+    collection_name="mixi_outfit",
+    schema=schema
+)

test/outfit_matcher_milvus/3.create index.py

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+from pymilvus import MilvusClient, Collection
+
+client = MilvusClient(
+    uri="http://10.1.1.240:19530",
+    token="root:Milvus",
+    db_name="mixi"
+)
+
+index_params = client.prepare_index_params()
+index_params.add_index(
+    field_name="id",
+    index_type="STL_SORT"
+)
+index_params.add_index(
+    field_name="vector",
+    index_type="IVF_FLAT",
+    metric_type="L2",
+    params={"nlist": 1024}
+)
+client.create_index(
+    collection_name="mixi_outfit",
+    index_params=index_params
+)

test/outfit_matcher_milvus/4.load clollection.py

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+from pymilvus import MilvusClient
+
+client = MilvusClient(
+    uri="http://10.1.1.240:19530",
+    token="root:Milvus",
+    db_name="mixi"
+)
+client.load_collection(
+    collection_name="mixi_outfit"
+)

test/outfit_matcher_milvus/5.similar match.py

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+import json
+import time
+
+from pymilvus import MilvusClient
+
+client = MilvusClient(
+    uri="http://10.1.1.240:19530",
+    token="root:Milvus",
+    db_name="mixi"
+)
+data = [0.019687360152602196, 0.839404821395874, 0.5053166747093201, 0.6062483787536621, 0.5455009341239929, 0.07595491409301758, 0.028354600071907043, 0.24453534185886383, 0.6116685271263123, 0.4527449309825897, 0.22063420712947845, 0.09205381572246552, 0.22853578627109528, 0.3041312098503113,
+        0.8354143500328064, 0.05135197564959526, 0.9292615652084351, 0.03914223983883858, 0.7091595530509949, 0.17939062416553497, 0.2958671748638153, 0.46751415729522705, 0.05523946136236191, 0.976833164691925, 0.3593502938747406, 0.0806853398680687, 0.3097323179244995, 0.12855321168899536,
+        0.12651172280311584, 0.3173355162143707, 0.17060844600200653, 0.9340737462043762, 0.8437095880508423, 0.7500482797622681, 0.22598184645175934, 0.8127533197402954, 0.39825528860092163, 0.9043431878089905, 0.9064653515815735, 0.14613617956638336, 0.582768976688385, 0.4516744315624237,
+        0.6479957699775696, 0.909612774848938, 0.7674093842506409, 0.47747865319252014, 0.5617552995681763, 0.967750072479248, 0.9146659970283508, 0.28031912446022034, 0.5092940330505371, 0.21442186832427979, 0.43696293234825134, 0.7705745100975037, 0.09395607560873032, 0.9103220701217651,
+        0.2616001069545746, 0.7469480037689209, 0.24508604407310486, 0.6890515089035034, 0.704613447189331, 0.7213652729988098, 0.3660031855106354, 0.2150406688451767]
+start_time = time.time()
+res = client.search(
+    collection_name="mixi_outfit",  # Replace with the actual name of your collection
+    # Replace with your query vector
+    data=[data],
+    limit=5,  # Max. number of search results to return
+    # search_params={"metric_type": "IP", "params": {}}  # Search parameters
+)
+print(time.time() - start_time)
+
+result = json.dumps(res, indent=4)
+print(result)