搭配服务修改

app/api/api_attribute.py

@@ -15,5 +15,4 @@ router = APIRouter()
 def attribute(request_data: AttributeModel):
     service = AttributeRecognition()
     response = service.attribute(const, request_data)
-    logger.info("test")
     return {"code": 200, "message": "ok", "data": response}

app/api/api_outfit_matcher.py

@@ -1,10 +1,13 @@
 import logging
 import time
+from copy import deepcopy
 
 from fastapi import APIRouter
+from pymilvus import MilvusClient
+
 from app.schemas.outfit_matcher import OutfitMatcher
 from app.service.outfit_matcher.dataset import FashionDataset
-from app.service.outfit_matcher.outfit_evaluator import OutfitMaterTypeAware
+from app.service.outfit_matcher.outfit_evaluator import OutfitMaterTypeAware, Backbone
 from app.service.utils.decorator import RunTime
 
 logger = logging.getLogger()
@@ -19,16 +22,28 @@ def outfit_matcher(request_item: OutfitMatcher):
         request_item['query'][i] = dict(request_item['query'][i])
     for i in range(len(request_item['database'])):
         request_item['database'][i] = dict(request_item['database'][i])
-
-    # try:
     fashion_dataset = FashionDataset(request_item['database'])
+    backbone_service = Backbone()
     service = OutfitMaterTypeAware()
+    all_items = request_item["query"] + request_item["database"]
+    prepared_feature = {}
+    extracted_features = backbone_service.get_result(all_items)
+    data = deepcopy(all_items)  # 做深拷贝 , all_items 是list 可变数组
+    for i, feature in enumerate(extracted_features):
+        data[i]['features'] = feature
+        if 'mapped_cate' in data[i].keys():
+            del data[i]['mapped_cate']
+
+    client = MilvusClient(uri="http://10.1.1.240:19530", token="root:Milvus", db_name="mixi")
+    res = client.insert(collection_name="mixi_outfit", data=data)
+    client.close()
+    for d in data:
+        prepared_feature[d['item_name']] = d['features']
     result = []
     start_time = time.time()
     for item in request_item['query']:
         outfits = fashion_dataset.generate_outfit(item, request_item["topk"], request_item["max_outfits"])
-        scores, features = service.get_result(outfits)
-        # save features in databases
+        scores = service.get_result(outfits, prepared_feature)
 
         if request_item['is_best']:
             best_outfits, best_scores = service.visualize(outfits, scores, request_item["topk"], best=True,
@@ -44,4 +59,4 @@ def outfit_matcher(request_item: OutfitMatcher):
     return {"message": "ok", "data": result}
     # except Exception as e:
     #     logger.warning(e)
-    #     return {"message": f"{e}", "data": e}
+    #     return {"message": f"{e}", "data": e}