attribute 字段名规范

app/service/outfit_matcher/service.py

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+import json
+import os
+from pprint import pprint
+
+from app.service.outfit_matcher.dataset import FashionDataset
+from app.service.outfit_matcher.outfit_evaluator import OutfitMaterTypeAware
+
+if __name__ == '__main__':
+    with open("./test_param/recommendation_test.json", "r") as f:
+        param = json.load(f)
+    fashion_dataset = FashionDataset(param["database"])
+    service = OutfitMaterTypeAware()
+    best_list = []
+    bad_list = []
+    for item in param["query"]:
+        outfits = fashion_dataset.generate_outfit(item, param["topk"], param["max_outfits"])
+        scores, features = service.get_result(outfits)
+        # save  features
+
+        # 链接milvus
+
+        # 存入数据库
+        # 关闭链接
+
+        # print(scores)
+        # print(len(scores))
+        best_outfits, best_scores = service.visualize(outfits, scores, param["topk"], best=True,
+                                                      # output_path=os.path.join(r"E:\workspace\outfit_matcher\2024 SS Outfit", f"{item['item_name']}_best_{param['topk']}.png")
+                                                      )
+        bad_outfits, bad_scores = service.visualize(outfits, scores, param["topk"], best=False,
+                                                    # output_path=os.path.join(r"E:\workspace\outfit_matcher\2024 SS Outfit", f"{item['item_name']}_worst_{param['topk']}.png")
+                                                    )
+        best_list.append({"best_outfits": best_outfits, "best_scores": best_scores})
+        bad_list.append({"bad_outfits": bad_outfits, "bad_scores": bad_scores})
+
+    pprint(best_list)
+    pprint(bad_list)