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1.新增是否推理获取特征判断

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2.取消搭配不足异常逻辑
This commit is contained in:
zhouchengrong
2024-04-05 17:45:25 +08:00
parent 010d1536eb
commit 726eee86ab
7 changed files with 332 additions and 110 deletions
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29
app/api/api_outfit_matcher.py
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@@ -1,4 +1,5 @@
import logging
import os
import time
from copy import deepcopy
@@ -36,20 +37,22 @@ def outfit_matcher(request_item: OutfitMatcher):
# 查询数据库，分成两批 需要过模型推理的和不需要的
have_features_data = []
no_have_features_data = []
for ai in all_items:
temp_data = deepcopy(all_items)
for td in temp_data:
for sd in search_data:
if ai['item_name'] == sd['item_name']:
ai['features'] = sd['features']
if "features" not in ai.keys():
no_have_features_data.append(ai)
if td['item_name'] == sd['item_name']:
td['features'] = sd['features']
if "features" not in td.keys():
no_have_features_data.append(td)
else:
have_features_data.append(ai)
have_features_data.append(td)
if len(no_have_features_data) > 0:
extracted_features = backbone_service.get_result(no_have_features_data)
# 准备数据
data = deepcopy(all_items) # 做深拷贝 , all_items 是list 可变数组
data = deepcopy(no_have_features_data) # 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():
@@ -68,17 +71,17 @@ def outfit_matcher(request_item: OutfitMatcher):
result = []
start_time = time.time()
for item in request_item['query']:
try:
outfits = fashion_dataset.generate_outfit(item, request_item["topk"], request_item["max_outfits"])
except ValueError as e:
logger.warning(e)
return {"code": 500, "message": f"valueError : {e}", "data": e}
# try:
outfits = fashion_dataset.generate_outfit(item, request_item["topk"], request_item["max_outfits"])
# except ValueError as e:
# logger.warning(e)
# return {"code": 500, "message": f"valueError : {e}", "data": e}
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,
# output_path=os.path.join(r"E:\workspace\outfit_matcher\2024 SS Outfit", f"{item['item_name']}_best_{param['topk']}.png")
# output_path=rf"E:\workspace\trinity_client_mixi\app\service\outfit_matcher\output_outfit\{item['item_name']}_best_{request_item['topk']}.png"
)
result.append({"outfits": best_outfits, "scores": best_scores})
else: