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代码整理
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zcr
2025-12-30 17:49:22 +08:00
parent aa57478852
commit 4951fab71a
1 changed files with 59 additions and 58 deletions
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117
app/service/design_fast/pipeline/keypoint.py
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@@ -1,7 +1,7 @@
import logging
import numpy as np
from pymilvus import MilvusClient
# from pymilvus import MilvusClient
from app.core.config import KEYPOINT_RESULT_TABLE_FIELD_SET, MILVUS_TABLE_KEYPOINT, settings
from app.service.design_fast.utils.design_ensemble import get_keypoint_result
@@ -54,63 +54,64 @@ class KeyPoint:
"keypoint_vector": result.tolist()
}
]
try:
client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
client.upsert(collection_name=MILVUS_TABLE_KEYPOINT, data=data)
client.close()
return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
except Exception as e:
logger.info(f"save keypoint cache milvus error : {e}")
return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
@staticmethod
def update_keypoint_cache(keypoint_id, infer_result, search_result, site):
if site == "up":
# 需要的是up 即推理出来的是up 那么查询的就是down
result = np.concatenate([infer_result.flatten(), search_result[-4:]])
else:
# 需要的是down 即推理出来的是down 那么查询的就是up
result = np.concatenate([search_result[:20], infer_result.flatten()])
data = [
{"keypoint_id": keypoint_id,
"keypoint_site": "all",
"keypoint_vector": result.tolist()
}
]
# try:
# client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
# client.upsert(collection_name=MILVUS_TABLE_KEYPOINT, data=data)
# client.close()
# except Exception as e:
# logger.info(f"save keypoint cache milvus error : {e}")
# return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
try:
client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
client.upsert(
collection_name=MILVUS_TABLE_KEYPOINT,
data=data
)
return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
except Exception as e:
logger.info(f"save keypoint cache milvus error : {e}")
return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
# @staticmethod
# def update_keypoint_cache(keypoint_id, infer_result, search_result, site):
# if site == "up":
# # 需要的是up 即推理出来的是up 那么查询的就是down
# result = np.concatenate([infer_result.flatten(), search_result[-4:]])
# else:
# # 需要的是down 即推理出来的是down 那么查询的就是up
# result = np.concatenate([search_result[:20], infer_result.flatten()])
# data = [
# {"keypoint_id": keypoint_id,
# "keypoint_site": "all",
# "keypoint_vector": result.tolist()
# }
# ]
#
# try:
# client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
# client.upsert(
# collection_name=MILVUS_TABLE_KEYPOINT,
# data=data
# )
# return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
# except Exception as e:
# logger.info(f"save keypoint cache milvus error : {e}")
# return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))
@RunTime
def keypoint_cache(self, result, site):
try:
client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
keypoint_id = result['image_id']
res = client.query(
collection_name=MILVUS_TABLE_KEYPOINT,
# ids=[keypoint_id],
filter=f"keypoint_id == {keypoint_id}",
output_fields=['keypoint_vector', 'keypoint_site']
)
if len(res) == 0:
# 没有结果 直接推理拿结果 并保存
keypoint_infer_result, site = self.infer_keypoint_result(result)
return self.save_keypoint_cache(result['image_id'], keypoint_infer_result, site)
elif res[0]["keypoint_site"] == "all" or res[0]["keypoint_site"] == site:
# 需要的类型和查询的类型一致，或者查询的类型为all 则直接返回查询的结果
return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, np.array(res[0]['keypoint_vector']).astype(int).reshape(12, 2).tolist()))
elif res[0]["keypoint_site"] != site:
# 需要的类型和查询到的不一致，则更新类型为all
keypoint_infer_result, site = self.infer_keypoint_result(result)
return self.update_keypoint_cache(result["image_id"], keypoint_infer_result, res[0]['keypoint_vector'], site)
except Exception as e:
logger.info(f"search keypoint cache milvus error {e}")
return False
# @RunTime
# def keypoint_cache(self, result, site):
# try:
# client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
# keypoint_id = result['image_id']
# res = client.query(
# collection_name=MILVUS_TABLE_KEYPOINT,
# # ids=[keypoint_id],
# filter=f"keypoint_id == {keypoint_id}",
# output_fields=['keypoint_vector', 'keypoint_site']
# )
# if len(res) == 0:
# # 没有结果 直接推理拿结果 并保存
# keypoint_infer_result, site = self.infer_keypoint_result(result)
# return self.save_keypoint_cache(result['image_id'], keypoint_infer_result, site)
# elif res[0]["keypoint_site"] == "all" or res[0]["keypoint_site"] == site:
# # 需要的类型和查询的类型一致，或者查询的类型为all 则直接返回查询的结果
# return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, np.array(res[0]['keypoint_vector']).astype(int).reshape(12, 2).tolist()))
# elif res[0]["keypoint_site"] != site:
# # 需要的类型和查询到的不一致，则更新类型为all
# keypoint_infer_result, site = self.infer_keypoint_result(result)
# return self.update_keypoint_cache(result["image_id"], keypoint_infer_result, res[0]['keypoint_vector'], site)
# except Exception as e:
# logger.info(f"search keypoint cache milvus error {e}")
# return False