完成项目训练模块的接口测试
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@ -6,9 +6,10 @@
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# @IDE : PyCharm
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# @desc : pydantic 模型，用于数据库序列化操作
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from pydantic import BaseModel, Field, ConfigDict
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from core.data_types import DatetimeStr
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from typing import Optional
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from datetime import datetime
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from pydantic import BaseModel, Field, ConfigDict
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class ProjectDetectIn(BaseModel):
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@ -36,7 +37,7 @@ class ProjectDetectOut(BaseModel):
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file_type: Optional[str]
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folder_url: Optional[str]
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rtsp_url: Optional[str]
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create_time: Optional[datetime]
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create_datetime: DatetimeStr
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model_config = ConfigDict(from_attributes=True)
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@ -5,9 +5,11 @@
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# @File : project_detect_file.py
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# @IDE : PyCharm
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# @desc : pydantic 模型，用于数据库序列化操作
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from pydantic import BaseModel, Field, ConfigDict
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from core.data_types import DatetimeStr
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from typing import Optional
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from datetime import datetime
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from pydantic import BaseModel, Field, ConfigDict
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class ProjectDetectFilePager(BaseModel):
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@ -21,6 +23,6 @@ class ProjectDetectFileOut(BaseModel):
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detect_id: Optional[int] = Field(..., description="训练集合id")
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file_name: Optional[str] = Field(None, description="文件名称")
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thumb_file_url: Optional[str] = Field(None, description="文件路径")
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create_time: Optional[datetime] = Field(None, description="上传时间")
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create_datetime: DatetimeStr
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model_config = ConfigDict(from_attributes=True)
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@ -6,9 +6,10 @@
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# @IDE : PyCharm
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# @desc : pydantic 模型，用于数据库序列化操作
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from pydantic import BaseModel, Field, ConfigDict
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from core.data_types import DatetimeStr
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from typing import Optional
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from datetime import datetime
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from pydantic import BaseModel, Field, ConfigDict
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class ProjectDetectLogIn(BaseModel):
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@ -25,6 +26,6 @@ class ProjectDetectLogOut(BaseModel):
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train_id: Optional[int]
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train_version: Optional[str]
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pt_type: Optional[str]
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create_time: Optional[datetime]
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create_datetime: DatetimeStr
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model_config = ConfigDict(from_attributes=True)
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@ -6,15 +6,16 @@
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# @IDE : PyCharm
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# @desc : pydantic 模型，用于数据库序列化操作
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from core.data_types import DatetimeStr
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from pydantic import BaseModel, ConfigDict
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from typing import Optional
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from datetime import datetime
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class ProjectDetectLogFileOut(BaseModel):
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id: Optional[int]
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file_name: Optional[str]
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thumb_file_url: Optional[str]
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create_time: Optional[datetime]
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create_datetime: DatetimeStr
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model_config = ConfigDict(from_attributes=True)
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@ -17,7 +17,6 @@ from utils.response import SuccessResponse, ErrorResponse
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import threading
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from redis.asyncio import Redis
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from sqlalchemy.ext.asyncio import AsyncSession
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from fastapi import Depends, APIRouter, Form, UploadFile
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@ -112,6 +112,12 @@ class ProjectInfoDal(DalBase):
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await self.flush(obj)
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return await self.out_dict(obj, None, False, schemas.ProjectInfoOut)
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async def update_version(self, data_id):
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proj = await self.get_data(data_id)
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if proj:
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proj.train_version = proj.train_version + 1
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await self.put_data(data_id=data_id, data=proj)
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class ProjectImageDal(DalBase):
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"""
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@ -246,22 +252,26 @@ class ProjectImageDal(DalBase):
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# 2 主查询
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query = (
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select(
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models.ProjectImage,
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models.ProjectImage.id,
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func.ifnull(subquery.c.label_count, 0).label('label_count')
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)
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.outerjoin(subquery, models.ProjectImage.id == subquery.c.image_id)
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)
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train_count_sql = await self.filter_core(
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v_start_sql=query,
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v_where=[models.ProjectImage.project_id == proj_id, models.ProjectImage.img_type == 'train'],
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v_where=[models.ProjectImage.project_id == proj_id,
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models.ProjectImage.img_type == 'train',
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subquery.c.label_count == 0],
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v_return_sql=True)
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train_count = await self.get_count(train_count_sql)
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train_count = await self.get_count_sql(train_count_sql)
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val_count_sql = await self.filter_core(
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v_start_sql=query,
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v_where=[models.ProjectImage.project_id == proj_id, models.ProjectImage.img_type == 'val'],
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v_where=[models.ProjectImage.project_id == proj_id,
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models.ProjectImage.img_type == 'val',
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subquery.c.label_count == 0],
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v_return_sql=True)
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val_count = await self.get_count(val_count_sql)
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val_count = await self.get_count_sql(val_count_sql)
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return train_count, val_count
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@ -295,14 +305,15 @@ class ProjectLabelDal(DalBase):
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async def get_label_for_train(self, project_id: int):
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id_list = []
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name_list = []
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label_list = self.get_datas(
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label_list = await self.get_datas(
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v_where=[self.model.project_id == project_id],
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limit=0,
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v_order='asc',
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v_order_field='id',
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v_return_count=False)
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for label in label_list:
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id_list.append(label.id)
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name_list.append(label.label_name)
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id_list.append(label['id'])
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name_list.append(label['label_name'])
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return id_list, name_list
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@ -326,10 +337,12 @@ class ProjectImgLabelDal(DalBase):
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async def get_img_label_list(self, image_id: int):
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return await self.get_datas(
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limit=0,
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v_return_count=False,
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v_where=[self.model.image_id == image_id],
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v_order="asc",
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v_order_field="id")
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v_order_field="id",
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v_return_objs=True)
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async def del_img_label(self, label_ids: list[int]):
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img_labels = self.get_datas(v_where=[self.model.label_id.in_(label_ids)])
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@ -6,7 +6,8 @@
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# @IDE : PyCharm
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# @desc : pydantic 模型，用于数据库序列化操作
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from datetime import datetime
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from core.data_types import DatetimeStr
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from pydantic import BaseModel, Field, ConfigDict
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from typing import Optional
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@ -18,6 +19,7 @@ from typing import Optional
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class ProjectTrainIn(BaseModel):
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project_id: Optional[int] = Field(..., description="项目id")
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weights_id: Optional[str] = Field(None, description="权重文件")
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weights_name: Optional[str] = Field(None, description="权重文件名称")
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epochs: Optional[int] = Field(50, description="训练轮数")
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patience: Optional[int] = Field(20, description="早停的耐心值")
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@ -28,7 +30,7 @@ class ProjectTrainOut(BaseModel):
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weights_name: Optional[str] = Field(None, description="权重名称")
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epochs: Optional[int] = Field(None, description="训练轮数")
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patience: Optional[int] = Field(None, description="早停的耐心值")
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create_time: Optional[datetime] = Field(None, description="训练时间")
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create_datetime: DatetimeStr
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model_config = ConfigDict(from_attributes=True)
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@ -1,4 +1,4 @@
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from utils import os_utils as os
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from utils import os_utils as osu
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from application.settings import *
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from . import schemas, models, crud
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from utils.websocket_server import room_manager
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@ -19,34 +19,39 @@ async def before_train(proj_info: proj_models.ProjectInfo, db: AsyncSession):
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:param db: 数据库session
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:return:
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"""
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proj_dal = proj_crud.ProjectInfoDal(db)
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img_dal = proj_crud.ProjectImageDal(db)
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label_dal = proj_crud.ProjectLabelDal(db)
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# 先查询两个图片列表
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project_images_train = img_dal.get_data(
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v_where=[proj_models.ProjectImage.project_id == proj_info.id, proj_models.ProjectImage.img_type == 'train'])
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project_images_val = img_dal.get_data(
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v_where=[proj_models.ProjectImage.project_id == proj_info.id, proj_models.ProjectImage.img_type == 'val'])
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project_images_train = await img_dal.get_datas(
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v_where=[proj_models.ProjectImage.project_id == proj_info.id, proj_models.ProjectImage.img_type == 'train'],
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limit=0,
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v_return_count=False,
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v_return_objs=True)
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project_images_val = await img_dal.get_datas(
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v_where=[proj_models.ProjectImage.project_id == proj_info.id, proj_models.ProjectImage.img_type == 'val'],
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limit=0,
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v_return_count=False,
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v_return_objs=True)
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# 得到训练版本
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version_path = 'v' + str(proj_info.train_version + 1)
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# 创建训练的根目录
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train_path = os.create_folder(datasets_url, proj_info.project_no, version_path)
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train_path = osu.create_folder(datasets_url, proj_info.project_no, version_path)
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# 查询项目所属标签，返回两个 id，name一一对应的数组
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label_id_list, label_name_list = label_dal.get_label_for_train(proj_info.id)
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label_id_list, label_name_list = await label_dal.get_label_for_train(proj_info.id)
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# 创建图片的的两个文件夹
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img_path_train = os.create_folder(train_path, 'images', 'train')
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img_path_val = os.create_folder(train_path, 'images', 'val')
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img_path_train = osu.create_folder(train_path, 'images', 'train')
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img_path_val = osu.create_folder(train_path, 'images', 'val')
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# 创建标签的两个文件夹
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label_path_train = os.create_folder(train_path, 'labels', 'train')
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label_path_val = os.create_folder(train_path, 'labels', 'val')
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label_path_train = osu.create_folder(train_path, 'labels', 'train')
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label_path_val = osu.create_folder(train_path, 'labels', 'val')
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# 在根目录下创建yaml文件
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yaml_file = os.file_path(train_path, proj_info.project_no + '.yaml')
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yaml_file = osu.file_path(train_path, proj_info.project_no + '.yaml')
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yaml_data = {
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'path': train_path,
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'train': 'images/train',
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@ -59,20 +64,20 @@ async def before_train(proj_info: proj_models.ProjectInfo, db: AsyncSession):
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# 开始循环复制图片和生成label.txt
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# 先操作train
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operate_img_label(project_images_train, img_path_train, label_path_train, db, label_id_list)
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await operate_img_label(project_images_train, img_path_train, label_path_train, db, label_id_list)
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# 再操作val
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operate_img_label(project_images_val, img_path_val, label_path_val, db, label_id_list)
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await operate_img_label(project_images_val, img_path_val, label_path_val, db, label_id_list)
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# 开始执行异步训练
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data = yaml_file
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project = os.file_path(runs_url, proj_info.project_no)
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project = osu.file_path(runs_url, proj_info.project_no)
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name = version_path
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return data, project, name
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async def operate_img_label(
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img_list: list[proj_models.ProjectImgLabel],
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img_list: list[proj_models.ProjectImage],
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img_path: str,
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label_path: str,
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db: AsyncSession,
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@ -90,10 +95,10 @@ async def operate_img_label(
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image = img_list[i]
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# 先复制图片，并把图片改名，不改后缀
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file_name = 'image' + str(i)
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os.copy_and_rename_file(image.image_url, img_path, file_name)
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osu.copy_and_rename_file(image.image_url, img_path, file_name)
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# 查询这张图片的label信息然后生成这张照片的txt文件
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img_label_list = await proj_crud.ProjectImgLabelDal(db).get_img_label_list(image.id)
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label_txt_path = os.file_path(label_path, file_name + '.txt')
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label_txt_path = osu.file_path(label_path, file_name + '.txt')
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with open(label_txt_path, 'w', encoding='utf-8') as file:
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for image_label in img_label_list:
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index = label_id_list.index(image_label.label_id)
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@ -103,20 +108,19 @@ async def operate_img_label(
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+ image_label.mark_height + '\n')
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async def run_event_loop(
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def run_event_loop(
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data: str,
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project: str,
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name: str,
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train_in: schemas.ProjectTrainIn,
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project_id: int,
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db: AsyncSession):
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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# 运行异步函数
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loop.run_until_complete(run_commend(data, project, name, train_in.epochs, train_in.patience, train_in.weights_id,
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project_id, db))
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# 可选: 关闭循环
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loop.close()
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train_info: models.ProjectTrain,
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is_gup: str):
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# 运行异步函数，开始训练
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loop_run = asyncio.new_event_loop()
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asyncio.set_event_loop(loop_run)
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loop_run.run_until_complete(run_commend(data, project, name, train_in.epochs, train_in.patience,
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project_id, train_info, is_gup))
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async def run_commend(
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@ -125,10 +129,9 @@ async def run_commend(
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name: str,
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epochs: int,
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patience: int,
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weights: str,
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project_id: int,
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db: AsyncSession,
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rd: Redis):
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train_info: models.ProjectTrain,
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is_gpu: str):
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"""
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执行训练
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:param data: 训练数据集
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@ -138,23 +141,20 @@ async def run_commend(
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:param patience: 早停耐心值
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:param weights: 权重文件
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:param project_id: 项目id
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:param db: 数据库session
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:param rd: redis连接
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:param train_info: 训练信息
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:param is_gpu: 是否是gpu环境
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:return:
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"""
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yolo_path = os.file_path(yolo_url, 'train.py')
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yolo_path = osu.file_path(yolo_url, 'train.py')
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room = 'train_' + str(project_id)
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await room_manager.send_to_room(room, f"AiCheckV2.0: 模型训练开始，请稍等。。。\n")
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commend = ["python", '-u', yolo_path, "--data=" + data, "--project=" + project, "--name=" + name,
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"--epochs=" + str(epochs), "--batch-size=8", "--exist-ok", "--patience=" + str(patience)]
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# 增加权重文件，在之前训练的基础上重新巡逻
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if weights != '' and weights is not None:
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train_info = await crud.ProjectTrainDal(db).get_data(data_id=int(weights))
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if train_info is not None:
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commend.append("--weights=" + train_info.best_pt)
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# 增加权重文件，在之前训练的基础上重新训练
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if train_info is not None:
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commend.append("--weights=" + train_info.best_pt)
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is_gpu = rd.get('is_gpu')
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# 判断是否存在cuda版本
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if is_gpu == 'True':
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commend.append("--device=0")
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@ -180,20 +180,33 @@ async def run_commend(
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await room_manager.send_to_room(room, 'error')
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else:
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await room_manager.send_to_room(room, 'success')
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# 然后保存版本训练信息
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train = models.ProjectTrain()
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train.project_id = project_id
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train.train_version = name
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train_url = os.file_path(project, name)
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train.train_url = train_url
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train.train_data = data
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bast_pt_path = os.file_path(train_url, 'weights', 'best.pt')
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last_pt_path = os.file_path(train_url, 'weights', 'last.pt')
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train.best_pt = bast_pt_path
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train.last_pt = last_pt_path
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if weights is not None and weights != '':
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train.weights_id = weights
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train.weights_name = train_info.train_version
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train.patience = patience
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train.epochs = epochs
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await crud.ProjectTrainDal(db).create_data(data=train)
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async def add_train(
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db,
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project_id,
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name,
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project,
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data,
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train_in,
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user_id):
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# 更新版本信息
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await proj_crud.ProjectInfoDal(db).update_version(data_id=project_id)
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# 增加训练版本信息
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train = models.ProjectTrain()
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train.project_id = project_id
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train.train_version = name
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train_url = osu.file_path(project, name)
|
||||
train.train_url = train_url
|
||||
train.train_data = data
|
||||
train.user_id = user_id
|
||||
bast_pt_path = osu.file_path(train_url, 'weights', 'best.pt')
|
||||
last_pt_path = osu.file_path(train_url, 'weights', 'last.pt')
|
||||
train.best_pt = bast_pt_path
|
||||
train.last_pt = last_pt_path
|
||||
if train_in is not None:
|
||||
train.weights_id = train_in.weights_id
|
||||
train.weights_name = train_in.weights_name
|
||||
train.patience = train_in.patience
|
||||
train.epochs = train_in.epochs
|
||||
await crud.ProjectTrainDal(db).create_model(data=train)
|
||||
@ -3,6 +3,8 @@
|
||||
# @version : 1.0
|
||||
# @Create Time : 2025/04/03 10:32
|
||||
# @File : views.py
|
||||
|
||||
from core.database import redis_getter
|
||||
from . import models, schemas, crud, service
|
||||
from apps.vadmin.auth.utils.current import AllUserAuth
|
||||
from apps.vadmin.auth.utils.validation.auth import Auth
|
||||
@ -10,6 +12,7 @@ from utils.response import SuccessResponse, ErrorResponse
|
||||
from apps.business.project.crud import ProjectInfoDal, ProjectImageDal
|
||||
|
||||
import threading
|
||||
from redis.asyncio import Redis
|
||||
from fastapi import APIRouter, Depends
|
||||
|
||||
|
||||
@ -19,10 +22,11 @@ app = APIRouter()
|
||||
###########################################################
|
||||
# 项目训练信息
|
||||
###########################################################
|
||||
@app.post("/", summary="执行训练")
|
||||
@app.post("/start", summary="执行训练")
|
||||
async def run_train(
|
||||
train_in: schemas.ProjectTrainIn,
|
||||
auth: Auth = Depends(AllUserAuth())):
|
||||
auth: Auth = Depends(AllUserAuth()),
|
||||
rd: Redis = Depends(redis_getter)):
|
||||
proj_id = train_in.project_id
|
||||
proj_dal = ProjectInfoDal(auth.db)
|
||||
proj_img_dal = ProjectImageDal(auth.db)
|
||||
@ -43,12 +47,17 @@ async def run_train(
|
||||
return ErrorResponse("训练图片中存在未标注的图片")
|
||||
if val_label_count > 0:
|
||||
return ErrorResponse("验证图片中存在未标注的图片")
|
||||
data, project, name = service.before_train(proj_info, auth.db)
|
||||
data, project, name = await service.before_train(proj_info, auth.db)
|
||||
is_gpu = await rd.get('is_gpu')
|
||||
train_info = None
|
||||
if train_in.weights_id is not None:
|
||||
train_info = await crud.ProjectTrainDal(auth.db).get_data(train_in.weights_id)
|
||||
# 异步执行操作，操作过程通过websocket进行同步
|
||||
thread_train = threading.Thread(
|
||||
target=service.run_event_loop,
|
||||
args=(data, project, name, train_in, proj_id, auth.db,))
|
||||
args=(data, project, name, train_in, proj_id, train_info, is_gpu))
|
||||
thread_train.start()
|
||||
await service.add_train(auth.db, proj_id, name, project, data, train_in, auth.user.id)
|
||||
return SuccessResponse(msg="执行成功")
|
||||
|
||||
|
||||
@ -57,15 +66,16 @@ async def train_list(
|
||||
proj_id: int,
|
||||
auth: Auth = Depends(AllUserAuth())):
|
||||
datas = await crud.ProjectTrainDal(auth.db).get_datas(
|
||||
limit=0,
|
||||
v_where=[models.ProjectTrain.project_id == proj_id],
|
||||
v_schema=schemas.ProjectTrainOut,
|
||||
v_order="asc",
|
||||
v_order_field="id",v_return_count=False)
|
||||
v_order_field="id",
|
||||
v_return_count=False)
|
||||
return SuccessResponse(data=datas)
|
||||
|
||||
|
||||
@app.get("/result/{proj_id}", summary="查询训练报告")
|
||||
async def get_result(train_id:int, auth: Auth = Depends(AllUserAuth())):
|
||||
@app.get("/result/{train_id}", summary="查询训练报告")
|
||||
async def get_result(train_id: int, auth: Auth = Depends(AllUserAuth())):
|
||||
result = await crud.ProjectTrainDal(auth.db).get_result(train_id)
|
||||
return SuccessResponse(data=result)
|
||||
|
||||
|
||||
10
core/crud.py
10
core/crud.py
@ -263,11 +263,17 @@ class DalBase:
|
||||
await self.db.execute(insert(self.model), datas)
|
||||
await self.db.flush()
|
||||
|
||||
async def create_model(self, data: Any) -> None:
|
||||
"""
|
||||
创建单个model
|
||||
:param data: model
|
||||
"""
|
||||
self.db.add(data)
|
||||
await self.db.flush()
|
||||
|
||||
async def create_models(self, datas: list[Any]) -> None:
|
||||
"""
|
||||
批量创建数据
|
||||
SQLAlchemy 2.0 批量插入不支持 MySQL 返回值：
|
||||
https://docs.sqlalchemy.org/en/20/orm/queryguide/dml.html#getting-new-objects-with-returning
|
||||
:param datas: model数组
|
||||
"""
|
||||
self.db.add_all(datas)
|
||||
|
||||
@ -7,7 +7,7 @@ from utils.websocket_server import room_manager
|
||||
|
||||
def websocket_config(app: FastAPI):
|
||||
|
||||
@app.websocket("/{room}")
|
||||
@app.websocket("/ws/{room}")
|
||||
async def websocket_room(websocket: WebSocket, room: str):
|
||||
"""
|
||||
websocket 房间管理
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user