完成线程启动训练并以websocket的方式进行发送shell

app/api/business/project_train_api.py

@@ -3,18 +3,20 @@ from app.model.crud import project_label_crud as plc
 from app.model.crud import project_info_crud as pic
 from app.model.crud import project_image_crud as pimc
 from app.model.crud import project_train_crud as ptnc
-from app.model.schemas.project_info_schemas import ProjectInfoIn, ProjectInfoPager
-from app.model.schemas.project_label_schemas import ProjectLabel
-from app.model.schemas.project_image_schemas import ProjectImgLeaferLabel, ProjectImagePager
 from app.model.bussiness_model import ProjectLabel as pl
+from app.model.schemas.project_label_schemas import ProjectLabel
+from app.model.schemas.project_info_schemas import ProjectInfoIn, ProjectInfoPager
+from app.model.schemas.project_image_schemas import ProjectImgLeaferLabel, ProjectImagePager
+from app.model.schemas.project_train_schemas import ProjectTrainIn
 from app.common.jwt_check import get_user_id
 from app.common import reponse_code as rc
 from app.service import project_train_service as ps
 from app.db.db_session import get_db
 
+import threading
+import asyncio
 from typing import List
 from fastapi import APIRouter, Depends, Request, UploadFile, File, Form
-from fastapi.responses import StreamingResponse
 from fastapi.encoders import jsonable_encoder
 from sqlalchemy.orm import Session
 
@@ -182,7 +184,7 @@ def get_image_list(image: ProjectImagePager, session: Session = Depends(get_db))
     :return:
     """
     if image.pagerNum is None and image.pagerSize is None:
-        image_list = pimc.get_image_list(image.project_id, session)
+        image_list = pimc.get_image_list(image.project_id, image.img_type, session)
         result = jsonable_encoder(image_list)
         return rc.response_success(data=result)
     else:
@@ -217,14 +219,15 @@ def get_img_leafer(image_id: int, session: Session = Depends(get_db)):
         return rc.response_success(data=img_leafer_out['leafer'])
 
 
-@project.get("/run_train/{project_id}")
+@project.post("/run_train")
-async def run_train(project_id: int, session: Session = Depends(get_db)):
+async def run_train(train_in: ProjectTrainIn, session: Session = Depends(get_db)):
     """
     执行项目训练方法
-    :param project_id:
+    :param train_in:
     :param session:
     :return:
     """
+    project_id = train_in.project_id
     project_info = pic.get_project_by_id(project_id, session)
     if project_info is None:
         return rc.response_error("项目查询错误")
@@ -240,10 +243,24 @@ async def run_train(project_id: int, session: Session = Depends(get_db)):
         return rc.response_error("请先上传验证图片")
     if val_img_count < 5:
         return rc.response_error("验证图片少于5张，请继续上传验证图片")
-    data, project_name, name = ps.run_train_yolo(project_info, session)
+    data, project, name = ps.run_train_yolo(project_info, train_in, session)
-    return StreamingResponse(
+    thread_train = threading.Thread(target=run_event_loop, args=(data, project, name, train_in,
-        ps.run_commend(data, project_name, name, 50, project_id, session),
+                                    project_id, session,))
-        media_type="text/plain")
+    thread_train.start();
+    return rc.response_success(msg="执行成功")
+
+
+def run_event_loop(data: str, project: str,
+                name: str, train_in: ProjectTrainIn,
+                project_id: int, session: Session):
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    # 运行异步函数
+    loop.run_until_complete(ps.run_commend(data, project, name, train_in.epochs,
+                                    train_in.patience, train_in.weights_id,
+                                    project_id, session))
+    # 可选: 关闭循环
+    loop.close()
 
 
 @project.get("/get_train_list/{project_id}")

app/api/business/websocket_api.py

@@ -1,4 +1,5 @@
 from fastapi import APIRouter, WebSocket
+from starlette.websockets import WebSocketState
 
 from app.websocket.web_socket_server import room_manager
 
@@ -19,9 +20,11 @@ async def websocket_room(websocket: WebSocket, room: str):
     try:
         while True:
             data = await websocket.receive_text()
-            await room_manager.broadcast_to_room(room, data, exclude_websocket=websocket)
+            room_manager.broadcast_to_room(room, data, exclude_websocket=websocket)
     except Exception as e:
-        print(f"连接关闭: {e}")
+        if websocket.client_state != WebSocketState.DISCONNECTED:
+            await websocket.close(code=1000)
     finally:
         await room_manager.remove_from_room(room, websocket)
-        await websocket.close()
+        if websocket.client_state != WebSocketState.DISCONNECTED:
+            await websocket.close(code=1001)

app/application/app.py

@@ -44,17 +44,17 @@ my_app.include_router(web_socket, prefix="/ws", tags=["websocket管理"])
 
 
 # fastapi定时执行任务
-async def periodic_task():
+async def serve_info_task():
     while True:
         server_json = get_server_json()
         await room_manager.send_to_room('server-info', server_json)
-        await asyncio.sleep(2)  # 每 10 秒执行
+        await asyncio.sleep(5)  # 每 5 秒执行
 
 
 @my_app.on_event("startup")
 async def start_periodic_task():
     # 在后台启动异步任务
-    asyncio.create_task(periodic_task())
+    asyncio.create_task(serve_info_task())
 
 
 

app/common/reponse_code.py

@@ -3,7 +3,7 @@ from fastapi import status
 from app.db.page_util import Pager
 
 
-def response_code_view(code: int,msg: str) -> Response:
+def response_code_view(code: int, msg: str) -> Response:
     return JSONResponse(
         status_code=code,
         content={

app/model/bussiness_model.py

@@ -81,6 +81,10 @@ class ProjectTrain(DbCommon):
     __tablename__ = "project_train"
     project_id: Mapped[int] = mapped_column(Integer, nullable=False)
     train_version: Mapped[str] = mapped_column(String(32), nullable=False)
+    weights_id: Mapped[int] = mapped_column(Integer)
+    weights_name: Mapped[str] = mapped_column(String(32))
+    epochs: Mapped[int] = mapped_column(Integer)
+    patience: Mapped[int] = mapped_column(Integer)
     best_pt: Mapped[str] = mapped_column(String(255), nullable=False)
     last_pt: Mapped[str] = mapped_column(String(255), nullable=False)
 

app/model/schemas/project_train_schemas.py

@@ -3,10 +3,20 @@ from pydantic import BaseModel, Field
 from typing import Optional
 
 
+class ProjectTrainIn(BaseModel):
+    project_id: Optional[int] = Field(..., description="项目id")
+    weights_id: Optional[int] = Field(None, description="权重文件")
+    epochs: Optional[int] = Field(50, description="训练轮数")
+    patience: Optional[int] = Field(20, description="早停的耐心值")
+
+
 class ProjectTrainOut(BaseModel):
     """项目训练版本信息表"""
     id: Optional[int] = Field(None, description="训练id")
     train_version: Optional[str] = Field(None, description="训练版本号")
+    weights_name: Optional[str] = Field(None, description="权重名称")
+    epochs: Optional[int] = Field(None, description="训练轮数")
+    patience: Optional[int] = Field(None, description="早停的耐心值")
     create_time: Optional[datetime] = Field(None, description="训练时间")
 
     class Config:

app/service/project_train_service.py

@@ -1,6 +1,7 @@
 from app.model.bussiness_model import ProjectImage, ProjectInfo, ProjectImgLeafer, ProjectImgLabel, ProjectTrain
 from app.model.schemas.project_info_schemas import ProjectInfoIn, ProjectInfoOut
 from app.model.schemas.project_image_schemas import ProjectImgLeaferLabel, ProjectImgLeaferOut
+from app.model.schemas.project_train_schemas import ProjectTrainIn
 from app.model.crud import project_info_crud as pic
 from app.model.crud import project_image_crud as pimc
 from app.model.crud import project_label_crud as plc
@@ -9,12 +10,14 @@ from app.model.crud import project_img_leafer_label_crud as pillc
 from app.util import os_utils as os
 from app.util import random_utils as ru
 from app.config.config_reader import datasets_url, runs_url, images_url, yolo_url
+from app.websocket.web_socket_server import room_manager
 
 from sqlalchemy.orm import Session
 from typing import List
 from fastapi import UploadFile
 import yaml
 import subprocess
+import asyncio
 
 
 def add_project(info: ProjectInfoIn, session: Session, user_id: int):
@@ -119,9 +122,10 @@ def get_img_leafer(image_id: int, session: Session):
     return img_leafer_out
 
 
-def run_train_yolo(project_info: ProjectInfoOut, session: Session):
+def run_train_yolo(project_info: ProjectInfoOut, train_in: ProjectTrainIn, session: Session):
     """
     yolov5执行训练任务
+    :param train_in: 训练参数
     :param project_info: 项目信息
     :param session: 数据库session
     :return:
@@ -168,29 +172,44 @@ def run_train_yolo(project_info: ProjectInfoOut, session: Session):
     # 打包完成开始训练，训练前，更改项目的训练状态
     pic.update_project_status(project_info.id, '1', session)
 
-    # 开始训练
+    # 开始执行异步训练
     data = yaml_file
-    project = os.file_path(runs_url, project_info.project_no, 'train')
+    project = os.file_path(runs_url, project_info.project_no)
     name = version_path
-
+    # thread_train = threading.Thread(target=ps.run_commend, args=(data, project, name, train_in.epochs,
+    #                                 train_in.patience, train_in.weights_id,
+    #                                 train_in.project_id, session,))
+    # thread_train.start();
     return data, project, name
 
 
-def run_commend(data: str, project: str,
+async def run_commend(data: str, project: str,
-                name: str, epochs: int,
+                name: str, epochs: int, patience: int, weights: str,
                 project_id: int, session: Session):
+    """
+    执行训练
+    :param data: 训练数据集
+    :param project: 训练结果的项目目录
+    :param name: 实验名称
+    :param epochs: 训练轮数
+    :param patience: 早停耐心值
+    :param weights: 权重文件
+    :param project_id: 项目id
+    :param session:
+    :return:
+    """
     yolo_path = os.file_path(yolo_url, 'train.py')
-
+    room = 'train_' + str(project_id)
-    yield f"stdout: 模型训练开始，请稍等。。。\n"
+    await room_manager.send_to_room(room, f"stdout: 模型训练开始，请稍等。。。\n")
+    commend = ["python", '-u', yolo_path, "--data=" + data, "--project=" + project, "--name=" + name,
+               "--epochs=" + str(epochs), "--batch-size=4", "--exist-ok", "--patience=" + str(patience)]
+    if weights != None and weights != '':
+        train_info = ptc.get_train(weights, session)
+        if train_info != None:
+            commend.append("--weights=" + train_info.best_pt)
     # 启动子进程
     with subprocess.Popen(
-            ["python", '-u', yolo_path,
+            commend,
-             "--data=" + data,
-             "--project=" + project,
-             "--name=" + name,
-             "--epochs=" + str(epochs),
-             "--batch-size=4",
-             "--exist-ok"],
             bufsize=1,  # bufsize=0时，为不缓存；bufsize=1时，按行缓存；bufsize为其他正整数时，为按照近似该正整数的字节数缓存
             shell=False,
             stdout=subprocess.PIPE,
@@ -202,13 +221,14 @@ def run_commend(data: str, project: str,
             line = process.stdout.readline()
             process.stdout.flush()  # 刷新缓存，防止缓存过多造成卡死
             if line != '\n':
-                yield line
+                await room_manager.send_to_room(room, line)
 
         # 等待进程结束并获取返回码
         return_code = process.wait()
         if return_code != 0:
             pic.update_project_status(project_id, '-1', session)
         else:
+            await room_manager.send_to_room(room, 'success')
             pic.update_project_status(project_id, '2', session)
             # 然后保存版本训练信息
             train = ProjectTrain()
@@ -218,6 +238,11 @@ def run_commend(data: str, project: str,
             last_pt_path = os.file_path(project, name, 'weights', 'last.pt')
             train.best_pt = bast_pt_path
             train.last_pt = last_pt_path
+            if weights != None and weights != '':
+                train.weights_id = weights
+                train.weights_name = train_info.train_version
+            train.patience = patience
+            train.epochs = epochs
             ptc.add_train(train, session)
 
 

app/util/ps_util.py

@@ -2,6 +2,7 @@ import psutil
 import platform
 import json
 from datetime import datetime
+# 获取服务器运行状态
 
 
 def get_server_info():

requirements.txt

@@ -10,6 +10,7 @@ python-multipart==0.0.5
 redis~=4.1.4
 SQLAlchemy~=2.0.34
 uvicorn~=0.17.5
+uvicorn[standard]
 loguru~=0.6.0
 xlrd~=2.0.1
 bcrypt==3.2.0