改进项目结构

app/service/project_detect_service.py

@@ -2,14 +2,12 @@ from sqlalchemy.orm import Session
 from typing import List
 from fastapi import UploadFile
 import subprocess
-from yolov5.models.common import DetectMultiBackend
-from yolov5.utils.torch_utils import select_device
-from yolov5.utils.dataloaders import LoadStreams
-from yolov5.utils.general import check_img_size, Profile, non_max_suppression, cv2, scale_boxes
 import torch
-from pathlib import Path
-from ultralytics.utils.plotting import Annotator, colors, save_one_box
-import platform
+from app.util.yolov5.models.common import DetectMultiBackend
+from app.util.yolov5.utils.torch_utils import select_device
+from app.util.yolov5.utils.dataloaders import LoadStreams
+from app.util.yolov5.utils.general import check_img_size, Profile, non_max_suppression, cv2, scale_boxes
+from ultralytics.utils.plotting import Annotator, colors
 
 from app.model.crud import project_detect_crud as pdc
 from app.model.schemas.project_detect_schemas import ProjectDetectIn, ProjectDetectOut, ProjectDetectLogIn
@@ -188,6 +186,8 @@ async def run_detect_rtsp(weights_pt: str, rtsp_url: str, data: str, detect_id:
     :param data: yaml文件
     :return:
     """
+    room = 'detect_rtsp_' + str(detect_id)
+    await room_manager.send_to_room(room, '开始推理rtsp视频流')
     # 选择设备（CPU 或 GPU）
     device = select_device('cpu')
 
@@ -247,7 +247,11 @@ async def run_detect_rtsp(weights_pt: str, rtsp_url: str, data: str, detect_id:
 
             # Stream results
             im0 = annotator.result()
-
+            # 将帧编码为 JPEG
+            ret, jpeg = cv2.imencode('.jpg', im0)
+            if ret:
+                frame_data = jpeg.tobytes()
+                await room_manager.send_stream_to_room(room, frame_data)