优化训练过程

app/service/project_detect_service.py

@@ -161,7 +161,7 @@ async def run_detect_img(weights: str, source: str, project: str, name: str, log
     yolo_path = os.file_path(yolo_url, 'detect.py')
     room = 'detect_' + str(detect_id)
     await room_manager.send_to_room(room, f"AiCheck: 模型训练开始，请稍等。。。\n")
-    commend = ["python", '-u', yolo_path, "--weights", weights, "--source", source, "--name", name, "--project", project, "--save-txt"]
+    commend = ["python", '-u', yolo_path, "--weights", weights, "--source", source, "--name", name, "--project", project, "--save-txt", "--conf-thres", "0.4"]
     is_gpu = redis_conn.get('is_gpu')
     # 判断是否存在cuda版本
     if is_gpu == 'True':
@@ -259,7 +259,7 @@ async def run_detect_rtsp(weights_pt: str, rtsp_url: str, data: str, detect_id:
                     pred = model(im, augment=False, visualize=False)
             # NMS
             with dt[2]:
-                pred = non_max_suppression(pred, 0.25, 0.45, None, False, max_det=1000)
+                pred = non_max_suppression(pred, 0.45, 0.45, None, False, max_det=1000)
 
             # Process predictions
             for i, det in enumerate(pred):  # per image

app/service/project_train_service.py

@@ -14,12 +14,11 @@ from app.websocket.web_socket_server import room_manager
 from app.util.csv_utils import read_csv
 from app.common.redis_cli import redis_conn
 
-from sqlalchemy.orm import Session
-from typing import List
-from fastapi import UploadFile
 import yaml
 import subprocess
-import torch
+from typing import List
+from fastapi import UploadFile
+from sqlalchemy.orm import Session
 
 
 def add_project(info: ProjectInfoIn, session: Session, user_id: int):

app/util/yolov5/utils/general.py

@@ -513,7 +513,7 @@ def check_font(font=FONT, progress=False):
     font = Path(font)
     file = CONFIG_DIR / font.name
     if not font.exists() and not file.exists():
-        url = f"https://github.com/ultralytics/assets/releases/download/v0.0.0/{font.name}"
+        url = f"https://ultralytics.com/assets/{font.name}"
         LOGGER.info(f"Downloading {url} to {file}...")
         torch.hub.download_url_to_file(url, str(file), progress=progress)
 

requirements_gpu.txt

@@ -31,11 +31,11 @@ PyYAML>=5.3.1
 requests>=2.32.2
 scipy==1.13.1
 thop>=0.1.1  # FLOPs computation
-torch==2.3.1+cu121 --extra-index-url https://mirrors.aliyun.com/pytorch-wheels/cu121/
-torchvision==0.18.1+cu121 --extra-index-url https://mirrors.aliyun.com/pytorch-wheels/cu121/
+# torch==2.6.0+cu124 # 本地安装
+# torchvision==0.21.0+cu124 # 本地安装
 tqdm>=4.66.3
 ultralytics==8.3.75  # https://ultralytics.com
 
 # Plotting --------------------------------------------------------------------
 pandas==2.2.3
-seaborn==0.11.0 # 对应的这个依赖也需要降
+seaborn==0.11.2 # 对应的这个依赖也需要降

toch_test.py

@@ -0,0 +1,5 @@
+import torch
+
+is_gpu = torch.cuda.is_available()
+
+print(str(is_gpu))

yolov5/train.py

@@ -409,7 +409,7 @@ def train(hyp, opt, device, callbacks):
                     imgs = nn.functional.interpolate(imgs, size=ns, mode="bilinear", align_corners=False)
 
             # Forward
-            with torch.cuda.amp.autocast(amp):
+            with torch.amp.autocast(device_type='cuda', enabled=amp):
                 pred = model(imgs)  # forward
                 loss, loss_items = compute_loss(pred, targets.to(device))  # loss scaled by batch_size
                 if RANK != -1:

yolov5/utils/general.py

@@ -513,7 +513,7 @@ def check_font(font=FONT, progress=False):
     font = Path(font)
     file = CONFIG_DIR / font.name
     if not font.exists() and not file.exists():
-        url = f"https://github.com/ultralytics/assets/releases/download/v0.0.0/{font.name}"
+        url = f"https://ultralytics.com/assets/{font.name}"
         LOGGER.info(f"Downloading {url} to {file}...")
         torch.hub.download_url_to_file(url, str(file), progress=progress)