sun15684712291/aicheckv2
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修改一些小问题

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sunyg
2025-06-05 08:45:44 +08:00
parent f32cd5b9a2
commit 0cd3d914e9
7 changed files with 31 additions and 84 deletions
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27
app/service/project_detect_service.py
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@ -54,7 +54,7 @@ def del_detect(detect_id: int, session: Session):
detect_logs = pdc.get_logs(detect_id, session)
for log in detect_logs:
folder_url.append(log.detect_folder_url)
os.create_folder(folder_url)
os.delete_paths(folder_url)
session.commit()
@ -168,7 +168,7 @@ async def run_detect_img(weights: str, source: str, project: str, name: str, log
is_gpu = redis_conn.get('is_gpu')
# 判断是否存在cuda版本
if is_gpu == 'True':
commend.append("--device", "0")
commend.append("--device=0")
# 启动子进程
with subprocess.Popen(
commend,
@ -225,12 +225,12 @@ async def run_detect_rtsp(weights_pt: str, rtsp_url: str, data: str, detect_id:
model = DetectMultiBackend(weights_pt, device=device, dnn=False, data=data, fp16=False)
stride, names, pt = model.stride, model.names, model.pt
imgsz = check_img_size((640, 640), s=stride) # check image size
img_sz = check_img_size((640, 640), s=stride) # check image size
dataset = LoadStreams(rtsp_url, img_size=imgsz, stride=stride, auto=pt, vid_stride=1)
dataset = LoadStreams(rtsp_url, img_size=img_sz, stride=stride, auto=pt, vid_stride=1)
bs = len(dataset)
model.warmup(imgsz=(1 if pt or model.triton else bs, 3, *imgsz))
model.warmup(imgsz=(1 if pt or model.triton else bs, 3, *img_sz))
seen, windows, dt = 0, [], (Profile(device=device), Profile(device=device), Profile(device=device))
@ -244,22 +244,11 @@ async def run_detect_rtsp(weights_pt: str, rtsp_url: str, data: str, detect_id:
im /= 255 # 0 - 255 to 0.0 - 1.0
if len(im.shape) == 3:
im = im[None] # expand for batch dim
if model.xml and im.shape[0] > 1:
ims = torch.chunk(im, im.shape[0], 0)
# Inference
with dt[1]:
if model.xml and im.shape[0] > 1:
pred = None
for image in ims:
if pred is None:
pred = model(image, augment=False, visualize=False).unsqueeze(0)
else:
pred = torch.cat((pred, model(image, augment=False, visualize=False).unsqueeze(0)),
dim=0)
pred = [pred, None]
else:
pred = model(im, augment=False, visualize=False)
pred = model(im, augment=False, visualize=False)
# NMS
with dt[2]:
pred = non_max_suppression(pred, 0.45, 0.45, None, False, max_det=1000)
@ -286,5 +275,5 @@ async def run_detect_rtsp(weights_pt: str, rtsp_url: str, data: str, detect_id:
frame_data = jpeg.tobytes()
await room_manager.send_stream_to_room(room, frame_data)
else:
print(room, '结束推理');
print(room, '结束推理')
break