-
Notifications
You must be signed in to change notification settings - Fork 459
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
加载自定义模型闪退 #9
Comments
您好,配置文件参数有误, |
这里有些区别 |
@Yuko1997 您好,这边复现了下发现是 onnx 与 opencv 和 torch 版本的兼容问题,请确保 torch <= 1.11,并修改 opset 版本(默认是 14): # pip install ultralytics
from ultralytics import YOLO
model = YOLO("yolov8n.yaml") # build a new model from scratch
model = YOLO("yolov8n.pt") # load a pretrained model (recommended for training)
path = model.export(format="onnx", opset=12) # export the model to ONNX format 测试版本为:torch==1.11.0 | opencv-python==4.6.0.66 | onnx==1.12.0 后续会对多版本做兼容,敬请留意,再次感谢您的关注与支持。 |
没有任何报错或提示,程序直接退出
type: test
name: testA
display_name: Test
model_path: D:/Auto/best.onnx
input_width: 640
input_height: 640
score_threshold: 0.45
classes:
The text was updated successfully, but these errors were encountered: