vietanhdev / anylabeling

Effortless AI-assisted data labeling with AI support from YOLO, Segment Anything (SAM+SAM2), MobileSAM!!
https://anylabeling.nrl.ai
GNU General Public License v3.0
2.2k stars 236 forks source link

Run on CPU #62

Closed ZJZ0405 closed 1 year ago

ZJZ0405 commented 1 year ago

I get the following error when running in cpu environment. "[ WARN:0@14.885] global net_impl.cpp:174 setUpNet DNN module was not built with CUDA backend; switching to CPU"

vietanhdev commented 1 year ago

It is only a warning - does not cause any problem with your program.

ZJZ0405 commented 1 year ago

It is only a warning - does not cause any problem with your program.

I was able to open the program normally, but when I used autotagging, the program crashed.I use ubuntu-desktop-20.04 and it tells me "Segmentation fault".I don't know why this happened.

frankool commented 1 year ago

but with this GPU is running?

ZJZ0405 commented 1 year ago

but with this GPU is running?

I read the source code and found that there are judgments about GPU and CPU. If I don't use GPU-accelerated DNN, I can open the software's GUI normally, but when I use the "Auto Labeling" function, the software will crash during loading. Because of this troublesome error message "segmentation fault", I cannot solve this problem without reading the source code completely. However, the problem may also be caused by not using "conda" to build the environment.

vietanhdev commented 1 year ago

@ZJZ0405 Please try with the newest code from master or v0.2.14 to see if the "Segmentation fault" is still there.

ZJZ0405 commented 1 year ago

I still have the above problem. [Does your program support the function of inputting images with different sizes from those preset in ”yaml“?

vietanhdev commented 1 year ago

If your program runs without crashing, it's only a warning.

ZJZ0405 commented 1 year ago

@vietanhdev I found that I couldn’t add a custom model by changing the yaml after I upgraded to the new version. I plan to give up using it on the native system and switch to using it in the conda environment.