Comments (4)
Yes, I am still working on it.
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Release 1.3 now supports execution using CUDA.
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do we need to re-export the onnx models to CUDA? how?
from segment-anything-cpp-wrapper.
No need to re-export. But using CUDA did not provide a significant improvement in efficiency (only about 4 times faster on my computer).
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Related Issues (20)
- if change cuda ,loading model is fail,what's wrong? HOT 4
- Questions about the speed at which the model runs HOT 2
- help!!! I use it as this,but get error:not enough space: expected 4194304, got 0. My memory is enough.What's wrong? HOT 3
- can run in cpu? HOT 1
- How to change the image size, still only 1024x720? HOT 2
- Could you make stable-diffusion-onnx-cpp-wrapper.exe, please? HOT 4
- Why I don't get as good results as you do in the python environment, I'm curious to know how you did it and what tips you have. HOT 2
- mask has Y offset, why cause that ? HOT 4
- 'SamPredictor' object has no attribute 'interm_features' HOT 1
- cuda mode problem HOT 1
- opencv2/opencv.hpp: No such file or directory HOT 1
- What should I do if the input size of the modified image is 640x480, and the obtained mask cannot coincide with the original image? HOT 3
- Image input 320x240 HOT 1
- Support EdgeSam HOT 2
- Support for Text Prompt HOT 2
- export_pre_model.py is not working anymore HOT 3
- can not find mobile_sam when using import mobile_sam as SAM in export_pre_model.py
- efficeientsam support HOT 1
- It takes a long time to run "sam.loadimage" ,How to reduce running time? HOT 1
- loadImage HOT 1
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