Comments (1)
I was working on this in the past but wasn't able to get the package working quite right for it. It's difficult to get it working for Linux specifically.
I'll come back to it at some point.
The issue is just that conversion from pytorch to ncnn isn't that simple, and the code that allows easy conversion isn't for python. So, the solution is to use temp files and the precompiled binaries (which is what cupscale does). The issue with this though is chainner supports more than just windows, which makes that kind of thing far more difficult thanks to all the varieties of Linux (and especially the pypi requirements to get a package published).
So, it'll be done at some point, but I don't know when.
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Related Issues (20)
- Errors during Onnx inference HOT 4
- ROCM AMD chainner requierment file HOT 4
- Converting ncnn and onnx model to a PyTorch model HOT 2
- when the "Conditional" node is used, the unused entry would be skipped
- BUG when trying to open the first image in a folder
- Add support for some models in fp16 mode
- Add additional save options for TIFF image format HOT 2
- An error occurred in a Upscale Face node HOT 7
- cli fetch timeout error, reversion of PR-1853 HOT 1
- blank screen when opening the program HOT 1
- NCNN but with really high memory usage.
- Confusing and very limited conditional nodes capability HOT 1
- Color and Luminance blending modes
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- [Question] May I get help with inpainting? HOT 1
- "Custom scale to longer side" functionality HOT 4
- I don't really know why this happens, tensor a (1460) must match the size of tensor b (1464) at non-singleton dimension 3 HOT 3
- List all special suggestion in node documentation
- Additional pytorch conversion support HOT 4
- Add optional second image input to "VIEW IMAGE" node and a slider for "before/after comparison HOT 1
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