Comments (5)
Thank you for the feedback @matthiasgeihs! I will try to improve the readme to include explanations for what each snippet is doing. This is a good idea 🙂
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Hi @matthiasgeihs, thanks for pointing out this issue. I will fix it ASAP and roll out a new version.
It might also contain some other interface changes, about which I will inform you after the update has been released.
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Hi @matthiasgeihs. I have fixed the error you were facing.
You can install the latest dev version of torch-dreams with this command:
pip install git+https://github.com/Mayukhdeb/torch-dreams
Please note that I've also been working on a new upgrade to torch-dreams which involves batched image parameters. Hence there is a small interface change that you have to make on your custom objectives:
I have also updated the colab notebook to use the dev version for now. So it should run through without any problems.
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Great, thanks for taking a look. Will try that out when I find some time. 🙏
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OK, this works now. 👍
@Mayukhdeb
What would be very helpful for someone like me who is not already familiar with the method:
Have some explanations between the commands in the notebook, what exactly is happening there.
I got aware of the project as I was interested in explainable AI, but what I currently see is just some nice looking pictures being produced. I have a very rough idea of what might be happening under the hood, but tbh I don't understand much at the moment. What is the minimal example exactly demonstrating? I think a few high-level comments would really help! 🙂
That being said, the issue seems solved.
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Related Issues (20)
- extra tools for torch-dreams
- static caricatures
- RuntimeError randomly when static = True on caricatures
- init custom_image_param from nchw tensor
- update args for custom_image_param initialization
- add support for n channel image parameters
- masked image params HOT 1
- add support for models on any image normalization HOT 1
- cannot change self.__custom_normalization_transform__ after calling set_custom_normalization() once
- revamp custom_func args
- caricatures dont consider set_custom_transforms()
- Support for latest pytorch 1.9 HOT 3
- layers_to_use should be a dict, not a list
- add gradcam, but for custom_func methods and not just output classes
- add support for noisegrad HOT 2
- v3.0
- confusion about visualizing individual channels HOT 2
- get rid of opencv
- Implement Magnitude Constrained Optimization (MaCo)
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