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SamSweere / xmm-superres-denoise

Deep Learning-Based Super-Resolution and De-Noising for XMM-Newton Images.
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About how to generate those model input data? #24

Closed leungzzz closed 3 weeks ago

leungzzz commented 4 weeks ago

I had downloaded those data from hugging face. then next, how can i use these current ".fit" format datas to generate the train/test/val data?

bojobo commented 3 weeks ago

Hi!

I'm currently really busy with another part of my thesis. As soon as I have that running I'll get back to you.

leungzzz commented 3 weeks ago

Hi!

I'm currently really busy with another part of my thesis. As soon as I have that running I'll get back to you.

thanks a lot! By the way, a little update have done in README.md file ( Inference part )?, the mentioned inference_example.ipynb & xmm_superres_denoise/inference.py, could not to find in this project ...

leungzzz commented 3 weeks ago

Hi! I'm currently really busy with another part of my thesis. As soon as I have that running I'll get back to you.

thanks a lot! By the way, a little update have done in README.md file ( Inference part )?, the mentioned inference_example.ipynb & xmm_superres_denoise/inference.py, could not to find in this project ...

Hi! I'm currently really busy with another part of my thesis. As soon as I have that running I'll get back to you.

thanks a lot! By the way, a little update have done in README.md file ( Inference part )?, the mentioned inference_example.ipynb & xmm_superres_denoise/inference.py, could not to find in this project ...

I was careless, got the answer in branch xmmsr_ivan .