Comments (4)
Hello,
Thanks for your interest in our package! Could you please indicate the format of your data? Is it tiff image?
If it is okay, could you please share an image with me so that I can find where the problem is?
Best regards
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Hey @PENGLU-WashU! Thank you for your response! Yes they are tiff images that are 1024x1024, and here is also the notebook I used to debug it to this line of code within generate_patches function: patch_collect_sub = self.extract_patches_from_img(Img_DIMR, Row_range, Col_range)
And I have attached 1 FOV as well, thank you so much and looking forward to your reply.
2022-12-03T15-18-19_BIGFISH1_pA_s1_R1C1.zip
IMC_Denoise_Train_and_Predict_MIBIexample.html.zip
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Hello! I just checked the images. Are these images the raw files? The images should be denoised before normalization. In that case, the range of the images is beyond [0,1]. Hope these can help.
from imc_denoise.
Hey @PENGLU-WashU ah that's totally fair, it works on raw data! Sorry for my confusion and thank you for your help!
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Related Issues (19)
- Image format HOT 5
- Val_loss HOT 4
- Updating tensorflow, cudnn and cudatoolkit HOT 1
- IMC_Denoise on M1 Mac HOT 3
- Logics behind data preprocessing HOT 2
- Isotype not found HOT 5
- Demo training data generates NaN for loss HOT 21
- Softplus activation function compatible for subsequent data normalisation? HOT 2
- Demo data produces NaN loss on multiple systems HOT 5
- IMC Denoising is too aggresive for certain channels HOT 9
- multi markers training HOT 2
- About the issue of GPU usage efficiency HOT 3
- Percentage of masked pixels HOT 4
- running DIMR and DeepSNiF together in the tutorial HOT 1
- Question about how to train DeepSNiF properly & integration with steinbock HOT 24
- Problems running on GPU (NVIDIA A40) HOT 7
- Edge case in training batch generation
- N2V2
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