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License: Other
Workflow for Simulation and Automatic Semantic Segmentation of Electron Microscopy Images
License: Other
Hello sir,
I am getting a data type error while using UNet_Segmentation.py.
In line number 258:
weights = (y_true *( weighting - 1)) + 1
TypeError: Expected uint8 passed to parameter 'y' of op 'Mul', got float instead.
Regards,
Shailendra
Hi, I am trying to reproduce your experiment. I directly use the images and masks in your Archive/Automatic_SEM_Image_Segmentation
directory. The environment and dependence is exactly the one listed in Releases/Version 1.1.1/requirements.txt
. I use NVIDIA GeForce RTX 4090. However I met the error in the title in the second step "Simulating fake masks" when running python3 StartProcess.py
. I tried using tensforflow 2.8 as suggested here however the issue still exists. Do you have any ideas how to fix it? Many thanks!
Ladies and Gentlemen,
thank you for sharing this very interesting work. I'm not a specialist in neural networks but anyway very interested in trying to apply your method.
I updated and installed all required packeges, using pip(3) and python 3.9.5. However, using the example from the folder "Archive/Automatic_SEM_Image_Segmentation' I'm getting the error:
File "C:\Users***\Desktop\automatic-sem-image-segmentation-master\Archive\Automatic_SEM_Image_Segmentation\startProcess.py", line 347, in
imgTiles = imgTiles.reshape([imgTiles.shape[0], imgTiles.shape[1], imgTiles.shape[2], 1]) / 255.0
IndexError: tuple index out of range
As the template is used right as is I can not figure out what's causing the problem here. Any suggestion is very welcome, thank you in advance!
Hello sir/Ma`am,
Thank you for sharing the important code for scientific research.
I have 21 images with size 1280 x 960 pixels and 13 sample masks with size 64 x 64 pixels. I installed all the dependencies as specified in the 'requirements.txt' file. However, when I run the most recent program, I got the following error message:
File “WassersteinGAN.py”, line 207, in init
self.train_images = (self.train_images.reshape((self.train_images.shape[0], 64, 64, 1)).astype(“float32”) – 127.5)/127.5
ValueError: cannot reshape array of size 851968 into shape (52,64,64,1)
Please let me know if I can fix the above error.
Regards,
Shailendra Kumar Verma
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