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PREPROCESSING OF CAMELYON16 DATASET USING CLAM #21
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is this the correct command to get patch level 1(20x) .h5 coordinates?: similarly i am just using patch level 2 and 3. and at patch level 3 each iamge has just 113 patches |
I see... I might have used the combination 0,1,2 instead of 1,2,3. To resolve this doubt, we can visually compare the patches I have with those you have. The cell nucleus (the black dots so to speak) are typically all the same size (30-50 nm). So just compare whether the space they occupy is similar or not. |
yes the patches seems to be of similar scale but my initial patch are different from these. there might be some other issue. One more thing to note that i think CLAM repo is updated with a slightly different dataset_h5.py code. so i have used the new code to extract h5 cordinates but an older repo which matches your code for convert_h5_to_jpg.py ro convert .h5 coordinates into jpg. they have changed the code for Whole_Slide_Bag_FP class in dataset_h5.py. can u look into it. |
Hin @routsourav1729, I have checked the current implementation of CLAM, but nothing unusual is happening. Could you tell me the commit of CLAM where it worked? In that case, I would refer to it in the readme |
Hi, i was trying to reproduce the results u have shown with CAMELYON 16 dataset. i have used the configuration u have provided in 0-extract_patches to run with create_pathes_fp.py
but i am getting around 1200 patches at level 1 compared to 5771 reported in the paper. and similarly for level 2 i got 400 images compared to 1528 as mentioned in paper. am i doing something wrong? do i need to change he config file?
also i think the CLAM repo is modified so i am getting some error while using convert_h5_to_jpg.py with CLAM. can u look into that and help me?
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