jopo666 / histoprep Goto Github PK

Hi!

Thank you for providing HistoPrep to the community.

I'm running trying to run the functions in the Readme page, using the following H2_1.jpg that can be downloaded here: https://data.mendeley.com/datasets/svw96g68dv/4.

I encounter the following error:

reader.get_tissue_mask(level=-1)
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Input In [22], in <cell line: 1>()
----> 1 reader.get_tissue_mask(level=-1)

AttributeError: 'SlideReader' object has no attribute 'get_tissue_mask'

Windows 11 Home, 64 bit, Anaconda Python, running in a Jupter notebook.

Happy to provide more details if needed, would love to be able to run HistoPrep on some images!

Hi there! I was trying to open a histology WSI in .tif and bumped into the following error:

File ~/.local/lib/python3.11/site-packages/histoprep/_backend.py:235 in init
self.__reader = openslide.OpenSlide(path)

AttributeError: module 'openslide' has no attribute 'OpenSlide'

I wonder if you have any thoughts or suggestions to fix this bug? I had both libraries, openslide and openslide_python (v 1.3.1), installed on Linux.

Thank you!

A class for easily adding labels for tiles would be awesome! Something like

metadata = histoprep.Labeler(metadata, prefix='cancer', mask=mask)

Hello,
Thank you for this nice package !

I used histoprep on two slides with different resolutions.
One was scanned at a mpp of 0.25, the other one with a mpp of 0.5. It seems that when extracting the tiles with the following code, it reads images of size 512x512 at the lowest openslide level, without taking in account the resolution. This implies that the cell scale etc.. differs between the images extracted on the two different slides (see images below, first is mpp 0.25, second is mpp 0.5).

from histoprep import SlideReader

# Read slide image.
reader = SlideReader("./slides/slide_with_ink.jpeg")
# Detect tissue.
threshold, tissue_mask = reader.get_tissue_mask(level=-1)
# Extract overlapping tile coordinates with less than 50% background.
tile_coordinates = reader.get_tile_coordinates(
    tissue_mask, width=512, overlap=0.5, max_background=0.5
)
# Save tile images with image metrics for preprocessing.
tile_metadata = reader.save_regions(
    "./train_tiles/", tile_coordinates, threshold=threshold, save_metrics=True
)

Is this an intended behaviour or am I missing something?
Best