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I am wondering if you can help me. Trying to understand how your tissue locator works. It looks like the locate_tissue_cnts function returns a list of coordinates for the various detected tissue region and the down-sampling level which is clear.
For your test image, the function returns 3 regions. How do you plot these coordinates? Do you have any pointers how i can overlay the coordinates on the image to check the accuracy?
I ran your function on one of my test images and I got 16 tissue regions. I am trying to figure out how to plot these coordinates.
Thank you kindly!
The text was updated successfully, but these errors were encountered:
Ok. I have made some progress since last night. I suppose i can create a zero numpy array that corresponds to the image dimensions, then load your region coordinates to create a mask using that zero array as a template or starting point. Close?
I also noticed that the 16 regions in my test images were mostly tiny areas that i want to discard, so by increasing the "min_tissue_size", i was able to get the regions I want. The next challenge is to automate this tissue size tweaking process for when i run this on my whole dataset which has a bout 50 slides.
@fgfmds Sorry for the late reply. Thanks for your interest in this repo. You might consider using cv2.drawContours to overlay the located contour over the image. This code gist can be taken as an example.
Hello,
I am wondering if you can help me. Trying to understand how your tissue locator works. It looks like the locate_tissue_cnts function returns a list of coordinates for the various detected tissue region and the down-sampling level which is clear.
For your test image, the function returns 3 regions. How do you plot these coordinates? Do you have any pointers how i can overlay the coordinates on the image to check the accuracy?
I ran your function on one of my test images and I got 16 tissue regions. I am trying to figure out how to plot these coordinates.
Thank you kindly!
The text was updated successfully, but these errors were encountered: