Closed fazlicodes closed 1 year ago
We specified the process on the public datasets in our paper (page9 - Public Data Usage).
For clarification, let me elaborate some more details:
bacteria
, worms
, ... . We selected the subdirectories with name bacteria
and worms
. grayscale_array = (original_array[:, :, 0] + original_array[:, :, 1]) / 2
We did not use specific processing code to process public data.
Noted, thank you for your quick response!
@Lee-Gihun how did you locate and exclude the non-microscopy images in the cellpose dataset?
We manually removed few obvious images from the set (about 10~20 images).
To best my understanding, the original Cellpose paper, they regard the cell segmentation problem as finding the unit entities in the images. Though, they did not mentioned such details in their paper.
At first, I thought it potentially hurts the performance so I removed them. But there was no noticeable difference. This might be the images in the cellpose is only a small portion in our entire pretraining set, and the testing modalities in the challenge datasets does not contain such non-cell entities in the image.
Hi, there are no codes given to process the public datasets, and what are the discarded data from each of the public dataset.