[FEATURE] Stitching after making prediction

[CheLamVien]

Dear all,

I wanted to make a prediction on the 3D stack, and I found that the stitching method works better than do_3D. However, I would like to use a different diameter for different 2D slices. Is there any option to perform that?

A workaround could be to predict 2D images one by one with specified diameter and then stitch them. How can I do it using Cellpose?

At the top of the 3D stack, where the fluorescent intensity is dimmer, fewer pixels are expected to be detected as a mask. I re-trained the "cyto3" model using GUI, but it seems to me that the model doesn't take the intensity values into consideration. I guess that it's because of normalization. To make a prediction, I have tried:

masks_stitched, flows_stitched, styles_stitched = model.eval(imgs[0], 
                                                        diameter=150, channels=[0,0], do_3D=False, stitch_threshold=0.5,
                                                            normalize={"normalize": True, "norm3D": True} )

normalize=False gave a poor results.

I found that reducing the diameter could solve my problem. Thank you so much for your time. I would greatly appreciate any feedback on improving the model.

Best regards. Vien Che