Hi, Joy Hsu, thanks for the interesting paper and open sourcing the code here. I'm trying to reproduce the code to understand more details. But I have some questions I would like your help with:
I saw how to use DARCNN at "darcnn_code/tutorial.ipynb" and the task demonstrated is the adaptation from coco to BBBC, right?
If I want to try adaptation from BBBC to Kumar, then in the first stage I need to load BBBC dataset and Kumar, and in the second stage only Kumar, right?
When adaptating from BBBC to Kumar, can I still use the pre-trained weights 'coco_class_agnostic_maskrcnn.pth' in the first stage? If not, what should be done here?
I downloaded the bbbc_10k_256.zip that you shared, is this data already done with all preprocessing including inversion?
If I have misunderstood, I would appreciate your clearer guidance!
Hi, Joy Hsu, Regarding kumar's data preprocessing, are there 10,000 randomly cropped patches from the official 16 training images? Is there any other data augmentation done?
Hi, Joy Hsu, thanks for the interesting paper and open sourcing the code here. I'm trying to reproduce the code to understand more details. But I have some questions I would like your help with: