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I was looking through the code but couldn't figure out what "scribble" indicates.
From dataloaders/customized.py
Line 103
support_scribbles = [[paired_sample[cumsum_idx[i] + j]['scribble'] for j in range(n_shots)]
for i in range(n_ways)]
Could you clarify what the support_scribbles mean? Also, what is "image_t"
From dataloaders/customized.py
Line 93
support_images_t = [[paired_sample[cumsum_idx[i] + j]['image_t'] for j in range(n_shots)]
for i in range(n_ways)]
Is it the segmentation target mask of the given image? While, label indicates the class_index of the mask?
Thanks in advance,
The text was updated successfully, but these errors were encountered:
Hi @dbjhbyun, scribble refers to the scribble annotations mentioned in Section 4.4 of our paper.
I must apologize for the confusing variable name image_t. I use it to denote the images after transformation (flip or resize) but before Pytorch's toTensor (which scales and normalizes the input with ImageNet mean and std). They are useful when you want to manually check the images or do some visualization.
Hi,
I was looking through the code but couldn't figure out what "scribble" indicates.
From dataloaders/customized.py
Line 103
support_scribbles = [[paired_sample[cumsum_idx[i] + j]['scribble'] for j in range(n_shots)]
for i in range(n_ways)]
Could you clarify what the support_scribbles mean? Also, what is "image_t"
From dataloaders/customized.py
Line 93
support_images_t = [[paired_sample[cumsum_idx[i] + j]['image_t'] for j in range(n_shots)]
for i in range(n_ways)]
Is it the segmentation target mask of the given image? While, label indicates the class_index of the mask?
Thanks in advance,
The text was updated successfully, but these errors were encountered: