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Hello, https://github.com/zbwxp/SegVit/blob/85616388cd8983e2d4daafd971540b210e956666/configs/_base_/models/seg_vit-b16.py#L24C9-L24C23
I found that you set with_cls_token=False. Is this means that ViT encoder in your model do not use class token, and use it for the decoder(ATM)?
The text was updated successfully, but these errors were encountered:
We used the feature embedding from the VIT encoder without using the class token. Alternatively, we initialized a class embedding in the decoder in
SegVit/decode_heads/atm_head.py
Lines 239 to 240 in 8561638
Sorry, something went wrong.
We used the feature embedding from the VIT encoder without using the class token. Alternatively, we initialized a class embedding in the decoder in SegVit/decode_heads/atm_head.py Lines 239 to 240 in 8561638 outputs_class = self.class_embed(qs) out = {"pred_logits": outputs_class[-1]}
Thank you for the reply! By the way, I was wonder when the SegViT2 especially Continual Learning part will be released.
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Hello,
https://github.com/zbwxp/SegVit/blob/85616388cd8983e2d4daafd971540b210e956666/configs/_base_/models/seg_vit-b16.py#L24C9-L24C23
I found that you set
with_cls_token=False.
Is this means that ViT encoder in your model do not use class token, and use it for the decoder(ATM)?
The text was updated successfully, but these errors were encountered: