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作者您好,感谢您的工作和开源的代码,我受益匪浅。 我有一个疑问,希望请教您一下:
根据train.py中的代码, mask_left = ((disp_left > 0) & (disp_left < 192)).float() mask_right = ((disp_right > 0) & (disp_right < 192)).float() 以及 loss_PAM_P = loss_pam_photometric(img_left, img_right, att, valid_mask, [mask_left, mask_right]) disp_left以及disp_right的信息被用在了训练过程中,这是否和无监督训练有所冲突呢?
mask_left = ((disp_left > 0) & (disp_left < 192)).float() mask_right = ((disp_right > 0) & (disp_right < 192)).float()
loss_PAM_P = loss_pam_photometric(img_left, img_right, att, valid_mask, [mask_left, mask_right])
The text was updated successfully, but these errors were encountered:
Hi, 请参考这条回复。
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谢谢!
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作者您好,感谢您的工作和开源的代码,我受益匪浅。
我有一个疑问,希望请教您一下:
根据train.py中的代码,
mask_left = ((disp_left > 0) & (disp_left < 192)).float() mask_right = ((disp_right > 0) & (disp_right < 192)).float()
以及
loss_PAM_P = loss_pam_photometric(img_left, img_right, att, valid_mask, [mask_left, mask_right])
disp_left以及disp_right的信息被用在了训练过程中,这是否和无监督训练有所冲突呢?
The text was updated successfully, but these errors were encountered: