You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
I wonder why we need do it?Flip image is some kind like data argument? if self.set_name=='train' and np.random.random(1)>0.5: image1 = image1.transpose(PIL.Image.FLIP_TOP_BOTTOM) image2 = image2.transpose(PIL.Image.FLIP_TOP_BOTTOM) if self.set_name=='train' and np.random.random(1)>0.5: image1 = image1.transpose(PIL.Image.FLIP_LEFT_RIGHT) image2 = image2.transpose(PIL.Image.FLIP_LEFT_RIGHT)
Yes. It is for augmenting training data. As mgPFF is a low-level vision
method, meaning that it does not need to understand high-level semantics,
such flip and flop augmentation can be applied here. But it is optional
when you have enough training data.
On Sun, Apr 28, 2019 at 7:53 PM zlw21gxy ***@***.***> wrote:
I wonder why we need do it?Flip image is some kind like data argument?
if self.set_name=='train' and np.random.random(1)>0.5: image1 =
image1.transpose(PIL.Image.FLIP_TOP_BOTTOM) image2 =
image2.transpose(PIL.Image.FLIP_TOP_BOTTOM) if self.set_name=='train' and
np.random.random(1)>0.5: image1 =
image1.transpose(PIL.Image.FLIP_LEFT_RIGHT) image2 =
image2.transpose(PIL.Image.FLIP_LEFT_RIGHT)
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
<#4 (comment)>,
or mute the thread
<https://github.com/notifications/unsubscribe-auth/ABRJSJHCDKVKJVASUUXUDWDPSZPKRANCNFSM4HI76GKA>
.
The text was updated successfully, but these errors were encountered: