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Data Augmentation

See original GitHub issue

Hey!

Ich checked your data augmentation. In random rotate there is

#flow vectors must be rotated too! careful about Y flow which is upside down
        target_=np.array(target, copy=True)
        target[:,:,0] = np.cos(angle1_rad)*target_[:,:,0] + np.sin(angle1_rad)*target_[:,:,1]
        target[:,:,1] = -np.sin(angle1_rad)*target_[:,:,0] + np.cos(angle1_rad)*target_[:,:,1]

but in RandomCropRotate it is

#flow vectors must be rotated too!
        target_=np.array(target, copy=True)
        target[:,:,0] = np.cos(angle1_rad)*target_[:,:,0] - np.sin(angle1_rad)*target_[:,:,1]
        target[:,:,1] = np.sin(angle1_rad)*target_[:,:,0] + np.cos(angle1_rad)*target_[:,:,1]

I guess the first one is correct? Furthermore, if positive y flow is pointing downwards wouldn’t you have to change the translation as well? In RandomTranslate you do:

target[:,:,1]+= th

I guess if th is positive (you tranlsate upwards), your y flow would decrease?

What are your test scores on sintel (final, clean) or kitti? Many thanks

Issue Analytics

State:
Created 6 years ago
Comments:7 (5 by maintainers)

Top GitHub Comments

1reaction

ClementPinardcommented, Mar 23, 2018

You can just delete this line in main.py : https://github.com/ClementPinard/FlowNetPytorch/blob/master/main.py#L144 All data augmentation is comprised in co_transform routines

0reactions

bkviecommented, Mar 22, 2018

Hi, any way to turn off data augmentation? I want to compare both methods (with/with out data pre-processing).

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