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To make it clear, the whole tranlation can be described as follows:
(1)world coordinate(unscaled)<->(2)world coordinate, but self.origin is the origin(unscaled)<->(3)sdf grid coordinate(scaled)
(3) to (2) is simply a scale transformation(multiplied by the scale factor, a.k.a. self.resolution), (2) to (1) is a translation(added by self.origin).
self.T_grid_sdf_ try to establish a tranform from (3) to (1). Since in autolab_core==0.0.4, SimilarityTransform is a two-step process begin with scale then rotation/translation(code). We should use an unscaled translation here, which means that the self.origin should not be divided by self.resolution.
The text was updated successfully, but these errors were encountered:
Thank you @jeasinema !! I was generating a custom dataset for Dex-Net using custom-databases branch and I can confirm that indeed I was able to fix an issue with this transform by editing this line to t_grid_sdf = self.origin.
At least now my grasp candidates are being stored and shown correctly!
To make it clear, the whole tranlation can be described as follows:
(3) to (2) is simply a scale transformation(multiplied by the scale factor, a.k.a.
self.resolution
), (2) to (1) is a translation(added byself.origin
).self.T_grid_sdf_
try to establish a tranform from (3) to (1). Since inautolab_core==0.0.4
,SimilarityTransform
is a two-step process begin with scale then rotation/translation(code). We should use an unscaled translation here, which means that theself.origin
should not be divided byself.resolution
.The text was updated successfully, but these errors were encountered: