CyberAgentAILab
Ratio parameter
Hi,
Im trying to run the code and Im following the steps for DiligentMV dataset:)
Im using Metashape to estimate the cameras from images and I exported the cameras to xml file from this software. So, I run the code called metashape2neus.py, but my cameras npz file are not the same that the npz file from downloaded data, are in a different scale and I set the ratio parameter to 10. How could I estimate the cameras correctly ? and how could I get this ratio parameter for my own data ? for example my camera is 10 cm to my object, and my object size is like 3 cm, my ratio would be 3.3 ?
Thank you so much for this great work!!
Best and thanks!
This image is the camera positions from each file, red color is the camera positions that i got and the blue is from downloaded data.
Hi, It seems the camera parameters estimated by Metashape are not reliable (if the figure corresponds to the Diligent-MV dataset). The well-calibrated camera parameters are stored in the 'Calib_info.mat' file of the diligent-mv dataset. The camera centers of the 20 views should have the same distance from the object and be uniformly distributed on the same elevation, since the object is rotated by a turntable and the camera is fixed.
For your information, we have updated the scene normalization method with a more intuitive hyper-parameter tuning in our new work. https://arxiv.org/abs/2507.23162 See Section 8 and Figure 16 in the supplementary for details. Code is coming in 1~2 weeks, but it should not be difficult to implement.
Best regards
Oh thank you so much for the fast answer!! Im going to implement this!
Best! :)
xucao-42 left a comment (CyberAgentAILab/SuperNormal#13) https://github.com/CyberAgentAILab/SuperNormal/issues/13#issuecomment-3154916043
Hi, It seems the camera parameters estimated by Metashape are not reliable (if the figure corresponds to the Diligent-MV dataset). The well-calibrated camera parameters are stored in the 'Calib_info.mat' file of the diligent-mv dataset. The camera centers of the 20 views should have the same distance from the object and be uniformly distributed on the same elevation, since the object is rotated by a turntable and the camera is fixed.
For your information, we have updated the scene normalization method with a more intuitive hyper-parameter tuning in our new work. https://arxiv.org/abs/2507.23162 See Section 8 and Figure 16 in the supplementary for details. Code is coming in 1~2 weeks, but it should not be difficult to implement.
Best regards
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