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latest version of pytorch3d does not support crop_bbox_xywh from CO3Dv2 #1835
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@amanikiruga Thanks for the report. More generally though, this field is an implementation detail (it is NOT the annotation bounding box, but merely an intermediate variable used in padded cropping). Does your code mean to load uncropped frames? In that case, you could just pass |
Thank you @shapovalov
I'm not sure why but I can look into it if that will be helpful. Indeed I am using the cropped values and I would just need to know the cropped coordinates in the original resolution. This is because I wanted to get the foreground object from the original image but the foreground mask is in the 800x800 cropped resolution. Unless there is a better way of doing this? |
@amanikiruga I see.
Then you can resize the mask if you have to.
Then probably the cropping behaviour may have changed. This value is indeed used (almost) directly to crop the image before resizing. Do you also see different crops in the old version? To produce this variable, we:
There are also some xyxy/xywh conversions along the way. This behaviour does not seem changed by ebdbfde |
If you do not know the root cause of the problem / bug, and wish someone to help you, please
post according to this template:
🐛 Bugs / Unexpected behaviors
The
FrameData
when loading CO3D dataset on the latest versionpytorch3d-0.7.7-py310_cu121_pyt231
shows thecrop_bbox_xywh
attribute to beNone
even though on older versions eg.0.7.2
don't.NOTE: Please look at the existing list of Issues tagged with the label 'bug`. Only open a new issue if this bug has not already been reported. If an issue already exists, please comment there instead..
Instructions To Reproduce the Issue:
I'm preprocessing CO3Dv2 following instructions from a paper's github repository. This issue is also referenced there: issue_link
Please include the following (depending on what the issue is):
git diff
) or code you wrotepython data_preprocessing.preprocess_co3d
Please also simplify the steps as much as possible so they do not require additional resources to
run, such as a private dataset.
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