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I met a strange question, you can reproduce this situation using the attached files.
I have a target pose A (a simple T-pose, in quaternion form, with a shape of [66, 4], representing 66 bones). I obtained a pose A (in quaternion form) through an optimization method.
When I used pymotion.ops.forward_kinematics.fk to check, I found that the joints obtained from these two poses were very close, and they also looked very similar visually.
To reproduce this, simply run "python debug_train.py"
This code should produce: 2.461019589902293e-07, which is the joint position error, seems good.
However, when I assigned these two poses to the corresponding bones in Blender, the results were significantly different.
To verify this, try the blender file in the attached file.
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Hi, thanks for your great code, it helps a lot!
I met a strange question, you can reproduce this situation using the attached files.
I have a target pose A (a simple T-pose, in quaternion form, with a shape of [66, 4], representing 66 bones). I obtained a pose A (in quaternion form) through an optimization method.
When I used pymotion.ops.forward_kinematics.fk to check, I found that the joints obtained from these two poses were very close, and they also looked very similar visually.
To reproduce this, simply run "python debug_train.py"
This code should produce: 2.461019589902293e-07, which is the joint position error, seems good.
However, when I assigned these two poses to the corresponding bones in Blender, the results were significantly different.

To verify this, try the blender file in the attached file.
Attached file:
issue_files.zip
The quaternion above are all normalized already.
What could be the possible reasons for this? Thanks!
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