Description
🐛 Bugs / Unexpected behaviors
Unable to reproduce the results shown in the plots of the bundle adjustment tutorial, with the script unmodified.
Instructions To Reproduce the Issue:
-
The exact command(s) you ran:
Go to bundle adjustment tutorial, click on run in google colab, run all cells. -
What you observed:
This imprecise result
to compare with the "expected result" from the notebook introduction:
Just to be sure that this wasn't "bad luck" with the random seed, I commented the line torch.manual_seed(42) in the second code cell and ran the last cell >20 times. Each time I got a different result, and in only one case was the result matching perfectly the ground truth. In the other cases the final estimation was qualitatively as bad as in the screenshot above.
Maybe I also had bad luck with my trials, but anyways I wanted to let you know about this discrepancy between expected and actual behavior.
- Correction proposition
Using 4000 iterations instead of 2000 and increasing the learning rate from 0.1 to 0.4 does help to reach the correct solution, as with the initial parameters the poses had not finished to converge at 2000 iterations (by looking at the plots). The correct solution is however not consistently reached (e.g. running once with manual seed = 0 and then running a second time doesn't converge completely)