rgbd_ptam
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performance issues
Hi, I tried to evaluate the performance on the TUM dataset (roo, desk2) and it does not look good.
Has anyone similar experience?
I found the problem: The way in dataset.py the rgb and depth frame association is done with make_pair function is wrong.
Please use associate.py from here: https://cvg.cit.tum.de/data/datasets/rgbd-dataset/tools And use these pairs. Then the code works ok. Not a similar performance as ORBV2 slam or PTAM but is close to ElasticFusion.