Open WilkoLu opened 2 years ago
Did you try? @mintar I think made everything backward compatible!
I had to check myself to see what I did. This is what I did:
train.py
) can now process both NDSS and NVISII data, but it doesn't have the nice tensorboard visualization.train2/train.py
) can only process NVISII data.The second point is @WilkoLu 's problem.
However, I think the differences are small, so it should be easy to adapt train2
to the NDSS format. Here is what's currently failing:
I think the best solution here would be to fix the NDSS json data (search/replace), because NDSS only stores visible objects (but always sets visibility to "0"), whereas "visibility = 0" in NVISII means that the object actually is occluded/out of view, so it must be discarded.
Here we could check whether we have 8 or 9 points in the json file, and if it's 8, read "projected_cuboid_centroid" and append it, like I did in the old train.py
script:
I think in the long run we should unify train.py
and train2
, there's no point in keeping both around.
Hello
I need NDDS Data to work on the "new" training script with tensorboard visualisation. It seems not possible yet. Do you consider to improve in this way? I want to use NDDS data for training and NVISII data for testing. NDDS is pretty performant in creating big datasets for training and NVISII delivers good looking testing datasets.