[3DV 2025] Code for "FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent" by Cameron Smith*, David Charatan*, Ayush Tewari, and Vincent Sitzmann
Hi! Thanks for sharing this amazing work. This is a minor issue but in my case reduced the overfit training time significantly:
Currently, the validation step is being executed 64 times at every val_check_interval (with the same data each time, generating 64 visualizations that are overriden 63 times). This is because the num_workers of the dummy validation DataLoader is set to 64.
The above can be avoided by simply setting num_workers=1 in the val_dataloader method of DataModuleOverfit. Alternatively, a limit_val_batches=1 can be set at Trainer initialization in overfit.py but this may be sub-optimal because I think it would still launch the 64 subprocesses.
Hi! Thanks for sharing this amazing work. This is a minor issue but in my case reduced the overfit training time significantly:
Currently, the validation step is being executed 64 times at every
val_check_interval
(with the same data each time, generating 64 visualizations that are overriden 63 times). This is because thenum_workers
of the dummy validationDataLoader
is set to 64.The above can be avoided by simply setting
num_workers=1
in theval_dataloader
method ofDataModuleOverfit
. Alternatively, alimit_val_batches=1
can be set atTrainer
initialization inoverfit.py
but this may be sub-optimal because I think it would still launch the 64 subprocesses.