Includes code to run some soft flow things. This git repository automatically uploads to weights and biases at the soft_flow
project (can be changed in overfit.yaml
).
To train a model, do
python main.py --name name_of_run --mode {online,dryrun,offline,disabled}
Note: pytorch lightning will try to use all the gpus on the machine.
main.py
: training loop, shouldn't need to be modifiedoverfit_soft_learner.py
: code for the soft flow model. This version uses superresolution, warping a 1024x512 source frame (frame 3) to a 256x128 target frame (frame 2), learning flows frame2 to frame3 (i think). Includes brief explanations of the logged datasintel_superres.py
: dataloading. Note: the path to the Sintel dataset needs to be changedroaming_images.py
: roamingimages dataset, toy dataset. Not integrated with the current soft flow learneroverfit.yaml
: configuration filedownload_learner.py
: some minimal code to download trained models (models are currently saved every 5000 steps), and then you can run arbitrary code on themsoft_losses.py, soft_utils.py
: losses and utilities for soft flow