Train and test a hand segmentation model with the UNet architecture by querying over 48 hours of complex first-person interactions from the EgoHands Dataset using filters (location, activity, viewer, partner), and create a PyTorch Database object of respective images and binary hand segmentation labels. Built entirely with Python!
Contributions:91 commits, 96 pushes, 5 branches in 4 months
databasepythonpytorchsegmentation
Configs and boilerplates for Label Studio's Machine Learning backend
Contributions:2 PRs, 39 pushes, 2 branches in 4 months
backendlabel-studiomachine-learning