Code for weakly supervised segmentation of a single class
SingleClassRL
Implementation of weak single object segmentation from paper “Regularized Loss for Weakly Supervised Single Class Semantic Segmentation”, ECCV2020. PDF
Main Files
- train_with_anneal.py: use for training first in annealing stage, then in normal stage
- train_with_transfer.py: use from training with weight transfer from another dataset, models that can be used for weight transfer are in directory ‘trained_models’
OxfodPet dataset
Download OxfordPet from (https://www.robots.ox.ac.uk/~vgg/data/pets/) Files in ‘SingleClassRLdataOxford_iit_petannotations’ should be placed in the ‘annotation’ directory of OxfordPet dataset
GitHub