Input|           # input batch of images / / /|\ \ \      # apply augmentations (flips, rotation, scale, etc.)| | | | | | |     # pass augmented batches through model| | | | | | |     # reverse transformations for each batch of masks/labels\ \ \ / / /      # merge predictions (mean, max, gmean, etc.)|           # output batch of masks/labelsOutput

        $ pip install ttach

        import ttach as tta
...
model.load_state_dict(torch.load('models/%s/model.pth' %args.name))

model.eval()
tta_model = tta.SegmentationTTAWrapper(model, tta.aliases.d4_transform(), merge_mode='mean')
...