train_tools.models.MEDIARFormer

Module Contents

class train_tools.models.MEDIARFormer.MEDIARFormer(encoder_name='mit_b5', encoder_weights='imagenet', decoder_channels=(1024, 512, 256, 128, 64), decoder_pab_channels=256, in_channels=3, classes=3)[source]

Bases: segmentation_models_pytorch.MAnet

MEDIAR-Former Model

segmentation_head = None[source]
cellprob_head[source]
gradflow_head[source]
forward(x)[source]

Forward pass through the network