Unverified Commit ce52a1a9 authored by Pavel Yakubovskiy's avatar Pavel Yakubovskiy Committed by GitHub

Update README.rst

parent 486b05ca
......@@ -57,16 +57,30 @@ Depending on the task, you can change the network architecture by choosing backb
model = Unet('resnet34', encoder_weights='imagenet')
Change number of output classes in the model:
Change number of output classes in the model (choose your case):
.. code:: python
# binary segmentation (this parameters are default when you call Unet('resnet34')
model = Unet('resnet34', classes=1, activation='sigmoid')
.. code:: python
# multiclass segmentation with non overlapping class masks (your classes + background)
model = Unet('resnet34', classes=3, activation='softmax')
.. code:: python
# multiclass segmentation with independent overlapping/non-overlapping class masks
model = Unet('resnet34', classes=3, activation='sigmoid')
Change input shape of the model:
.. code:: python
# if you set input channels not equal to 3, you have to set encoder_weights=None
# how to handle such case with encoder_weights='imagenet' described in docs
model = Unet('resnet34', input_shape=(None, None, 6), encoder_weights=None)
Simple training pipeline
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