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Jun 5, 2024
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Add create_model to docs #883

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13 changes: 13 additions & 0 deletions docs/quickstart.rst
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Expand Up @@ -20,6 +20,19 @@ Segmentation model is just a PyTorch nn.Module, which can be created as easy as:
- Check the table with :doc:`available ported encoders and its corresponding weights <encoders>`.
- `Pytorch Image Models (timm) <https://github.com/huggingface/pytorch-image-models>`_ encoders are also supported, check it :doc:`here<encoders_timm>`.

Alternatively, you can use `smp.create_model` function to create a model by name:

.. code-block:: python

model = smp.create_model(
arch="fpn", # name of the architecture, e.g. 'Unet'/ 'FPN' / etc. Case INsensitive!
encoder_name="mit_b0",
encoder_weights="imagenet",
in_channels=1,
classes=3,
)


**2. Configure data preprocessing**

All encoders have pretrained weights. Preparing your data the same way as during weights pre-training may give your better results (higher metric score and faster convergence). But it is relevant only for 1-2-3-channels images and **not necessary** in case you train the whole model, not only decoder.
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