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typos correction #525

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38 changes: 19 additions & 19 deletions README.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ Table of Contents
- `Change log`_
- `Citing`_
- `License`_

Quick start
~~~~~~~~~~~
Library is build to work together with Keras and TensorFlow Keras frameworks
Expand Down Expand Up @@ -73,9 +73,9 @@ This can be useful for further model conversion to Nvidia TensorRT format or opt
Created segmentation model is just an instance of Keras Model, which can be build as easy as:

.. code:: python

model = sm.Unet()

Depending on the task, you can change the network architecture by choosing backbones with fewer or more parameters and use pretrainded weights to initialize it:

.. code:: python
Expand All @@ -85,29 +85,29 @@ Depending on the task, you can change the network architecture by choosing backb
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 = sm.Unet('resnet34', classes=1, activation='sigmoid')

.. code:: python

# multiclass segmentation with non overlapping class masks (your classes + background)
model = sm.Unet('resnet34', classes=3, activation='softmax')

.. code:: python

# multiclass segmentation with independent overlapping/non-overlapping class masks
model = sm.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
~~~~~~~~~~~~~~~~~~~~~~~~

Expand Down Expand Up @@ -185,9 +185,9 @@ PSPNet FPN

**Backbones**

.. table::
.. table::

============= =====
============= =====
Type Names
============= =====
VGG ``'vgg16' 'vgg19'``
Expand All @@ -196,14 +196,14 @@ PSPNet FPN
ResNeXt ``'resnext50' 'resnext101'``
SE-ResNeXt ``'seresnext50' 'seresnext101'``
SENet154 ``'senet154'``
DenseNet ``'densenet121' 'densenet169' 'densenet201'``
DenseNet ``'densenet121' 'densenet169' 'densenet201'``
Inception ``'inceptionv3' 'inceptionresnetv2'``
MobileNet ``'mobilenet' 'mobilenetv2'``
EfficientNet ``'efficientnetb0' 'efficientnetb1' 'efficientnetb2' 'efficientnetb3' 'efficientnetb4' 'efficientnetb5' efficientnetb6' efficientnetb7'``
============= =====

.. epigraph::
All backbones have weights trained on 2012 ILSVRC ImageNet dataset (``encoder_weights='imagenet'``).
All backbones have weights trained on 2012 ILSVRC ImageNet dataset (``encoder_weights='imagenet'``).


Installation
Expand Down Expand Up @@ -234,10 +234,10 @@ Installation
.. code:: bash

$ pip install git+https://github.com/qubvel/segmentation_models

Documentation
~~~~~~~~~~~~~
Latest **documentation** is avaliable on `Read the
Latest **documentation** is available on `Read the
Docs <https://segmentation-models.readthedocs.io/en/latest/>`__

Change Log
Expand All @@ -256,7 +256,7 @@ Citing
Publisher = {GitHub},
Journal = {GitHub repository},
Howpublished = {\url{https://github.com/qubvel/segmentation_models}}
}
}

License
~~~~~~~
Expand Down