update readme and doc

Author: brianhou0208

README.md

@@ -19,7 +19,7 @@ Segmentation based on [PyTorch](https://pytorch.org/).**
 The main features of this library are:
 
  - High-level API (just two lines to create a neural network)
- - 9 models architectures for binary and multi class segmentation (including legendary Unet)
+ - 10 models architectures for binary and multi class segmentation (including legendary Unet)
  - 124 available encoders (and 500+ encoders from [timm](https://github.com/rwightman/pytorch-image-models))
  - All encoders have pre-trained weights for faster and better convergence
  - Popular metrics and losses for training routines
@@ -94,6 +94,7 @@ Congratulations! You are done! Now you can train your model with your favorite f
  - PAN [[paper](https://arxiv.org/abs/1805.10180)] [[docs](https://smp.readthedocs.io/en/latest/models.html#pan)]
  - DeepLabV3 [[paper](https://arxiv.org/abs/1706.05587)] [[docs](https://smp.readthedocs.io/en/latest/models.html#deeplabv3)]
  - DeepLabV3+ [[paper](https://arxiv.org/abs/1802.02611)] [[docs](https://smp.readthedocs.io/en/latest/models.html#id9)]
+ - UPerNet [[paper](https://arxiv.org/abs/1807.10221)] [[docs](https://smp.readthedocs.io/en/latest/models.html#upernet)]
 
 #### Encoders <a name="encoders"></a>
 

docs/models.rst

@@ -66,3 +66,10 @@ MAnet
 PAN
 ~~~
 .. autoclass:: segmentation_models_pytorch.PAN
+
+
+.. _upernet:
+
+UPerNet
+~~~
+.. autoclass:: segmentation_models_pytorch.UPerNet