Update info in README.md & docs/encoders.rst to add mbv3, & update requirements.txt for torchvision 0.9.0

Author: ludics

README.md

@@ -12,7 +12,7 @@ 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)
- - 104 available encoders
+ - 106 available encoders
  - All encoders have pre-trained weights for faster and better convergence
 
 ### [📚 Project Documentation 📚](http://smp.readthedocs.io/)
@@ -284,6 +284,8 @@ The following is a list of supported encoders in the SMP. Select the appropriate
 |Encoder                         |Weights                         |Params, M                       |
 |--------------------------------|:------------------------------:|:------------------------------:|
 |mobilenet_v2                    |imagenet                        |2M                              |
+|mobilenet_v3_large              |imagenet                        |3M                              |
+|mobilenet_v3_small              |imagenet                        |1M                              |
 
 </div>
 </details>

docs/encoders.rst

@@ -252,11 +252,15 @@ EfficientNet
 MobileNet
 ~~~~~~~~~
 
-+-----------------+------------+-------------+
-| Encoder         | Weights    | Params, M   |
-+=================+============+=============+
-| mobilenet\_v2   | imagenet   | 2M          |
-+-----------------+------------+-------------+
++---------------------+------------+-------------+
+| Encoder             | Weights    | Params, M   |
++=====================+============+=============+
+| mobilenet\_v2       | imagenet   | 2M          |
++---------------------+------------+-------------+
+| mobilenet\_v3_large | imagenet   | 3M          |
++---------------------+------------+-------------+
+| mobilenet\_v2_small | imagenet   | 1M          |
++---------------------+------------+-------------+
 
 DPN
 ~~~

requirements.txt

@@ -1,4 +1,4 @@
-torchvision>=0.3.0
+torchvision==0.9.0
 pretrainedmodels==0.7.4
 efficientnet-pytorch==0.6.3
 timm==0.3.2