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Update README.md

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@@ -39,6 +39,7 @@ Trained by [Tissue Image Analytics (TIA) Centre](https://warwick.ac.uk/fac/cross
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  ```python
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  from urllib.request import urlopen
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  from PIL import Image
 
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  import timm
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  # get example histology image
@@ -54,6 +55,9 @@ model = timm.create_model(
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  pretrained=True,
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  ).eval()
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  # get model specific transforms (normalization, resize)
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  data_config = timm.data.resolve_model_data_config(model)
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  transforms = timm.data.create_transform(**data_config, is_training=False)
@@ -67,6 +71,7 @@ output = model(data) # output is a (batch_size, num_features) shaped tensor
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  ```python
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  from urllib.request import urlopen
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  from PIL import Image
 
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  import timm
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  # get example histology image
@@ -83,6 +88,9 @@ model = timm.create_model(
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  num_classes=0,
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  ).eval()
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  # get model specific transforms (normalization, resize)
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  data_config = timm.data.resolve_model_data_config(model)
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  transforms = timm.data.create_transform(**data_config, is_training=False)
 
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  ```python
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  from urllib.request import urlopen
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  from PIL import Image
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+ import torch.nn as nn
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  import timm
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  # get example histology image
 
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  pretrained=True,
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  ).eval()
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+ # disable norm5's activation, as per torchvision's implementation
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+ model.features.norm5.act == nn.Identity()
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+
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  # get model specific transforms (normalization, resize)
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  data_config = timm.data.resolve_model_data_config(model)
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  transforms = timm.data.create_transform(**data_config, is_training=False)
 
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  ```python
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  from urllib.request import urlopen
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  from PIL import Image
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+ import torch.nn as nn
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  import timm
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  # get example histology image
 
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  num_classes=0,
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  ).eval()
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+ # disable norm5's activation, as per torchvision's implementation
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+ model.features.norm5.act == nn.Identity()
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+
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  # get model specific transforms (normalization, resize)
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  data_config = timm.data.resolve_model_data_config(model)
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  transforms = timm.data.create_transform(**data_config, is_training=False)