MaxwellMeyer
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Update README.md
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README.md
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@@ -40,7 +40,7 @@ BEN2 was trained on the DIS5k and our 22K proprietary segmentation dataset. Our
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## Quick start code (inside cloned repo)
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```python
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import
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from PIL import Image
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import torch
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@@ -49,7 +49,7 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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file = "./image.png" # input image
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model =
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model.loadcheckpoints("./BEN2_Base.pth")
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image = Image.open(file)
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## Batch image processing
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```python
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import
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from PIL import Image
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import torch
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model =
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model.loadcheckpoints("./BEN2_Base.pth")
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```
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```python
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import
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from PIL import Image
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import torch
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@@ -111,7 +111,7 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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file = "./image.png" # input image
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model =
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model.loadcheckpoints("./BEN2_Base.pth")
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## Quick start code (inside cloned repo)
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```python
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import BEN2
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from PIL import Image
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import torch
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file = "./image.png" # input image
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model = BEN2.BEN_Base().to(device).eval() #init pipeline
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model.loadcheckpoints("./BEN2_Base.pth")
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image = Image.open(file)
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## Batch image processing
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```python
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import BEN2
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from PIL import Image
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import torch
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model = BEN2.BEN_Base().to(device).eval() #init pipeline
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model.loadcheckpoints("./BEN2_Base.pth")
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```
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```python
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import BEN2
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from PIL import Image
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import torch
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file = "./image.png" # input image
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model = BEN2.BEN_Base().to(device).eval() #init pipeline
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model.loadcheckpoints("./BEN2_Base.pth")
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