GV05 commited on
Commit
af4c588
1 Parent(s): 88e0145

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +3 -6
app.py CHANGED
@@ -13,14 +13,11 @@ model = VariationalAutoEncoder(INPUT_DIM, H_DIM, Z_DIM)
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  model.load_state_dict(torch.load("MnistVAEmodel.pt"))
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  model.eval()
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  def predict(img):
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- img = img.convert('1')
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  img = transforms.ToTensor()(img)
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- img = transforms.CenterCrop(size=28)(img)
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- print(type(img), img.shape)
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  mu, sigma = model.encode(img.view(1, INPUT_DIM))
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  res = []
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- for example in range(10):
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  epsilon = torch.randn_like(sigma)
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  z = mu + sigma * epsilon
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  out = model.decode(z)
@@ -30,6 +27,6 @@ def predict(img):
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  title = "Variational-Autoencoder-on-MNIST "
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  description = "TO DO"
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- examples = ["original_5.png", "original_8.png"]
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- gr.Interface(fn=predict, inputs = gr.inputs.Image(), outputs= gr.Gallery(),
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  examples=examples, title=title, description=description).launch(inline=False)
 
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  model.load_state_dict(torch.load("MnistVAEmodel.pt"))
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  model.eval()
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  def predict(img):
 
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  img = transforms.ToTensor()(img)
 
 
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  mu, sigma = model.encode(img.view(1, INPUT_DIM))
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  res = []
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+ for example in range(5):
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  epsilon = torch.randn_like(sigma)
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  z = mu + sigma * epsilon
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  out = model.decode(z)
 
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  title = "Variational-Autoencoder-on-MNIST "
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  description = "TO DO"
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+ examples = ["original_8.png"]
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+ gr.Interface(fn=predict, inputs = gr.inputs.Image(shape=(28,28), image_mode="L"), outputs= gr.Gallery(),
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  examples=examples, title=title, description=description).launch(inline=False)