edyoshikun commited on
Commit
90ad424
1 Parent(s): 400cbe1

delete duplicated images and adding removing gpu dependency

Browse files
Files changed (3) hide show
  1. a549.png +0 -0
  2. app.py +5 -3
  3. hek.png +0 -0
a549.png DELETED
Binary file (107 kB)
 
app.py CHANGED
@@ -11,6 +11,9 @@ class VSGradio:
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  def __init__(self, model_config, model_ckpt_path):
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  self.model_config = model_config
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  self.model_ckpt_path = model_ckpt_path
 
 
 
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  self.model = None
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  self.load_model()
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@@ -20,10 +23,9 @@ class VSGradio:
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  self.model_ckpt_path,
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  architecture="UNeXt2_2D",
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  model_config=self.model_config,
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- accelerator="gpu",
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  )
 
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  self.model.eval()
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- self.model
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  def normalize_fov(self, input: ArrayLike):
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  "Normalizing the fov with zero mean and unit variance"
@@ -38,7 +40,7 @@ class VSGradio:
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  inp = torch.from_numpy(np.array(inp).astype(np.float32))
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  test_dict = dict(
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  index=None,
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- source=inp.unsqueeze(0).unsqueeze(0).unsqueeze(0).to(self.model.device),
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  )
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  with torch.inference_mode():
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  self.model.on_predict_start()
 
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  def __init__(self, model_config, model_ckpt_path):
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  self.model_config = model_config
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  self.model_ckpt_path = model_ckpt_path
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+ self.device = torch.device(
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+ "cuda" if torch.cuda.is_available() else "cpu"
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+ ) # Check if GPU is available
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  self.model = None
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  self.load_model()
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  self.model_ckpt_path,
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  architecture="UNeXt2_2D",
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  model_config=self.model_config,
 
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  )
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+ self.model.to(self.device)
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  self.model.eval()
 
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  def normalize_fov(self, input: ArrayLike):
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  "Normalizing the fov with zero mean and unit variance"
 
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  inp = torch.from_numpy(np.array(inp).astype(np.float32))
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  test_dict = dict(
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  index=None,
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+ source=inp.unsqueeze(0).unsqueeze(0).unsqueeze(0).to(self.device),
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  )
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  with torch.inference_mode():
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  self.model.on_predict_start()
hek.png DELETED
Binary file (98.1 kB)