akhaliq HF staff commited on
Commit
4280f5a
1 Parent(s): c0a3f1e

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +12 -11
app.py CHANGED
@@ -60,20 +60,21 @@ def predict_depth(input_image):
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  if depth.ndim != 2:
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  depth = depth.squeeze()
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- # Normalize depth for visualization
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- depth_min = np.min(depth)
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- depth_max = np.max(depth)
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- depth_normalized = (depth - depth_min) / (depth_max - depth_min)
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-
 
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  # Create a color map
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  plt.figure(figsize=(10, 10))
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- plt.imshow(depth_normalized, cmap='viridis')
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- plt.colorbar(label='Depth')
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- plt.title('Predicted Depth Map')
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  plt.axis('off')
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  # Save the plot to a file
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- output_path = "depth_map.png"
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  plt.savefig(output_path)
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  plt.close()
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@@ -89,9 +90,9 @@ def predict_depth(input_image):
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  iface = gr.Interface(
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  fn=predict_depth,
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  inputs=gr.Image(type="filepath"),
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- outputs=[gr.Image(type="filepath", label="Depth Map"), gr.Textbox(label="Focal Length or Error Message")],
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  title="DepthPro Demo",
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- description="[DepthPro](https://huggingface.co/apple/DepthPro) is a fast metric depth prediction model. Simply upload an image to predict its depth map and focal length. Large images will be automatically resized."
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  )
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  # Launch the interface
 
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  if depth.ndim != 2:
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  depth = depth.squeeze()
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+ # Calculate inverse depth
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+ inverse_depth = 1.0 / depth
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+
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+ # Clip inverse depth to 0-10 range
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+ inverse_depth_clipped = np.clip(inverse_depth, 0, 10)
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+
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  # Create a color map
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  plt.figure(figsize=(10, 10))
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+ plt.imshow(inverse_depth_clipped, cmap='viridis')
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+ plt.colorbar(label='Inverse Depth')
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+ plt.title('Predicted Inverse Depth Map')
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  plt.axis('off')
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  # Save the plot to a file
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+ output_path = "inverse_depth_map.png"
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  plt.savefig(output_path)
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  plt.close()
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  iface = gr.Interface(
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  fn=predict_depth,
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  inputs=gr.Image(type="filepath"),
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+ outputs=[gr.Image(type="filepath", label="Inverse Depth Map"), gr.Textbox(label="Focal Length or Error Message")],
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  title="DepthPro Demo",
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+ description="[DepthPro](https://huggingface.co/apple/DepthPro) is a fast metric depth prediction model. Simply upload an image to predict its inverse depth map and focal length. Large images will be automatically resized."
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  )
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  # Launch the interface