ascarlettvfx commited on
Commit
e7f42e5
·
verified ·
1 Parent(s): 0dcbc31

Update app.py

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Files changed (1) hide show
  1. app.py +25 -3
app.py CHANGED
@@ -20,15 +20,37 @@ def predict_depth(image):
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  -50, # Frame's near plane offset
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  api_name="/submit_depth_fn"
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  )
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- return response['image'] # Adjust according to the actual key in the response
 
 
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  # Gradio Interface
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  iface = gr.Interface(
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  fn=predict_depth,
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  inputs=gr.Image(type='filepath', label="Upload your image"),
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- outputs=gr.Image(type='auto', label="Depth Map Image"),
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  title="Depth Map Generator",
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- description="Upload an image to receive a depth map."
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  )
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  iface.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  -50, # Frame's near plane offset
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  api_name="/submit_depth_fn"
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  )
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+ # Assuming the API returns a filepath or you save the result to a file
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+ output_file_path = save_image_to_file(response['image']) # Implement this function based on your API's response
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+ return output_file_path
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  # Gradio Interface
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  iface = gr.Interface(
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  fn=predict_depth,
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  inputs=gr.Image(type='filepath', label="Upload your image"),
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+ outputs=gr.Image(type='filepath', label="Depth Map Image"),
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  title="Depth Map Generator",
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+ description="Upload an image to receive a depth map file."
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  )
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  iface.launch()
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+
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+ def save_image_to_file(image_data):
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+ # Assuming 'image_data' is the image data in a compatible format
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+ # You would save the image to a file and return the path
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+ import matplotlib.pyplot as plt
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+ import matplotlib.image as mpimg
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+ import numpy as np
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+ import tempfile
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+ import os
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+
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+ # Create a temporary file
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+ fd, path = tempfile.mkstemp(suffix=".png")
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+ try:
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+ # Assume image_data is a numpy array
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+ img = np.array(image_data).astype(np.uint8)
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+ plt.imsave(path, img)
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+ finally:
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+ os.close(fd)
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+
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+ return path