sayedM commited on
Commit
a80efbb
·
1 Parent(s): 8cc4adb

Update app.py

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -82,7 +82,7 @@ description_html = """
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  </head>
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  <body>
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  <h1>Tuba AI Auto-Annotation 🚀</h1>
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- <h2>Saving Time, Bounding Boxes at a Time </h2>
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  <h2>Introduction</h2>
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  <p>Welcome to the world of DevisionX, where AI meets vision to revolutionize annotation. Our mission is to make computer vision accessible to all, and this README is your gateway to understanding how our auto-annotation model can change the way you work.</p>
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  <h2>Meet Tuba.AI - Your Partner in Vision</h2>
@@ -128,8 +128,8 @@ with gr.Blocks() as demo:
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  """
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  <div style="text-align: center;">
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  <h1>Tuba Autoannotation Demo</h1>
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- <h3>A prompt based controllable model for auto annotation </h3>
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- <h3>Saving Time, Bounding Boxes at a Time </h3>
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  Powered by <a href="https://Tuba.ai">Tuba</a>
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  </div>
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  """
@@ -137,7 +137,7 @@ with gr.Blocks() as demo:
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  # Define the input components and add them to the layout
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  with gr.Row():
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- image_input = gr.inputs.Image()
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  output = gr.Image(type="numpy", label="Output Image")
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  # Define the output component and add it to the layout
 
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  </head>
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  <body>
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  <h1>Tuba AI Auto-Annotation 🚀</h1>
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+ <h2>Saving Time, Bounding Boxes & Polygons at a Time </h2>
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  <h2>Introduction</h2>
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  <p>Welcome to the world of DevisionX, where AI meets vision to revolutionize annotation. Our mission is to make computer vision accessible to all, and this README is your gateway to understanding how our auto-annotation model can change the way you work.</p>
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  <h2>Meet Tuba.AI - Your Partner in Vision</h2>
 
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  """
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  <div style="text-align: center;">
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  <h1>Tuba Autoannotation Demo</h1>
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+ <h3>A prompt based controllable model for auto annotation (Detection and Segmentation) </h3>
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+ <h3>Saving Time, Bounding Boxes & Polygons at a Time </h3>
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  Powered by <a href="https://Tuba.ai">Tuba</a>
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  </div>
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  """
 
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  # Define the input components and add them to the layout
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  with gr.Row():
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+ image_input = gr.Image()
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  output = gr.Image(type="numpy", label="Output Image")
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  # Define the output component and add it to the layout