BhumikaMak commited on
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3f486c1
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1 Parent(s): 09b4bbd

Update app.py

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  1. app.py +13 -11
app.py CHANGED
@@ -75,21 +75,23 @@ custom_css = """
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  display: flex;
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  justify-content: center; /* Center-align contents */
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  }
 
 
 
 
 
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  """
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  with gr.Blocks(css=custom_css) as interface:
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- gr.Markdown(
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- """
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- # NeuralVista
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- Welcome to NeuralVista, a powerful tool designed to help you visualize object detection models in action. With the integration of state-of-the-art YOLO models, you can explore the performance of object detection algorithms on various images.
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-
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- Whether you're looking to analyze pre-existing samples or upload your own images,
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- NeuralVista allows you to experiment with different YOLO versions, providing you with valuable
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- insights into how these models interpret and detect objects. Additionally,
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- you can view deep feature factorization outputs and gain a deeper understanding of model behavior at different layers,
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- all within an intuitive interface."""
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- )
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  # Default sample
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  default_sample = "Sample 1"
 
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  display: flex;
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  justify-content: center; /* Center-align contents */
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  }
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+ .highlighted-text {
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+ color: blue;
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+ font-size: 32px; /* Increase font size */
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+ font-weight: bold;
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+ }
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  """
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  with gr.Blocks(css=custom_css) as interface:
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+ gr.Markdown("""
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+ ## NeuralVista
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+ <p>Welcome to <span class="highlighted-text">NeuralVista</span>, a powerful tool designed to help you visualize object detection models in action.
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+ With the integration of state-of-the-art YOLO models, you can explore the performance of object detection algorithms on various images.</p>
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+ <p>Whether you're looking to analyze pre-existing samples or upload your own images, NeuralVista allows you to experiment with different YOLO versions,
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+ providing you with valuable insights into how these models interpret and detect objects. Additionally, you can view deep feature factorization outputs
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+ and gain a deeper understanding of model behavior at different layers, all within an intuitive interface.</p>
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+ """)
 
 
 
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  # Default sample
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  default_sample = "Sample 1"