Ateeqq commited on
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c892189
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1 Parent(s): 2b933d2

Update app.py

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Files changed (1) hide show
  1. app.py +8 -18
app.py CHANGED
@@ -122,8 +122,6 @@ body { font-family: 'Inter', sans-serif; }
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  /* Ensure label text inside columns is readable */
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  #prediction-label .label-name { font-weight: bold; font-size: 1.1em; }
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  #prediction-label .confidence { font-size: 1em; }
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- /* Theme should make label text light, but force if needed: */
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- /* #prediction-label { color: #e5e7eb; } */
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  /* Footer styling */
@@ -145,17 +143,9 @@ body { font-family: 'Inter', sans-serif; }
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  """
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  # --- Gradio Interface using Blocks and Theme ---
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- # Apply .dark() to the theme
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- theme = gr.themes.Soft(
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- primary_hue="emerald",
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- secondary_hue="blue",
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- neutral_hue="slate",
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- radius_size=gr.themes.sizes.radius_lg,
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- spacing_size=gr.themes.sizes.spacing_lg,
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- ).dark() # <<< APPLY DARK MODE HERE
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-
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-
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- with gr.Blocks(theme=theme, css=css) as iface:
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  # Title and Description
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  gr.Markdown("# AI vs Human Image Detector", elem_id="app-title")
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  gr.Markdown(
@@ -165,7 +155,7 @@ with gr.Blocks(theme=theme, css=css) as iface:
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  )
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  # Main layout
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- with gr.Row(variant='panel'): # Panel might look different in dark theme, adjust if needed
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  with gr.Column(scale=1, min_width=300, elem_id="input-column"):
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  image_input = gr.Image(
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  type="pil",
@@ -181,7 +171,6 @@ with gr.Blocks(theme=theme, css=css) as iface:
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  num_top_classes=2,
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  label="Classification",
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  elem_id="prediction-label"
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- # The theme should now correctly style the label text for dark mode
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  )
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  # Examples Section
@@ -193,18 +182,19 @@ with gr.Blocks(theme=theme, css=css) as iface:
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  fn=classify_image,
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  cache_examples=True,
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  label="✨ Click an Example to Try!"
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- # Examples appearance will also adapt to the dark theme
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  )
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  # Footer / Article section
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- # Removed explicit model ID formatting from Markdown string, use f-string
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  gr.Markdown(f"""
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  ---
 
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  This application uses a fine-tuned [SigLIP](https://huggingface.co/docs/transformers/model_doc/siglip) vision model
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  specifically trained to differentiate between images generated by Artificial Intelligence and those created by humans.
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- You can find the model card here: <a href='https://huggingface.co/{MODEL_IDENTIFIER}' target='_blank'>{MODEL_IDENTIFIER}</a>
 
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  Fine tuning code available at [https://exnrt.com/blog/ai/fine-tuning-siglip2/](https://exnrt.com/blog/ai/fine-tuning-siglip2/).
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  """,
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  elem_id="app-footer"
 
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  /* Ensure label text inside columns is readable */
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  #prediction-label .label-name { font-weight: bold; font-size: 1.1em; }
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  #prediction-label .confidence { font-size: 1em; }
 
 
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  /* Footer styling */
 
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  """
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  # --- Gradio Interface using Blocks and Theme ---
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+ # Use the theme string identifier for the dark mode variant
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+ # Other options: "default/dark", "monochrome/dark", "glass/dark"
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+ with gr.Blocks(theme="soft/dark", css=css) as iface: # <<< CHANGE IS HERE
 
 
 
 
 
 
 
 
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  # Title and Description
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  gr.Markdown("# AI vs Human Image Detector", elem_id="app-title")
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  gr.Markdown(
 
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  )
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  # Main layout
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+ with gr.Row(variant='panel'):
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  with gr.Column(scale=1, min_width=300, elem_id="input-column"):
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  image_input = gr.Image(
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  type="pil",
 
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  num_top_classes=2,
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  label="Classification",
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  elem_id="prediction-label"
 
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  )
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  # Examples Section
 
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  fn=classify_image,
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  cache_examples=True,
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  label="✨ Click an Example to Try!"
 
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  )
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  # Footer / Article section
 
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  gr.Markdown(f"""
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  ---
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+ **How it Works:**
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  This application uses a fine-tuned [SigLIP](https://huggingface.co/docs/transformers/model_doc/siglip) vision model
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  specifically trained to differentiate between images generated by Artificial Intelligence and those created by humans.
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+ **Model:**
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+ * You can find the model card here: <a href='https://huggingface.co/{MODEL_IDENTIFIER}' target='_blank'>{MODEL_IDENTIFIER}</a>
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+ **Training Code:**
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  Fine tuning code available at [https://exnrt.com/blog/ai/fine-tuning-siglip2/](https://exnrt.com/blog/ai/fine-tuning-siglip2/).
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  """,
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  elem_id="app-footer"