LPX55 commited on
Commit
7820a52
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1 Parent(s): 12cea06

Update app.py

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Files changed (1) hide show
  1. app.py +12 -3
app.py CHANGED
@@ -17,8 +17,17 @@ clf = pipeline(model=model, task="image-classification", image_processor=image_p
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  class_names = ['artificial', 'real']
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  def predict_image(img, confidence_threshold):
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- # Convert the image to a PIL Image and resize it
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- img_pil = Image.fromarray(img).convert('RGB') # Convert NumPy array to PIL Image
 
 
 
 
 
 
 
 
 
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  img_pil = transforms.Resize((256, 256))(img_pil)
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  # Get the prediction
@@ -39,7 +48,7 @@ def predict_image(img, confidence_threshold):
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  return f"Label: real, Confidence: {result['real']:.4f}"
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  else:
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  return "Uncertain Classification"
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-
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  # Define the Gradio interface
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  image = gr.Image(label="Image to Analyze", sources=['upload'], type='pil') # Ensure the image type is PIL
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  confidence_slider = gr.Slider(0.0, 1.0, value=0.5, step=0.01, label="Confidence Threshold")
 
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  class_names = ['artificial', 'real']
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  def predict_image(img, confidence_threshold):
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+ print(f"Type of img: {type(img)}") # Debugging statement
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+ if not isinstance(img, Image.Image):
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+ raise ValueError(f"Expected a PIL Image, but got {type(img)}")
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+
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+ # Convert the image to RGB if not already
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+ if img.mode != 'RGB':
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+ img_pil = img.convert('RGB')
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+ else:
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+ img_pil = img
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+
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+ # Resize the image
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  img_pil = transforms.Resize((256, 256))(img_pil)
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  # Get the prediction
 
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  return f"Label: real, Confidence: {result['real']:.4f}"
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  else:
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  return "Uncertain Classification"
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+
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  # Define the Gradio interface
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  image = gr.Image(label="Image to Analyze", sources=['upload'], type='pil') # Ensure the image type is PIL
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  confidence_slider = gr.Slider(0.0, 1.0, value=0.5, step=0.01, label="Confidence Threshold")