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Update README.md

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@@ -3,6 +3,44 @@ library_name: transformers
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  tags: []
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  ---
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  # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->
 
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  tags: []
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  ---
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+ ## Model Usage
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+ import gradio as gr
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+ from transformers import pipeline
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+ from PIL import Image
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+ import numpy as np
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+
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+ ### Define function to perform inference
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+ def predict_image(image):
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+ # Initialize the pipeline outside the function if possible for efficiency
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+ pipe = pipeline("image-classification", model="itsTomLie/Jaundice_Classifier")
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+
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+ # Convert NumPy array to PIL Image if necessary
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+ if isinstance(image, np.ndarray):
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+ image = Image.fromarray(image.astype('uint8'))
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+ elif isinstance(image, str): # If image is a file path
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+ image = Image.open(image)
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+
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+ # Perform prediction
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+ result = pipe(image)
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+
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+ # Extract label and confidence
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+ label = result[0]['label']
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+ confidence = result[0]['score']
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+
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+ print(f"Prediction: {label}, Confidence: {confidence}")
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+
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+ return label, confidence
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+
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+ ### Create Gradio interface
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+ interface = gr.Interface(
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+ fn=predict_image,
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+ inputs=gr.Image(type="numpy", label="Upload an Image"),
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+ outputs=[gr.Textbox(label="Prediction"), gr.Textbox(label="Confidence")]
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+ )
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+
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+ interface.launch(debug=True)
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+
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+
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  # Model Card for Model ID
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  <!-- Provide a quick summary of what the model is/does. -->