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import gradio as gr
from transformers import pipeline
# Load the models using pipeline
image_model = pipeline("image-classification", model="dima806/deepfake_vs_real_image_detection")
# Define the prediction function
def predict(image):
result = image_model(image)
print("Raw prediction result:", result) # Debugging statement
# Convert the result to the expected format
output = {item['label']: item['score'] for item in result}
print("Formatted prediction result:", output) # Debugging statement
return output
# Create Gradio interface
inputs = gr.Image(type="filepath", label="Upload Image File", visible=False)
outputs = gr.Label(output)
gr.Interface(fn=predict, inputs=image_input, outputs=output).launch()
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