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Update app.py
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app.py
CHANGED
@@ -43,7 +43,7 @@ def detect(image, confidence_threshold=0.5):
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face_manipulation_likelihood = confidence_fake # Refine if possible
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# Add diagnostic output for debugging
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logger.info(f"Probabilities - Real: {confidence_real:.1f}%, Fake: {confidence_fake:.1f}
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overall = f"{confidence_score:.1f}% Confidence ({threshold_predicted})"
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aigen = f"{aigen_likelihood:.1f}% (AI-Generated Content Likelihood)"
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@@ -112,7 +112,7 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Default()) as demo:
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with gr.Row(elem_classes="container"):
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with gr.Column(scale=1):
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image = gr.Image(type='filepath', height=400, label="Upload Image")
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threshold = gr.Slider(0, 1, value=0.
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detect_button = gr.Button("Analyze Image", elem_classes="button-gradient")
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with gr.Column(scale=2):
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overall = gr.Label(label="Confidence Score")
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face_manipulation_likelihood = confidence_fake # Refine if possible
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# Add diagnostic output for debugging
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logger.info(f"Image: {image.name}, Probabilities - Real: {confidence_real:.1f}%, Fake: {confidence_fake:.1f}%, Predicted: {predicted_label}")
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overall = f"{confidence_score:.1f}% Confidence ({threshold_predicted})"
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aigen = f"{aigen_likelihood:.1f}% (AI-Generated Content Likelihood)"
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with gr.Row(elem_classes="container"):
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with gr.Column(scale=1):
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image = gr.Image(type='filepath', height=400, label="Upload Image")
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threshold = gr.Slider(0, 1, value=0.7, step=0.01, label="Confidence Threshold (Fake)")
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detect_button = gr.Button("Analyze Image", elem_classes="button-gradient")
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with gr.Column(scale=2):
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overall = gr.Label(label="Confidence Score")
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