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Update app.py
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app.py
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@@ -11,6 +11,20 @@ from pytorch_grad_cam import GradCAM
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from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
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from pytorch_grad_cam.utils.image import show_cam_on_image
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#gr.themes.Soft()
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#gr.themes.builder()
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@@ -97,6 +111,9 @@ title = "Deepfake Image Detection"
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description = "~ AI - ML implementation for fake and real image detection..."
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article = "<p style='text-align: center'>...</p>"
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interface = gr.Interface(
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fn=predict,
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inputs=[
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@@ -109,6 +126,7 @@ interface = gr.Interface(
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gr.outputs.Image(label="Face with Explainability", type="pil")
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#ValueError: Invalid value for parameter `type`: auto. Please choose from one of: ['numpy', 'pil', 'filepath']
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],
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theme = gr.themes.Soft(),
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title = title,
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description = description,
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from pytorch_grad_cam.utils.model_targets import ClassifierOutputTarget
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from pytorch_grad_cam.utils.image import show_cam_on_image
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#ai-pict-detect
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from transformers import pipeline
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pipe = pipeline("image-classification", "nightfury/AI-picture-detector")
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def image_classifier(image):
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outputs = pipe(image)
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results = {}
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for result in outputs:
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results[result['label']] = result['score']
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return results
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#ai-pict-detect
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#gr.themes.Soft()
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#gr.themes.builder()
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description = "~ AI - ML implementation for fake and real image detection..."
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article = "<p style='text-align: center'>...</p>"
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demo = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label", title=title, description=description)
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demo.launch(show_api=False)
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interface = gr.Interface(
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fn=predict,
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inputs=[
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gr.outputs.Image(label="Face with Explainability", type="pil")
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#ValueError: Invalid value for parameter `type`: auto. Please choose from one of: ['numpy', 'pil', 'filepath']
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],
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theme = gr.themes.Soft(),
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title = title,
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description = description,
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