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Update app.py

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  1. app.py +22 -1
app.py CHANGED
@@ -1,3 +1,24 @@
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  import gradio as gr
 
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- gr.load("models/umm-maybe/AI-image-detector").launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  import gradio as gr
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+ from transformers import pipeline
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+ pipe = pipeline("image-classification", "umm-maybe/AI-image-detector")
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+
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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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+
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+ title = "Maybe's AI Art Detector"
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+ description = """
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+ This app is a proof-of-concept demonstration of using a ViT model to predict whether an artistic image was generated using AI.
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+ It was created in October 2022, and as such, the training data did not include any samples generated by Midjourney 5, SDXL, or DALLE-3. It still may be able to correctly identify samples from these more recent models due to being trained on outputs of their predecessors.
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+ Furthermore the intended scope of this tool is artistic images; that is to say, it is not a deepfake photo detector, and general computer imagery (webcams, screenshots, etc.) may throw it off.
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+ In general, this tool can only serve as one of many potential indicators that an image was AI-generated. Images scoring as very probably artificial (e.g. 90% or higher) could be referred to a human expert for further investigation, if needed.
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+ For more information please see the blog post describing this project at:
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+ https://medium.com/@matthewmaybe/can-an-ai-learn-to-identify-ai-art-545d9d6af226
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+ """
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+
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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)