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import gradio as gr
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from transformers import pipeline
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vit_classifier = pipeline("image-classification", model="LindiSimon/vit-beans-model")
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clip_detector = pipeline(model="openai/clip-vit-large-patch14", task="zero-shot-image-classification")
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labels_beans = ["angular_leaf_spot", "bean_rust", "healthy"]
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def classify_bean(image):
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vit_results = vit_classifier(image)
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vit_output = {result['label']: result['score'] for result in vit_results}
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clip_results = clip_detector(image, candidate_labels=labels_beans)
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clip_output = {result['label']: result['score'] for result in clip_results}
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return {"ViT Classification": vit_output, "CLIP Zero-Shot Classification": clip_output}
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examples = [["example_input.png"]]
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iface = gr.Interface(
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fn=classify_bean,
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inputs=gr.Image(type="filepath"),
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outputs=gr.JSON(),
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title="Bean Disease Classification",
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description="Vergleich eines trainierten ViT-Modells mit CLIP für Bean-Disease-Klassifikation.",
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examples=examples
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)
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iface.launch()
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