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import gradio as gr |
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import os |
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from transformers import pipeline |
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image_classifier = pipeline(task="zero-shot-image-classification", model="google/siglip-so400m-patch14-384") |
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labels = ['street sweeping', 'litter pickup', 'pothole repair', 'parking enforcement'] |
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def image_mod(image): |
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outputs = image_classifier(image, candidate_labels=labels) |
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result = {dic["label"]: dic["score"] for dic in outputs} |
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return result |
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app = gr.Interface( |
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image_mod, |
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gr.Image(type="pil"), |
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gr.Label(), |
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examples=[ |
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os.path.join(os.path.dirname(__file__), "images/garbage-pickup.jpg"), |
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os.path.join(os.path.dirname(__file__), "images/litter.jpg"), |
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os.path.join(os.path.dirname(__file__), "images/wrong-park.jpg"), |
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os.path.join(os.path.dirname(__file__), "images/pothole.jpg"), |
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], |
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) |
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if __name__ == "__main__": |
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app.launch() |
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