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feat: inital demo app
Browse filesSigned-off-by: Sahil <[email protected]>
- README.md +1 -1
- app.py +27 -0
- images/garbage-pickup.jpg +0 -0
- images/litter.jpg +0 -0
- images/pothole.jpg +0 -0
- images/wrong-park.jpg +0 -0
- requirements.txt +5 -0
README.md
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---
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title: Image Classification
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sdk: gradio
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---
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title: Image Classification
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emoji: 🖼️
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colorFrom: green
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colorTo: green
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sdk: gradio
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app.py
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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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images/garbage-pickup.jpg
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images/litter.jpg
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images/pothole.jpg
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images/wrong-park.jpg
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requirements.txt
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gradio==4.22.0
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tensorflow==2.16.1
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torch==2.2.2
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transformers==4.39.2
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sentencepiece==0.2.0
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