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Create app.py
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app.py
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from turtle import title
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import gradio as gr
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from transformers import pipeline
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import numpy as np
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from PIL import Image
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pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")
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def shot(image, labels_text):
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PIL_image = Image.fromarray(np.uint8(image)).convert('RGB')
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labels = labels_text.split(",")
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res = pipe(images=PIL_image,
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candidate_labels=labels,
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hypothesis_template= "This is a photo of a {}")
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return {dic["label"]: dic["score"] for dic in res}
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iface = gr.Interface(shot,
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["image", "text"],
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"label",
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description="Ajouter une image avc une liste de labels séparées par la virgule",
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title="Zero-shot Image Classification")
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iface.launch()
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