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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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import spaces |
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pipe = pipeline("zero-shot-image-classification", model="patrickjohncyh/fashion-clip") |
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images="dog.jpg" |
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@spaces.GPU |
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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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examples=[["dog.jpg", "dog,cat,bird"], |
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["germany.jpg", "germany,belgium,colombia"], |
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["colombia.jpg", "germany,belgium,colombia"]], |
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description="Add a picture and a list of labels separated by commas", |
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title="Zero-shot Image Classification") |
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iface.launch() |
