tadeyina commited on
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e828d18
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Upload app.py

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  1. app.py +29 -0
app.py ADDED
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+ from sklearn.metrics.pairwise import cosine_similarity
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+ from sentence_transformers import SentenceTransformer
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+ import datasets
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+ import gradio as gr
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+
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+ model = SentenceTransformer('clip-ViT-B-16')
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+ dataset = datasets.load_dataset('tadeyina/celeb-identities')
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+
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+ def predict(im1, im2):
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+
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+ embeddings = model.encode([im1, im2])
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+ sim = cosine_similarity(embeddings)
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+ sim = sim[0, 1]
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+ if sim > 0.8:
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+ return sim, "SAME PERSON, UNLOCK PHONE"
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+ else:
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+ return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
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+
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+
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+ interface = gr.Interface(fn=predict,
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+ inputs= [gr.Image(value = dataset['train']['image'][0], type="pil", source="webcam"),
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+ gr.Image(value = dataset['train']['image'][1], type="pil", source="webcam")],
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+ outputs= [gr.Number(label="Similarity"),
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+ gr.Textbox(label="Message")],
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+ title = 'Face ID',
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+ description = 'This app uses emage embeddings and cosine similarity to function as a Face ID application. Cosine similarity is used, so it ranges from -1 to 1.'
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+ )
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+
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+ interface.launch(debug=True)