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import matplotlib.pyplot as plt |
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from sentence_transformers import SentenceTransformer |
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from sklearn.metrics.pairwise import cosine_similarity |
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import gradio as gr |
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model = SentenceTransformer("clip-ViT-B-16") |
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def predict(im1, im2): |
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embeddings = model.encode([im1,im2]) |
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cos_sim = cosine_similarity(embeddings) |
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sim = cos_sim[0][1] |
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if sim > 0.90: |
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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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interface = gr.Interface(fn=predict, |
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inputs= [gr.Image(type="pil", source="webcam"), |
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gr.Image(type="pil",source="webcam")], |
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title="FaceID App", |
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description="This is a FaceID app using Sentence Transformer as part of week 3 end to end vision application project on CoRise by Abubakar Abid!", |
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outputs= [gr.Number(label="Similarity"), |
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gr.Textbox(label="Message")] |
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) |
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interface.launch() |
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