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import matplotlib.pyplot as plt
import gradio as gr
from sklearn.metrics.pairwise import cosine_similarity
from sentence_transformers import SentenceTransformer
model = SentenceTransformer(f'sentence-transformers/clip-ViT-L-14')
def predict(im1, im2):
embeddings = model.encode([im1, im2])
sim = cosine_similarity(embeddings[0].reshape(1, -1), embeddings[1].reshape(1, -1))[0][0]
if sim > 0.89:
return sim, "SAME PERSON, UNLOCK PHONE"
else:
return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
interface = gr.Interface(fn=predict,
inputs= [gr.Image(type="pil", source="webcam"),
gr.Image(type="pil", source="webcam")],
outputs= [gr.Number(label="Similarity"),
gr.Textbox(label="Message")]
)
interface.launch(debug=True) |