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import matplotlib.pyplot as plt
from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity
import gradio as gr
model = SentenceTransformer("clip-ViT-B-16")
def predict(im1, im2):
# ANSWER HERE
embeddings = model.encode([im1,im2])
cos_sim = cosine_similarity(embeddings)
sim = cos_sim[0][1]
if sim > 0.80:# THRESHOLD HERE
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()
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