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from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity
import gradio as gr
def predict(im1, im2):
model = SentenceTransformer("sentence-transformers/clip-ViT-B-16")
embeddings = model.encode([im1,im2])
similarities = cosine_similarity(embeddings)
sim = similarities[0][1]
if sim > .8:
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) |