app.py

import gradio as gr
import matplotlib.pyplot as plt
from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity

def predict(im1, im2):
  model, theta = SentenceTransformer('sentence-transformers/clip-ViT-L-14'), 0.55
  emb1, emb2 = model.encode(im1), model.encode(im2)
  sim = cosine_similarity(emb1.reshape(1, -1), emb2.reshape(1, -1))[0][0]

  if sim > theta:
    return sim, "User authenticated. Phone unlocked"
  else:
    return sim, "Unrecognized user. Unable to unlock phone"

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)