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)