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()