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

model = SentenceTransformer("sentence-transformers/clip-ViT-L-14")

def predict(im1, im2):
  embeddings = model.encode([im1, im2])
  sim = cosine_similarity(embeddings[0][None,:], embeddings[1][None,:])[0][0]
  # ANSWER HERE
  if sim > 0.78:
    return sim, "SAME PERSON, UNLOCK PHONE"
  else:
    return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
    
    
title = "Face ID"
description = "Upload two selfies and find out if they are of the same person."
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")],
                         title=title,
                         description=description
                         )

interface.launch(debug=False)