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app.py

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+import gradio as gr
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+
+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")]
+                         )