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app.py

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+import torch
+import gradio as gr
+import matplotlib.pyplot as plt
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+
+
+model = SentenceTransformer('clip-ViT-B-32')
+
+
+
+def predict(im1, im2):
+  embeding = model.encode([im1, im2])
+  sim = cosine_similarity(embeding)
+  sim = sim[0][1]
+  if sim > 0.78: # THRESHOLD HERE
+    return sim, "SAME PERSON, UNLOCK PHONE"
+  else:
+    return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
+
+
+
+title = 'Face ID'
+description = 'This model detects the similarity between two images and passes a command!'
+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=True)