add files from colab

app.py

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+import datasets
+import gradio as gr
+from sklearn.metrics.pairwise import cosine_similarity
+
+dataset = load_dataset("justina/celeb-identities")
+model = SentenceTransformer("sentence-transformers/clip-ViT-B-16")
+
+def predict(im1, im2):
+  image_embs = model.encode([im1, im2])
+  similarities = cosine_similarity(image_embs)
+  sim = similarities[0][1]
+  threshold = 0.65
+  if sim > threshold:
+    return sim, "SAME PERSON, UNLOCK PHONE"
+  else:
+    return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
+
+
+with gr.Blocks() as demo:
+  gr.Markdown("Based on two images, the goal is to recognize the similarities/differences between facial images and determine whether or not to unlock a phone based on a cosine similarity score.")
+              
+  with gr.Tab("Image"):
+    with gr.Row():  
+      with gr.Column():
+        img_inputs = [gr.Image(type="pil", source="upload"),
+                      gr.Image(type="pil", source="upload")]
+        examples = gr.Examples([["https://live.staticflickr.com/2883/33785597726_47880fa539_b.jpg","https://live.staticflickr.com/65535/49086637987_f7622c3345.jpg"],
+                                ["https://live.staticflickr.com/3423/3197571945_123937185f_b.jpg", "https://live.staticflickr.com/7259/7001667239_11cece02c8_b.jpg"],
+                                ["https://live.staticflickr.com/4015/4334237247_08af133b4b_b.jpg", "https://live.staticflickr.com/3701/9364116426_87b8918e9d_b.jpg"]],
+                               inputs=img_inputs)
+        btn = gr.Button("Run")
+      with gr.Column():
+        btn.click(fn=predict,
+            inputs=img_inputs, 
+            outputs=[gr.Number(label="Similarity"),
+                     gr.Textbox(label="Message")],
+            )
+      
+  with gr.Tab("Webcam"):
+    with gr.Row():  
+      with gr.Column():
+        img_inputs = [gr.Image(type="pil", source="webcam"), 
+                    gr.Image(type="pil", source="webcam")]
+        btn = gr.Button("Run")
+      with gr.Column():
+        btn.click(fn=predict,
+                inputs=img_inputs, 
+                outputs=[gr.Number(label="Similarity"),
+                        gr.Textbox(label="Message")],
+                )
+
+demo.launch(debug=True)

requirements.txt

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+datasets