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app.py

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+import gradio as gr
+from sklearn.metrics.pairwise import cosine_similarity
+from sentence_transformers import SentenceTransformer
+from PIL import Image
+import cv2
+
+def predict(im1, im2,thresh,model_name):
+  im1_face = Image.open(im1)
+  im2_face = Image.open(im2)
+
+  model = load_model(model_name)
+
+  sim=cosine_similarity(model.encode([im1_face,im2_face]))[0][1]
+
+  if sim > thresh:
+    return sim, "SAME PERSON, UNLOCK PHONE"
+  else:
+    return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
+
+def load_model(model_name):
+  model = SentenceTransformer(model_name)
+
+title = """<h1 id="title">FaceID for Facial Recognition with Face Detector</h1>"""
+
+models = ['clip-ViT-B-16','clip-ViT-B-32','clip-ViT-L-14']
+
+twitter_link = """
+[![](https://img.shields.io/twitter/follow/nickmuchi?label=@nickmuchi&style=social)](https://twitter.com/nickmuchi)
+"""
+
+css = '''
+h1#title {
+  text-align: center;
+}
+'''
+demo = gr.Blocks(css=css)
+
+with demo:
+    gr.Markdown(title)
+    gr.Markdown(twitter_link)
+    model_options = gr.Dropdown(choices=models,label='Embedding Models',value=models[-1],show_label=True)
+    thresh = gr.Slider(minimum=0.5,maximum=1,value=0.85,step=0.1,label='Confidence')
+    
+    with gr.Tabs():
+        with gr.TabItem("Face ID with No Face Detection"):
+            
+            with gr.Row():
+                with gr.Column():
+                    nd_image_input_1 = gr.Image(label='Image 1',type='pil',source='webcam')
+                    nd_image_input_2 = gr.Image(label='Image 2',type='pil',source='webcam')
+                    
+                with gr.Column():
+                    sim = gr.Number(label="Similarity")
+                    msg = gr.Textbox(label="Message")
+                
+            nd_but = gr.Button('Verify')
+                            
+        with gr.TabItem("Face ID with Face Detector"):
+            
+            with gr.Row():
+                with gr.Column():
+                    fd_image_1 = gr.Image(label='Image 1',type='pil',source='webcam')
+                    fd_image_2 = gr.Image(label='Image 2',type='pil',source='webcam')
+
+                with gr.Column():
+                    face_1 = gr.Image(label='Face Detected 1',type='filepath')
+                    face_2 = gr.Image(label='Face Detected 2',type='filepath')
+                    fd_image_1.change(extract_face,fd_image_1,face_1)
+                    fd_image_1.change(extract_face,fd_image_1,face_1)
+      
+                            
+            with gr.Row():
+                with gr.Column():
+                    sim_1 = gr.Number(label="Similarity")
+                    msg_1 = gr.Textbox(label="Message")
+                                                    
+            fd_but = gr.Button('Verify')          
+                
+            
+    nd_but.click(predict,inputs=[nd_image_input_1,nd_image_input_2,thresh,model_options],outputs=[sim,msg],queue=True)
+    fd_but.click(predict,inputs=[face_1,face_2,thresh,model_options],outputs=[sim_1,msg_1],queue=True)
+# 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(debug=True)
+
+demo.launch(debug=True,enable_queue=True)