Updated from colab

app.py

@@ -0,0 +1,55 @@
+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-L-14')
+
+def predict(im1, im2):
+  embeding = model.encode([im1, im2])
+  sim = cosine_similarity(embeding)
+  sim = sim[0][1]
+  if sim > 0.75:
+    return sim, "SAME PERSON, UNLOCK PHONE"
+  else:
+    return sim, "DIFFERENT PEOPLE, DON'T UNLOCK"
+
+
+title="Face-id Application Demo"
+description = "Upload similar/different images to compare Image similarity for face-id demo"
+article = """
+            - Select an image from the examples provided as demo image
+            - Click submit button to make Image classification
+            - Click clear button to try new Image for classification
+          """
+
+img_upload = gr.Interface(
+    fn=predict, 
+    inputs= [gr.Image(type="pil", source="upload"), 
+             gr.Image(type="pil", source="upload")], 
+    outputs= [gr.Number(label="Similarity"),
+              gr.Textbox(label="Message")],
+    title=title,
+    description=description,
+    article=article,
+    examples=[['examples/img1.jpg', 'examples/img2.jpg'],
+              ['examples/img1.jpg', 'examples/img3.jpg']]
+    )
+
+webcam_upload = 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,
+    article=article,
+    )
+
+face_id = gr.TabbedInterface(
+    [img_upload, webcam_upload], 
+    ["Upload-Image", "Use Webcam"])
+
+face_id.launch(debug=True)

requirements.txt

@@ -0,0 +1,3 @@
+torch
+transformers
+sentence-transformers