Compare with two images

api.py

@@ -0,0 +1,22 @@
+import requests
+
+
+class FacialSyncService:
+    def __init__(self, access_token: str) -> None:
+        self.access_token = access_token
+
+    def similarity(self, img1, img2) -> float:
+        res = requests.post(
+            "https://natexcvi-facialexpressionsyncservice.hf.space/similarity",
+            files={
+                # "image1": img_file_buffer.getvalue(),
+                "image1": img1,
+                # "image2": static_image.getvalue(),
+                "image2": img2,
+            },
+            params={
+                "token": self.access_token,
+            },
+        )
+        res.raise_for_status()
+        return res.json()["score"]

app.py

@@ -3,29 +3,29 @@ import stat
 import requests
 import streamlit as st
 
+from api import FacialSyncService
+
 access_token = st.experimental_get_query_params().get("token", [""])[0]
 
 if access_token == "":
     st.error("Access denied")
     st.stop()
 
-st.title("🤪 Facial Expression Sync Service")
+api = FacialSyncService(access_token)
 
-static_image = st.file_uploader("Upload image", type=["png", "jpg", "jpeg"])
-if static_image is not None:
-    st.image(static_image, caption="Uploaded image", width=200)
+st.title("🤪 Facial Expression Sync Service")
 
 img_file_buffer = st.camera_input("Take a picture")
 
-if img_file_buffer is not None and static_image is not None:
-    res = requests.post(
-        "https://natexcvi-facialexpressionsyncservice.hf.space/similarity",
-        files={
-            "image1": img_file_buffer.getvalue(),
-            "image2": static_image.getvalue(),
-        },
-        params={
-            "token": access_token,
-        },
-    )
-    st.metric("Similarity", res.json()["score"])
+st.write("Compare with static images")
+col1, col2 = st.columns(2)
+for col in [col1, col2]:
+    with col:
+        static_image = st.file_uploader("Upload image", type=["png", "jpg", "jpeg"])
+        if static_image is not None:
+            st.image(static_image, caption="Uploaded image", width=200)
+            if img_file_buffer is not None:
+                st.metric(
+                    "Similarity",
+                    f"{api.similarity(img_file_buffer.getvalue(), static_image.getvalue()):.2f}",
+                )