Update app.py

app.py

@@ -3,7 +3,7 @@ from PIL import Image
 import numpy as np
 import cv2 
 import requests
-
+from gradio_client import Client
 import face_recognition
 import os
 from datetime import datetime
@@ -62,17 +62,24 @@ if img_file_buffer is not None:
          matchIndex = np.argmin(faceDis)
 
          if matches[matchIndex]:
-             name = classnames[matchIndex]
-             st.write(name)
-             y1, x2, y2, x1 = faceLoc
-             y1, x2, y2, x1 = y1*4,x2*4,y2*4,x1*4
-             cv2.rectangle(image,(x1,y1),(x2,y2),(0,255,0),2)
-             cv2.rectangle(image,(x1,y2-35),(x2,y2),(0,255,0),cv2.FILLED)
-             cv2.putText(image,name,(x1+6,y2-6),cv2.FONT_HERSHEY_COMPLEX,1,(255, 255, 255),2)
-
-             ##############
-             url = "https://kiwi-whispering-plier.glitch.me/update" 
-             
-             data = {
-                     'name': name,
-             }
+            name = classnames[matchIndex]
+            st.write(name)
+            y1, x2, y2, x1 = faceLoc
+            y1, x2, y2, x1 = y1*4,x2*4,y2*4,x1*4
+            cv2.rectangle(image,(x1,y1),(x2,y2),(0,255,0),2)
+            cv2.rectangle(image,(x1,y2-35),(x2,y2),(0,255,0),cv2.FILLED)
+            cv2.putText(image,name,(x1+6,y2-6),cv2.FONT_HERSHEY_COMPLEX,1,(255, 255, 255),2)
+            client = Client("https://rahulsinghpundir-facial-expression.hf.space/")
+            result = client.predict(
+                            "https://raw.githubusercontent.com/gradio-app/gradio/main/test/test_files/bus.png",	# str (filepath or URL to image) in 'img' Image component
+                            api_name="/predict"
+            )
+            if result == "happy":
+                 ##############
+                 url = "https://kiwi-whispering-plier.glitch.me/update" 
+                 
+                 data = {
+                         'name': name,
+                 }
+            else:
+                st.write("Please smile")