Update app.py

app.py

@@ -1,3 +1,6 @@
+# code adapted from Sefik Ilkin Serengil's Facial Expression Recognition with Keras tutorial
+# https://raw.githubusercontent.com/serengil/tensorflow-101/master/python/emotion-analysis-from-video.py
+
 import gradio as gr
 import cv2
 import numpy as np
@@ -14,10 +17,6 @@ emotions = ('angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral')
 
 # Define the frame scaling factor
 scaling_factor = 1.0
-
-def blur_image(img):
-  blur = cv2.blur(img,(10, 10))
-  return blur
   
 def process_image(img):
   # Resize the frame
@@ -57,10 +56,9 @@ def process_image(img):
 
 interface = gr.Interface(
   fn = process_image,
-  #inputs='image',
-  inputs="webcam",
+  inputs='webcam',
   outputs='image',
-  title='Facial Expression',
-  description='Facial expression detection test')
+  title='Facial Expression Detection',
+  description='Simple facial expression detection example with OpenCV, using a CNN model pre-trained on the FER 2013 dataset.')
   
 interface.launch()