Update app.py

app.py

@@ -1,12 +1,8 @@
-
 import gradio as gr
 import cv2
 from deepface import DeepFace
 import numpy as np
 
-# For Colab-specific display
-from google.colab.patches import cv2_imshow
-
 # Function to predict emotion from an image
 def predict_emotion_image(image):
     try:
@@ -34,6 +30,11 @@ def predict_emotion_video(video):
         # Initialize variables to store detected emotions
         detected_emotions = []
         
+        # Define codec and create VideoWriter object to save the output video
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')  # Codec for .mp4
+        output_filename = "output_video.mp4"
+        out = cv2.VideoWriter(output_filename, fourcc, 20.0, (int(cap.get(3)), int(cap.get(4))))
+        
         # Processing each frame of the video
         while True:
             ret, frame = cap.read()
@@ -62,16 +63,12 @@ def predict_emotion_video(video):
                 except Exception as e:
                     print(f"Error analyzing face in video: {e}")
             
-            # Display the frame in Colab
-            cv2_imshow(frame)
-            
-            # Break the loop if 'q' is pressed (ignored in Colab)
-            if cv2.waitKey(1) & 0xFF == ord('q'):
-                break
-        
+            # Write the frame with the detection to the output video
+            out.write(frame)
+
         # Release video resources
         cap.release()
-        cv2.destroyAllWindows()
+        out.release()
         
         # Combine detected emotions into a result string
         result_text = "Video Emotion Results: " + ", ".join(detected_emotions) if detected_emotions else "No emotion detected."