Rename emotion.py to app.py

emotion.py → app.py

@@ -1,4 +1,6 @@
 import cv2
+import gradio as gr
+import numpy as np
 from deepface import DeepFace
 
 # Load the pre-trained emotion detection model
@@ -10,13 +12,7 @@ emotion_labels = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutr
 # Load face cascade classifier
 face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
 
-# Start capturing video
-cap = cv2.VideoCapture(0)
-
-while True:
-    # Capture frame-by-frame
-    ret, frame = cap.read()
-
+def predict_emotion(frame):
     # Convert frame to grayscale
     gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
@@ -45,13 +41,8 @@ while True:
         cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
         cv2.putText(frame, emotion, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
 
-    # Display the resulting frame
-    cv2.imshow('Real-time Emotion Detection', frame)
-
-    # Press 'q' to exit
-    if cv2.waitKey(1) & 0xFF == ord('q'):
-        break
+    return frame
 
-# Release the capture and close all windows
-cap.release()
-cv2.destroyAllWindows()
+# Gradio UI
+iface = gr.Interface(fn=predict_emotion, inputs="webcam", outputs="image")
+iface.launch()