fix function

app.py

@@ -16,23 +16,27 @@ no_face_detection_alert = "Cannot Detect Face"
 low_confidence_alert = "Cannot Detect Emotion"
 
 # Define the predict_emotion function
-for (x, y, w, h) in faces:
-	face = gray[y:y+h, x:x+w]
-	face = cv2.resize(face, (48, 48), interpolation = cv2.INTER_AREA)
-	if np.sum([face])!=0:
-		face = face.astype('float')/255.0
-		face = tf.keras.utils.img_to_array(face)
-		face = np.expand_dims(face, axis=0)
-		prediction = model.predict(face)
-		if any(prob >.5 for prob in prediction[0]):
-			emotion = emotions[np.argmax(prediction)]
-			cv2.putText(frame, emotion, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (128, 128, 0), 2)
-			cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 0), 2)
+
+def predict_emotion(frame):
+	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+	faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+	for (x, y, w, h) in faces:
+		face = gray[y:y+h, x:x+w]
+		face = cv2.resize(face, (48, 48), interpolation = cv2.INTER_AREA)
+		if np.sum([face])!=0:
+			face = face.astype('float')/255.0
+			face = tf.keras.utils.img_to_array(face)
+			face = np.expand_dims(face, axis=0)
+			prediction = model.predict(face)
+			if any(prob >.5 for prob in prediction[0]):
+				emotion = emotions[np.argmax(prediction)]
+				cv2.putText(frame, emotion, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (128, 128, 0), 2)
+				cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 0), 2)
+			else:
+				cv2.putText(frame, low_confidence_alert, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 69, 255),
+	                                2)
 		else:
-			cv2.putText(frame, low_confidence_alert, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 69, 255),
-                                2)
-	else:
-		cv2.putText(frame, no_face_detection_alert, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 69, 255), 2)
+			cv2.putText(frame, no_face_detection_alert, (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 69, 255), 2)
 
 return frame