fix format

app.py

@@ -20,19 +20,19 @@ 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),
+		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, no_face_detection_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)
 
 return frame