diff --git a/face_detect.py b/face_detect.py
index 247a4d1..2b9364a 100644
--- a/face_detect.py
+++ b/face_detect.py
@@ -1,4 +1,51 @@
 """ Experiment with face detection and image filtering using OpenCV """
 
 import cv2
-import numpy as np
\ No newline at end of file
+import numpy as np
+
+cap = cv2.VideoCapture(0)
+
+red = (0,0,255)
+white = (0,0,0)
+blue = (255,0,0)
+black = (255,255,255)
+
+
+while True:
+    # Capture frame-by-frame
+    ret, frame = cap.read()
+    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+    faces = face_cascade.detectMultiScale(frame, scaleFactor=1.2, minSize=(20, 20))
+    kernel = np.ones((21,21), 'uint8')
+
+    for (x, y, w, h) in faces:
+        frame[y:y+h, x:x+w, :] = cv2.dilate(frame[y:y+h, x:x+w, :], kernel)
+
+        # mouse
+        cv2.ellipse(frame,(int(x+w*0.5),int(y+h*0.65)),(100,50),0,0,180,red,-1)
+
+        # Nose
+        cv2.line(frame, (int(x+w*0.47), int(y+h*0.55)), (int(x+w*0.53), int(y+h*0.55)), black, 10)
+        cv2.line(frame, (int(x+w*0.5), int(y+h*0.55)), (int(x+w*0.5), int(y+h*0.4)), black, 10)
+
+        # eyes
+        cv2.circle(frame, (int(x+w*0.7), int(y+h*0.35)), 25, black, -1)
+        cv2.circle(frame, (int(x+w*0.3), int(y+h*0.35)), 25, black, -1)
+        cv2.circle(frame, (int(x+w*0.3), int(y+h*0.35)), 20, blue, -1)
+        cv2.circle(frame, (int(x+w*0.7), int(y+h*0.35)), 20, blue, -1)
+        cv2.circle(frame, (int(x+w*0.7), int(y+h*0.40)), 15, white, -1)
+        cv2.circle(frame, (int(x+w*0.3), int(y+h*0.40)), 15, white, -1)
+
+        # comments
+        font = cv2.FONT_HERSHEY_SIMPLEX
+        cv2.putText(frame,'You looks good!',(int(x+w*0.2),int(y+h*0.9)), font, 1,black,2)
+
+        # Display the resulting frame
+        cv2.imshow('frame', frame)
+
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+# When everything done, release the capture
+cap.release()
+cv2.destroyAllWindows()