diff --git a/face_detect.py b/face_detect.py
index 247a4d1..91c50af 100755
--- a/face_detect.py
+++ b/face_detect.py
@@ -1,4 +1,33 @@
-""" Experiment with face detection and image filtering using OpenCV """
-
+import numpy as np
 import cv2
-import numpy as np
\ No newline at end of file
+
+cap = cv2.VideoCapture(0)
+
+face_cascade = cv2.CascadeClassifier('/home/andrewholmes/haarcascade_frontalface_alt.xml')
+
+kernel = np.ones((41,41),'uint8')
+
+while(True):
+	# Capture frame-by-frame
+	ret, frame = cap.read()
+	faces = face_cascade.detectMultiScale(frame, scaleFactor=1.2, minSize=(20,20))
+	for (x,y,w,h) in faces:
+		frame[y:y+h,x:x+w,:] = cv2.dilate(frame[y:y+h,x:x+w,:], kernel)
+		cv2.circle(frame, (x+w/3,y+h/3), 30, (255,255,255), -1)
+		cv2.circle(frame, (x+2*w/3,y+h/3), 30, (255,255,255), -1)
+		cv2.circle(frame, (x+w/3,y+h/3+15), 15, (0,0,0), -1)
+		cv2.circle(frame, (x+2*w/3,y+h/3-8), 15, (0,0,0), -1)
+		cv2.ellipse(frame, (x+w/2,y+2*h/3,), (50,70),0,0,180,(0,0,0),-1)
+		cv2.ellipse(frame, (x+w/2,y+2*h/3,), (50,70),0,0,180,(0,0,0),-1)
+		cv2.ellipse(frame, (x+w/2,y+2*h/3,), (25,70),0,0,180,(180,105,255),-1)
+		#cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255))
+
+	# 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()
+