diff --git a/face_detect.py b/face_detect.py
deleted file mode 100755
index 247a4d1..0000000
--- a/face_detect.py
+++ /dev/null
@@ -1,4 +0,0 @@
-""" Experiment with face detection and image filtering using OpenCV """
-
-import cv2
-import numpy as np
\ No newline at end of file
diff --git a/image.py b/image.py
new file mode 100644
index 0000000..2016e4c
--- /dev/null
+++ b/image.py
@@ -0,0 +1,27 @@
+import cv2
+import numpy as np
+
+cap = cv2.VideoCapture('project.avi')
+
+while(cap.isOpened()):
+    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+    kernel = np.ones((21,21),'uint8')
+    ret, frame = cap.read()
+    faces = face_cascade.detectMultiScale(frame, scaleFactor=1.2, minSize=(20,20))
+
+    for (x,y,w,h) in faces:
+        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255))
+        frame[y:y+h,x:x+w,:] = cv2.dilate(frame[y:y+h,x:x+w,:], kernel)
+        cv2.circle(frame,(x+w/4,y+h*4/10),(w/16),(0,0,0),-1)
+        cv2.circle(frame,(x+w*3/4,y+h*4/10),(w/16),(0,0,0),-1)
+        cv2.line(frame,(x+w/4,y+h/5),(x+w/2,y+h*4/10),(0,0,0),3)
+        cv2.line(frame,(x+w*3/4,y+h/5),(x+w/2,y+h*4/10),(0,0,0),3)
+        cv2.ellipse(frame,(x + w/2, int(y + .75*h)),(50,25),0,0,180,(0, 0, 0), thickness=4)
+
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    cv2.imshow('frame',gray)
+    if cv2.waitKey(25) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()