turning in open CV toolbox

face_detect.py

@@ -1,4 +1,33 @@
-""" Experiment with face detection and image filtering using OpenCV """
+"""
+Author: Cedric Kim
+Experiment with face detection and image filtering using OpenCV """
 
+
+import numpy as np
 import cv2
-import numpy as np
+
+cap = cv2.VideoCapture(0)
+face_cascade = cv2.CascadeClassifier('/home/cedric/ToolBoxes/ToolBox-ComputerVision/haarcascade_frontalface_alt.xml')
+kernel = np.ones((50,50),'uint8')
+
+while(True):
+
+    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) ##blurs image
+        cv2.circle(frame, (x+w/2, y+h/2), (w/2), (0, 255, 0), (5))                  ##create head
+        cv2.circle(frame, (x+w/2 - 30, y+h/2 - 50), (6), (0, 0, 0), (5))            ##create eyes
+        cv2.circle(frame, (x+w/2 + 30, y+h/2 - 30), (6), (0, 0, 0), (5))
+        cv2.ellipse(frame, (x+w/2, y+h/2), (70, 50), 20, 90, 30, (0,0,0), (5))      ##create smile
+        #cv2.ellipse(frame,(256,256),(100,50),0,0,180,255,-1)
+        #cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255)) ##draws the rectangle
+     # 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()