Lauren Pudvan - Turning in my computer vision toolbox

face_detect.py

@@ -1,4 +1,29 @@
 """ Experiment with face detection and image filtering using OpenCV """
 
 import cv2
-import numpy as np
+import numpy as np
+
+cap = cv2.VideoCapture(0)
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+kernel = np.ones((10,10),'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) # Blurs Face
+    	cv2.circle(frame, (x+w/2, y+h/2), (w/2), (40, 40, 40), (5)) # Cirlce around face
+    	cv2.circle(frame, (x+w/2 - 55, y+h/2 - 23), (6), (0, 0, 0), (5)) # Left eye
+    	cv2.circle(frame, (x+w/2 + 55, y+h/2 - 23), (6), (0, 0, 0), (5)) # Right eye
+    	cv2.ellipse(frame, (x+w/2, y+h/2 + 20), (70, 50), 20, 90, 30, (0,0,150), (5)) # Smile
+#    	cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255)) # Was used to draw rectangle around face
+
+    # 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()