Toolbox Completed

face_detect.py

@@ -1,4 +1,31 @@
 """ Experiment with face detection and image filtering using OpenCV """
 
+
+import numpy as np
 import cv2
-import numpy as np
+
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+kernel = np.ones((40, 40), 'uint8')
+
+cap = cv2.VideoCapture(0)
+
+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.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255))
+        #smile
+        cv2.ellipse(frame, (x+int(.5*w),y+int(.65*h)), (int(w/4), int(h/5)), 0, 0, 180, (140,109,40), 10)
+        #eyes
+        cv2.circle(frame, (int(x+.35*w), int(y+.4*h)), 20, (200, 106, 30), 10)
+        cv2.circle(frame, (int(x+.65*w), int(y+.4*h)), 20, (127, 103, 35), 10)
+    # 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()