louise submits opencv toolbox

face_detect.py

@@ -1,4 +1,34 @@
 """ Experiment with face detection and image filtering using OpenCV """
 
 import cv2
-import numpy as np
+import numpy as np
+
+cap = cv2.VideoCapture(0)
+# this is for recognizing faces and putting a box around them
+face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml')
+# this is for blurring inside the aforementioned box
+kernel = np.ones((21, 21), '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.rectangle(frame, (x, y), (x+w, y+h), (0, 0, 255))
+        # draw the mouth
+        cv2.ellipse(frame, (int(x+w/2), int(y+h/1.4)), (int(w/5), int(y/6)), 0, 0, 180, 0, 10, 1)
+        # draw the scleras
+        cv2.circle(frame, (int(x+w/4), int(y+h/3)), w/10, (255,255,255), -1)
+        cv2.circle(frame, (int(x+3*w/4), int(y+h/3)), w/10, (255,255,255), -1)
+        # draw the pupils
+        cv2.circle(frame, (int(x+w/4), int(y+h/3)), w/30, 0, -1)
+        cv2.circle(frame, (int(x+3*w/4), int(y+h/3)), w/30, 0, -1)
+    # display resulting frame
+    cv2.imshow('frame', frame)
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+# release capture when everything done
+cap.release()
+cv2.destroyAllWindows()