Computer vision toolbox.

face_detect.py

@@ -1,4 +1,34 @@
-""" Experiment with face detection and image filtering using OpenCV """
+""" Experiment with face detection and image filtering using OpenCV. This is
+mostly copied code, though I tried to look through the docs and understand
+what is going on. I made a rather silly annoyed face for the rectangle."""
 
 import cv2
-import numpy as np
+import numpy as np
+
+cap = cv2.VideoCapture(0)
+
+while(True):
+    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))
+        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))
+            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.line(frame,(x+w/4,y+h*3/4),(x+w*3/4,y+h*3/4),(0,0,0),3)
+
+    # 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()