Complete image processing toolbox

face_detect.py

@@ -1,4 +1,39 @@
-""" Experiment with face detection and image filtering using OpenCV """
+"""
+AVA LAKMAZAHERI
+IMAGE PROCESSING TOOLBOX
+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((100, 100), '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.ellipse(frame, (int(x+w/2), int(y+3*h/5)), (int(w/4),int(h/4)), 110, -90, 50, (0, 0, 0), 5)
+        cv2.circle(frame, (int(x+w/4), int(y+h/3)), 20, (255,255,255), -1)
+        cv2.circle(frame, (int(x+3*w/4), int(y+h/3)), 20, (255,255,255), -1)
+        cv2.circle(frame, (int(x+w/4), int(y+h/3)), 5, (0,0,0), -1)
+        cv2.circle(frame, (int(x+3*w/4), int(y+h/3)), 5, (0,0,0), -1)
+        cv2.line(frame, (int(x+w/2), int(y+2*h/3)), (int(x+w/2+10), int(y+2*h/3)), (0,0,0), 2)
+        cv2.line(frame, (int(x+w/2), int(y+2*h/3)), (int(x+w/2+10), int(y+h/2)), (0,0,0), 2)
+
+        cv2.ellipse(frame, (int(x + w/4), int(y + h/4+5)), (int(w/4),int(h/4)), 120, 90, 180, (0, 0, 0), 2)
+        cv2.ellipse(frame, (int(x + 3*w/4), int(y + h/4+5)), (int(w/4),int(h/4)), 120, 110, 200, (0, 0, 0), 2)
+
+    # 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()