notifications

1 files changed, 79 insertions, 25 deletions

diff --git a/cv-head-lock/autolock.py b/cv-head-lock/autolock.py
index a4f4bf9..acbbbc0 100644..100755
--- a/cv-head-lock/autolock.py
+++ b/cv-head-lock/autolock.py
@@ -1,3 +1,4 @@
+#!/usr/bin/python
 import cv2
 import time
 import logging
@@ -5,48 +6,101 @@ import dbus
 
 
 session_bus = dbus.SessionBus()
+notif_id = id(__name__) % (2**32)
+
+
+def get_dbus_object(dest, path, iface):
+    proxy = session_bus.get_object(dest, path)
+    return dbus.Interface(proxy, iface)
+
+
+def notify(summary, body):
+    notif = get_dbus_object("org.freedesktop.Notifications",
+                            "/org/freedesktop/Notifications",
+                            "org.freedesktop.Notifications")
+    notif.Notify("autolock", notif_id, "", summary, body, [], {}, 1)
+
+
+def close_notification():
+    notif = get_dbus_object("org.freedesktop.Notifications",
+                            "/org/freedesktop/Notifications",
+                            "org.freedesktop.Notifications")
+    notif.CloseNotification(notif_id)
 
 
 def tryLock():
-    DBUS_DEST = "org.mate.ScreenSaver"
-    DBUS_PATH = "/org/mate/ScreenSaver"
-    DBUS_IFACE = "org.mate.ScreenSaver"
-    proxy = session_bus.get_object(DBUS_DEST, DBUS_PATH)
-    screensaver = dbus.Interface(proxy, DBUS_IFACE)
-
-    if screensaver.Hello() == DBUS_DEST:
-        if not screensaver.GetActive():
-            logging.info("call Lock()")
-            screensaver.Lock()
+    try:
+        screensaver = get_dbus_object("org.mate.ScreenSaver",
+                                      "/org/mate/ScreenSaver",
+                                      "org.mate.ScreenSaver")
+        if screensaver.Hello() == "org.mate.ScreenSaver":
+            if not screensaver.GetActive():
+                logging.info("call Lock()")
+                screensaver.Lock()
+            else:
+                logging.debug("Is locked already")
         else:
-            logging.debug("Is locked already")
-    else:
-        logging.error("Mate-Screensaver doesn't answer our call")
+            logging.error("Mate-Screensaver doesn't answer our call")
+    except:
+        pass
 
 
 def detect(show_window=False):
-    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
+    haar_cascade = cv2.CascadeClassifier("xml/haarcascade_eye.xml")
     capture = cv2.VideoCapture(0)
     last_seen = time.time()
+    last_analysis = last_seen
     try:
         while True:
-            ret, frame = capture.read()
+            ret = capture.grab()
+
+            if time.time() - last_analysis < 0.5:
+                continue
+
+            ret, frame = capture.retrieve()
+            last_analysis = time.time()
             gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
-            faces = face_cascade.detectMultiScale(gray, 1.3, 5)
-            if len(faces) == 1:
+            matches = haar_cascade.detectMultiScale(gray, 1.3, 5)
+            if len(matches) >= 1:
+                close_notification()
                 last_seen = time.time()
-            elif time.time() - last_seen > 10:  # sec
-                tryLock()
-
-            for (x, y, w, h) in faces:
-                cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
-                roi_gray = gray[y:y+h, x:x+w]
-                roi_color = frame[y:y+h, x:x+w]
+            else:
+                timeout = (last_seen - time.time()) + 12
+                if timeout <= 10:
+                    notify("Autolocker:",
+                           "Activate screenlock in {:.0f}s".format(timeout))
+                if timeout <= 0:
+                    tryLock()
 
             if show_window:
+                gray = cv2.GaussianBlur(gray, (5, 5), 0)
+                gray = cv2.adaptiveThreshold(gray, 255,
+                                             cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
+                                             cv2.THRESH_BINARY, 11, 2)
+                for (x, y, w, h) in matches:
+                    cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+
+#                    roi = gray[y:(y+h), x:(x+w)]
+#                    if not roi != []: continue
+#                    print (x, y, w, h)
+#                    det = cv2.SimpleBlobDetector()
+#                    for blob in det.detect(roi):
+#                        cv2.circle(frame, (x+int(blob.pt[0]), y+int(blob.pt[1])), int(blob.size), (255,0,0))
+#                    circles = cv2.HoughCircles(roi, cv2.cv.CV_HOUGH_GRADIENT, 1, 20,
+#                              param1=40,param2=15,minRadius=4,maxRadius=min(w,h)/2)
+#                    if circles != None and len(circles) > 0:
+#                        circles = np.uint16(np.around(circles))
+#                        for circle in circles[0]:
+#                            center = (x + int(circle[0]), y + int(circle[1]))
+#                            cv2.circle(frame, center, int(circle[2]), (0,255,255))
+
                 cv2.imshow("img", frame)
-                if cv2.waitKey(500) >= 0:
+                cv2.imshow("gray", gray)
+
+                key = cv2.waitKey(1)
+                ctrl_mask = 0x40000
+                if key in [ctrl_mask | ord("q"), ctrl_mask | ord("w"), 27]:
                     break
             else:
                 time.sleep(0.3)