Remove commented out code.

examples/coffeescript/camera-face-detection.coffee

@@ -30,32 +30,14 @@ intervalId = setInterval(()->
     # otherwise it will fail when trying to do namedWindow.show()
     # and the image has width or height equal or less than 0.
     if im.width() > 0 and im.height() > 0
-      # We apply filters and effects to the frame we got from the
-      # camera to manipulate the video that we'll display.
-      # First we convert to grayscale.
-      #im.convertGrayscale()
-      # We then apply GaussianBlur.
-      # It takes an array of type double and size 2
-      # that indicates how strong the gaussian blur should be.
-      im.gaussianBlur([7,7])
-      # We then apply canny edge filtering.
-      # Params are lower and higher threshold and aperture size,
-      # although nodejs-opencv overwrite the aperture size param
-      # with 0. An update to consider it is needed.
-      #im.canny(0, 30, 3)
-      #gray = new cv.Matrix(src1.width(), src2.height())
-      #gray = im.copy()
-      #gray.convertGrayscale()
-
       im.detectObject('./haarcascades/haarcascade_frontalface_alt.xml', {}, (err, faces) ->
-        console.log("Faces length => #{ faces }")
         for face in faces
           im.rectangle([face.x, face.y], [face.x + face.width, face.y + face.height], [0,255,0], 2)
 
+        # We use the previously created namedWindow to display the
+        # video frame to wich we applied the blur and filter.
         namedWindow.show(im)
       )
-      # We use the previously created namedWindow to display the
-      # video frame to wich we applied the blur and filter.
 
     # Finally we get the key pressed on the window to terminate
     # execution of the program.

examples/coffeescript/camera-gaussian-effect.coffee

@@ -0,0 +1,57 @@
+cv = require 'opencv'
+
+# First we create a new VideoCapture object to get
+# video from the camera (0 for default camera)
+camera = new cv.VideoCapture(1)
+
+# we create a window to display the Video frames
+namedWindow = new cv.NamedWindow('Video',1)
+
+# We set an interval to retrieve frames from the
+# video source and we get the intervalId so we can
+# stop the program from the video feed window.
+intervalId = setInterval(()->
+
+  # camera.read allows us to retrieve the current
+  # frame to be displayed in the video window.
+  camera.read((err, im) ->
+    # We can check for errors and even break the
+    # program execution if an error is detected here.
+    console.log "The err ==>#{ err }" if err
+
+    # There is no need to display the image width or Height
+    # but I leave this here in case anyone needs to check them.
+    #console.log("Width: #{im.width()}")
+    #console.log("height: #{im.height()}")
+
+    # Before working with the frame we need to check the image
+    # is already available and has a width and height greater than 0,
+    # otherwise it will fail when trying to do namedWindow.show()
+    # and the image has width or height equal or less than 0.
+    if im.width() > 0 and im.height() > 0
+      # We apply filters and effects to the frame we got from the
+      # camera to manipulate the video that we'll display.
+      # First we convert to grayscale.
+      im.convertGrayscale()
+      # We then apply GaussianBlur.
+      # It takes an array of type double and size 2
+      # that indicates how strong the gaussian blur should be.
+      im.gaussianBlur([7,7])
+      # We then apply canny edge filtering.
+      # Params are lower and higher threshold and aperture size,
+      # although nodejs-opencv overwrite the aperture size param
+      # with 0. An update to consider it is needed.
+      im.canny(0, 30, 3)
+
+      # We use the previously created namedWindow to display the
+      # video frame to wich we applied the blur and filter.
+      namedWindow.show(im)
+
+    # Finally we get the key pressed on the window to terminate
+    # execution of the program.
+    res = namedWindow.blockingWaitKey(0, 20)
+
+    # In this case I terminate the program if any key is pressed.
+    if res >= 0 then clearInterval(intervalId)
+  )
+, 50)