Merge pull request #74 from hybridgroup/opencv-examples

Added Opencv examples.

examples/opencv/display-camera-feed.coffee

@@ -0,0 +1,44 @@
+Cylon = require('../..')
+
+Cylon.robot
+  connection:
+    name: 'opencv', adaptor: 'opencv'
+
+  devices: [
+    { name: 'window', driver: 'window' }
+    {
+      name: 'camera',
+      driver: 'camera',
+      camera: 1,
+      haarcascade: "#{ __dirname }/examples/opencv/haarcascade_frontalface_alt.xml"
+    } # Default camera is 0
+  ]
+
+  work: (my) ->
+    my.camera.once('cameraReady', ->
+      console.log('The camera is ready!')
+      # We listen for frame ready event, when triggered
+      # we display the frame/image passed as an argument
+      # and we tell the window to wait 40 milliseconds
+      my.camera.on('frameReady', (err, im) ->
+        console.log("FRAMEREADY!")
+        my.window.show(im, 40)
+        #my.camera.readFrame()
+      )
+      # Here we have two options to start reading frames from
+      # the camera feed.
+      # 1. As fast as possible triggering the next frame read
+      #    in the listener for frameReady, if you need video
+      #    as smooth as possible uncomment #my.camera.readFrame()
+      #    in the listener above and the one below this comment.
+      #
+      # my.camera.readFrame()
+      #
+      # 2. Use an interval of time to try and get aset amount
+      #    of frames per second  (FPS), in the next example
+      #    we are trying to get 1 frame every 50 milliseconds
+      #    (20 FPS).
+      #
+      every 50, my.camera.readFrame
+    )
+.start()

examples/opencv/display-image-from-camera.coffee

@@ -0,0 +1,20 @@
+Cylon = require('../..')
+
+Cylon.robot
+  connection:
+    name: 'opencv', adaptor: 'opencv'
+
+  devices: [
+    { name: 'window', driver: 'window' }
+    { name: 'camera', driver: 'camera', camera: 1 }
+  ]
+
+  work: (my) ->
+    my.camera.on('cameraReady', ->
+      console.log('THE CAMERA IS READY!')
+      my.camera.on('frameReady', (err, im) ->
+        my.window.show(im, 5000)
+      )
+      my.camera.readFrame()
+    )
+.start()

examples/opencv/face-detection.coffee

@@ -0,0 +1,58 @@
+Cylon = require('../..')
+
+Cylon.robot
+  connection:
+    name: 'opencv', adaptor: 'opencv'
+
+  devices: [
+    { name: 'window', driver: 'window' }
+    {
+      name: 'camera',
+      driver: 'camera',
+      camera: 1,
+      haarcascade: "#{ __dirname }/haarcascade_frontalface_alt.xml"
+    } # Default camera is 0
+  ]
+
+  work: (my) ->
+    # We setup our face detection once the camera is ready to
+    # siplays images, we used once to make sure the event listeners
+    # are only registered once.
+    my.camera.once('cameraReady', ->
+      console.log('The camera is ready!')
+      # We add a listener for the facesDetected event
+      # here we will get (err, image/frame, faces) params.
+      # The faces param is an array conaining any face detected
+      # in the frame (im).
+      my.camera.on('facesDetected', (err, im, faces) ->
+        # We loop trhough the faces and manipulate the image
+        # to display a square in the coordinates for the detected
+        # faces.
+        for face in faces
+          im.rectangle([face.x, face.y], [face.x + face.width, face.y + face.height], [0,255,0], 2)
+        # Once the image has been updated with rectangles around
+        # detected faces we display it in our window.
+        my.window.show(im, 40)
+
+        # After displaying the updated image we trigger another
+        # frame read to ensure the fastest processing possible.
+        # We could also use an interval to try and get a set
+        # amount of processed frames per second, see below.
+        my.camera.readFrame()
+      )
+      # We listen for frameReady event, when triggered
+      # we start the face detection passsing the frame
+      # that we jsut got.
+      my.camera.on('frameReady', (err, im) ->
+        my.camera.detectFaces(im)
+      )
+
+      # Here we could also try to get a set amount of processed FPS
+      # by setting an interval and reading frames every set amount
+      # of time. We could just uncomment the next line and commenting
+      # out the my.camera.readFrame() in the facesDetected listener
+      # as well as the one two lines below.
+      #every 150, my.camera.readFrame
+      my.camera.readFrame()
+    )
+.start()