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Remove OpenCV examples 

They live in hybridgroup/cylon-opencv now.
This commit is contained in:
Andrew Stewart 2014-03-06 11:15:52 -08:00
parent 267c9fc7f6
commit f3135bfd2c
15 changed files with 0 additions and 78878 deletions
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examples/opencv_display_camera/.DS_Store vendored
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examples/opencv_display_camera/display-camera-feed.coffee
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Cylon = require('../..')
Cylon.robot
connection:
name: 'opencv', adaptor: 'opencv'
devices: [
{ name: 'window', driver: 'window' }
{
name: 'camera',
driver: 'camera',
camera: 0,
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 the frameReady event, when triggered
# we display the frame/image passed as an argument to
# the listener function, 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.
# Also comment out the `every 50, my.camera.readFrame`
# at the end of the comments.
#
# my.camera.readFrame()
#
# 2. `Use an interval of time`: to try to get a set amount
# of frames per second (FPS), we use an `every 50, myFunction`,
# we are trying to get 1 frame every 50 milliseconds
# (20 FPS), hence the following line of code.
#
every 50, my.camera.readFrame
)
.start()

29
examples/opencv_display_camera/display-camera-feed.js
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var Cylon = require('../..');
Cylon.robot({
connection: {
name: 'opencv',
adaptor: 'opencv'
},
devices: [
{
name: 'window',
driver: 'window'
}, {
name: 'camera',
driver: 'camera',
camera: 0,
haarcascade: "" + __dirname + "/examples/opencv/haarcascade_frontalface_alt.xml"
}
],
work: function(my) {
return my.camera.once('cameraReady', function() {
console.log('The camera is ready!');
my.camera.on('frameReady', function(err, im) {
console.log("FRAMEREADY!");
return my.window.show(im, 40);
});
return every(50, my.camera.readFrame);
});
}
}).start();

62
examples/opencv_display_camera/display-camera-feed.litcoffee
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@ -1,62 +0,0 @@
# Display Camera
First, let's import Cylon:
Cylon = require('../..')
Now that we have Cylon imported, we can start defining our robot
Cylon.robot
Let's define the connections and devices:
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
]
Now that Cylon knows about the necessary hardware we're going to be using, we'll
tell it what work we want to do:
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 to
# the listener function, 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.
# Also comment out the `every 50, my.camera.readFrame`
# at the end of the comments.
#
# my.camera.readFrame()
#
# 2. `Use an interval of time`: to try to get a set amount
# of frames per second (FPS), we use an `every 50, myFunction`,
# we are trying to get 1 frame every 50 milliseconds
# (20 FPS), hence the following line of code.
#
every 50, my.camera.readFrame
)
Now that our robot knows what work to do, and the work it will be doing that
hardware with, we can start it:
.start()

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examples/opencv_display_camera/haarcascade_frontalface_alt.xml
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examples/opencv_display_image/.DS_Store vendored
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examples/opencv_display_image/display-image-from-camera.coffee
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Cylon = require('../..')
Cylon.robot
connection:
name: 'opencv', adaptor: 'opencv'
devices: [
{ name: 'window', driver: 'window' }
{ name: 'camera', driver: 'camera', camera: 0 }
]
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()

27
examples/opencv_display_image/display-image-from-camera.js
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@ -1,27 +0,0 @@
var Cylon = require('../..');
Cylon.robot({
connection: {
name: 'opencv',
adaptor: 'opencv'
},
devices: [
{
name: 'window',
driver: 'window'
}, {
name: 'camera',
driver: 'camera',
camera: 0
}
],
work: function(my) {
return my.camera.on('cameraReady', function() {
console.log('THE CAMERA IS READY!');
my.camera.on('frameReady', function(err, im) {
return my.window.show(im, 5000);
});
return my.camera.readFrame();
});
}
}).start();

36
examples/opencv_display_image/display-image-from-camera.litcoffee
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@ -1,36 +0,0 @@
# Display Image from Camera
First, let's import Cylon:
Cylon = require('../..')
Now that we have Cylon imported, we can start defining our robot
Cylon.robot
Let's define the connections and devices:
connection:
name: 'opencv', adaptor: 'opencv'
devices: [
{ name: 'window', driver: 'window' }
{ name: 'camera', driver: 'camera', camera: 0 }
]
Now that Cylon knows about the necessary hardware we're going to be using, we'll
tell it what work we want to do:
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()
)
Now that our robot knows what work to do, and the work it will be doing that
hardware with, we can start it:
.start()

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examples/opencv_display_image/haarcascade_frontalface_alt.xml
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examples/opencv_face_detection/.DS_Store vendored
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61
examples/opencv_face_detection/face-detection.coffee
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Cylon = require('../..')
Cylon.robot
connection:
name: 'opencv', adaptor: 'opencv'
devices: [
{ name: 'window', driver: 'window' }
{
name: 'camera',
driver: 'camera',
camera: 0,
haarcascade: "#{ __dirname }/haarcascade_frontalface_alt.xml"
} # Default camera is 0
]
work: (my) ->
# We setup our face detection when the camera is ready to
# display images, we use `once` instead of `on` to make sure
# other 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 back in
# the listener function that we pass.
# The faces param is an array conaining any face detected
# in the frame (im).
my.camera.on('facesDetected', (err, im, faces) ->
# We loop through 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)
# The second to last param is the color of the rectangle
# as an rgb array e.g. [r,g,b].
# Once the image has been updated with rectangles around
# the faces detected, 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 passing the frame
# that we just got from the camera feed.
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, then comment
# out the my.camera.readFrame() in the facesDetected listener
# above, as well as the one two lines below.
#every 150, my.camera.readFrame
my.camera.readFrame()
)
.start()

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examples/opencv_face_detection/face-detection.js
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@ -1,37 +0,0 @@
var 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"
}
],
work: function(my) {
return my.camera.once('cameraReady', function() {
console.log('The camera is ready!');
my.camera.on('facesDetected', function(err, im, faces) {
var face, _i, _len;
for (_i = 0, _len = faces.length; _i < _len; _i++) {
face = faces[_i];
im.rectangle([face.x, face.y], [face.x + face.width, face.y + face.height], [0, 255, 0], 2);
}
my.window.show(im, 40);
return my.camera.readFrame();
});
my.camera.on('frameReady', function(err, im) {
return my.camera.detectFaces(im);
});
return my.camera.readFrame();
});
}
}).start();

77
examples/opencv_face_detection/face-detection.litcoffee
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@ -1,77 +0,0 @@
# Face Detection
First, let's import Cylon:
Cylon = require('../..')
Now that we have Cylon imported, we can start defining our robot
Cylon.robot
Let's define the connections and devices:
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
]
Now that Cylon knows about the necessary hardware we're going to be using, we'll
tell it what work we want to do:
work: (my) ->
# We setup our face detection when the camera is ready to
# display images, we use `once` instead of `on` to make sure
# other 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 back in
# the listener function that we pass.
# The faces param is an array conaining any face detected
# in the frame (im).
my.camera.on('facesDetected', (err, im, faces) ->
# We loop through 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)
# The second to last param is the color of the rectangle
# as an rgb array e.g. [r,g,b].
# Once the image has been updated with rectangles around
# the faces detected, 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 passing the frame
# that we just got from the camera feed.
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, then comment
# out the my.camera.readFrame() in the facesDetected listener
# above as well as the one two lines below.
#every 150, my.camera.readFrame
my.camera.readFrame()
)
Now that our robot knows what work to do, and the work it will be doing that
hardware with, we can start it:
.start()

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examples/opencv_face_detection/haarcascade_frontalface_alt.xml
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