OpenCV bindings for Node.js. OpenCV is the defacto computer vision library - by interfacing with it natively in node, we get powerful real time vision in js.
People are using node-opencv to fly control quadrocoptors, detect faces from webcam images and annotate video streams. If you're using it for something cool, I'd love to hear about it!
You'll need OpenCV 2.3.1 installed.
Then:
npm install opencv
Or to build the repo:
node-gyp rebuild
cv.readImage("./examples/test.jpg", function(err, im){
im.detectObject("./data/haarcascade_frontalface_alt.xml", {}, function(err, faces){
for (var i=0;i<faces.length; i++){
var x = faces[i]
im.ellipse(x.x + x.width/2, x.y + x.height/2, x.width/2, x.height/2);
}
im.save('./out.jpg');
});
})
The matrix is the most useful base datastructure in OpenCV. Things like images are just matrices of pixels.
new Matrix(width, height)
Or you can use opencv to read in image files. Supported formats are in the OpenCV docs, but jpgs etc are supported.
cv.readImage(filename, function(mat){
...
})
cv.readImage(buffer, function(mat){
...
})
If you need to pipe data into an image, you can use an imagestream:
var s = new cv.ImageStream()
s.on('load', function(matrix){ ...
}) fs.createReadStream('./examples/test.jpg').pipe(s); var mat = new cv.Matrix.Eye(4,4); // Create identity matrix
mat.get(0,0) // 1
mat.row(0) // [1,0,0,0]
mat.col(4) // [0,0,0,1]
mat.save('./pic.jpg')
or:
var buff = mat.toBuffer()
im.convertGrayscale()
im.canny(5, 300)
im.houghLinesP()
im.ellipse(x, y)
im.line([x1,y1], [x2, y2])
There is a shortcut method for Viola-Jones Haar Cascade object detection. This can be used for face detection etc.
mat.detectObject(haar_cascade_xml, opts, function(err, matches){})
Also:
mat.goodFeaturesToTrack
mat.findCountours
mat.drawContour
mat.drawAllContours
The library is distributed under the MIT License - if for some reason that doesn't work for you please get in touch.
- toBuffer can now take a callback and be run async (re #21)