mirror of
https://github.com/peterbraden/node-opencv.git
synced 2025-12-08 19:45:55 +00:00
103 lines
2.2 KiB
Markdown
Executable File
103 lines
2.2 KiB
Markdown
Executable File
# node-opencv
|
|
|
|
[](http://travis-ci.org/peterbraden/node-opencv)
|
|
|
|
|
|
[OpenCV](http://opencv.willowgarage.com/wiki/) bindings for Node.js
|
|
|
|
## Install
|
|
|
|
You'll need OpenCV 2.3.1 installed.
|
|
|
|
Then:
|
|
|
|
|
|
npm install opencv
|
|
|
|
|
|
Or to build the repo:
|
|
|
|
|
|
node-gyp rebuild
|
|
|
|
|
|
## Examples
|
|
|
|
### Face Detection
|
|
|
|
|
|
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');
|
|
|
|
});
|
|
})
|
|
|
|
|
|
|
|
## API Documentation
|
|
|
|
### Matrix
|
|
|
|
The [matrix](http://opencv.jp/opencv-2svn_org/cpp/core_basic_structures.html#mat) is the most useful
|
|
base datastructure in OpenCV. Things like images are just matrices of pixels.
|
|
|
|
#### Creation
|
|
|
|
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);
|
|
|
|
#### Accessors
|
|
|
|
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]
|
|
|
|
|
|
|
|
#### Image Processing
|
|
|
|
|
|
#### Object Detection
|
|
|
|
There is a shortcut method for
|
|
[Viola-Jones Haar Cascade](http://www.cognotics.com/opencv/servo_2007_series/part_2/sidebar.html) object
|
|
detection. This can be used for face detection etc.
|
|
|
|
|
|
mat.detectObject(haar_cascade_xml, opts, function(err, matches){})
|
|
|
|
|
|
|
|
|
|
## WIP
|
|
|
|
This is a WIP. I've never written C++ before so the code may be _interesting_ - if
|
|
I'm doing stuff wrong please feel free to correct me.
|