README.md

node-opencv

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!

Install

You'll need OpenCV 2.3.1 or newer installed before installing node-opencv. Note that OpenCV 3.x is not yet fully supported.

Specific for Windows

1. Download and install OpenCV (Be sure to use a 2.4 version) @ http://opencv.org/downloads.html For these instructions we will assume OpenCV is put at C:\OpenCV, but you can adjust accordingly.

2. If you haven't already, create a system variable called OPENCV_DIR and set it to C:\OpenCV\build\x64\vc12

   Make sure the "x64" part matches the version of NodeJS you are using.

   Also add the following to your system PATH ;%OPENCV_DIR%\bin

3. Install Visual Studio 2013. Make sure to get the C++ components. You can use a different edition, just make sure OpenCV supports it, and you set the "vcxx" part of the variables above to match.

4. Download peterbraden/node-opencv fork git clone https://github.com/peterbraden/node-opencv

5. run npm install

$ npm install opencv

Examples

Run the examples from the parent directory.

Face Detection

cv.readImage("./examples/files/mona.png", function(err, im){
  im.detectObject(cv.FACE_CASCADE, {}, 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 is the most useful base data structure in OpenCV. Things like images are just matrices of pixels.

Creation

new Matrix(rows, cols)

Or if you're thinking of a Matrix as an image:

new Matrix(height, width)

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(err, mat){
  ...
})

cv.readImage(buffer, function(err, mat){
  ...
})

If you need to pipe data into an image, you can use an ImageDataStream:

var s = new cv.ImageDataStream()

s.on('load', function(matrix){
  ...
})

fs.createReadStream('./examples/files/mona.png').pipe(s);

If however, you have a series of images, and you wish to stream them into a stream of Matrices, you can use an ImageStream. Thus:

var s = new cv.ImageStream()

s.on('data', function(matrix){
   ...
})

ardrone.createPngStream().pipe(s);

Note: Each 'data' event into the ImageStream should be a complete image buffer.

Accessing Data

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]

Save

mat.save('./pic.jpg')

or:

var buff = mat.toBuffer()

Image Processing

im.convertGrayscale()
im.canny(5, 300)
im.houghLinesP()

Simple Drawing

im.ellipse(x, y)
im.line([x1,y1], [x2, y2])

Object Detection

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){})

For convenience in face detection, cv.FACE_CASCADE is a cascade that can be used for frontal face detection.

Also:

mat.goodFeaturesToTrack

Contours

mat.findCountours
mat.drawContour
mat.drawAllContours

Using Contours

findContours returns a Contours collection object, not a native array. This object provides functions for accessing, computing with, and altering the contours contained in it. See relevant source code and examples

var contours = im.findContours();

// Count of contours in the Contours object
contours.size();

// Count of corners(verticies) of contour `index`
contours.cornerCount(index);

// Access vertex data of contours
for(var c = 0; c < contours.size(); ++c) {
  console.log("Contour " + c);
  for(var i = 0; i < contours.cornerCount(c); ++i) {
    var point = contours.point(c, i);
    console.log("(" + point.x + "," + point.y + ")");
  }
}

// Computations of contour `index`
contours.area(index);
contours.arcLength(index, isClosed);
contours.boundingRect(index);
contours.minAreaRect(index);
contours.isConvex(index);
contours.fitEllipse(index);

// Destructively alter contour `index`
contours.approxPolyDP(index, epsilon, isClosed);
contours.convexHull(index, clockwise);

Test

Using tape. Run with command:

npm test.

Code coverage

Using istanbul and lcov. Run with command:

make cover

Build version of opencv.node will be generated, and coverage files will be put in coverage/ directory. These files can be remvoved automatically by running make clean.

MIT License

The library is distributed under the MIT License - if for some reason that doesn't work for you please get in touch.