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node-opencv/src/Matrix.cc

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#include "Contours.h"
#include "Matrix.h"
#include "OpenCV.h"
#include <string.h>
#include <nan.h>
Nan::Persistent<FunctionTemplate> Matrix::constructor;
cv::Scalar setColor(Local<Object> objColor);
cv::Point setPoint(Local<Object> objPoint);
cv::Rect* setRect(Local<Object> objRect, cv::Rect &result);
void Matrix::Init(Local<Object> target) {
Nan::HandleScope scope;
//Class
Local<FunctionTemplate> ctor = Nan::New<FunctionTemplate>(Matrix::New);
constructor.Reset(ctor);
ctor->InstanceTemplate()->SetInternalFieldCount(1);
ctor->SetClassName(Nan::New("Matrix").ToLocalChecked());
// Prototype
Nan::SetPrototypeMethod(ctor, "row", Row);
Nan::SetPrototypeMethod(ctor, "col", Col);
Nan::SetPrototypeMethod(ctor, "pixelRow", PixelRow);
Nan::SetPrototypeMethod(ctor, "pixelCol", PixelCol);
Nan::SetPrototypeMethod(ctor, "empty", Empty);
Nan::SetPrototypeMethod(ctor, "get", Get);
Nan::SetPrototypeMethod(ctor, "getPixel", GetPixel);
Nan::SetPrototypeMethod(ctor, "set", Set);
Nan::SetPrototypeMethod(ctor, "put", Put);
Nan::SetPrototypeMethod(ctor, "brightness", Brightness);
Nan::SetPrototypeMethod(ctor, "normalize", Normalize);
Nan::SetPrototypeMethod(ctor, "norm", Norm);
Nan::SetPrototypeMethod(ctor, "getData", GetData);
Nan::SetPrototypeMethod(ctor, "pixel", Pixel);
Nan::SetPrototypeMethod(ctor, "width", Width);
Nan::SetPrototypeMethod(ctor, "height", Height);
Nan::SetPrototypeMethod(ctor, "type", Type);
Nan::SetPrototypeMethod(ctor, "size", Size);
Nan::SetPrototypeMethod(ctor, "clone", Clone);
Nan::SetPrototypeMethod(ctor, "crop", Crop);
Nan::SetPrototypeMethod(ctor, "toBuffer", ToBuffer);
Nan::SetPrototypeMethod(ctor, "toBufferAsync", ToBufferAsync);
Nan::SetPrototypeMethod(ctor, "ellipse", Ellipse);
Nan::SetPrototypeMethod(ctor, "rectangle", Rectangle);
Nan::SetPrototypeMethod(ctor, "line", Line);
Nan::SetPrototypeMethod(ctor, "fillPoly", FillPoly);
Nan::SetPrototypeMethod(ctor, "save", Save);
Nan::SetPrototypeMethod(ctor, "saveAsync", SaveAsync);
Nan::SetPrototypeMethod(ctor, "resize", Resize);
Nan::SetPrototypeMethod(ctor, "rotate", Rotate);
Nan::SetPrototypeMethod(ctor, "warpAffine", WarpAffine);
Nan::SetPrototypeMethod(ctor, "copyTo", CopyTo);
Nan::SetPrototypeMethod(ctor, "convertTo", ConvertTo);
Nan::SetPrototypeMethod(ctor, "pyrDown", PyrDown);
Nan::SetPrototypeMethod(ctor, "pyrUp", PyrUp);
Nan::SetPrototypeMethod(ctor, "channels", Channels);
Nan::SetPrototypeMethod(ctor, "convertGrayscale", ConvertGrayscale);
Nan::SetPrototypeMethod(ctor, "convertHSVscale", ConvertHSVscale);
Nan::SetPrototypeMethod(ctor, "gaussianBlur", GaussianBlur);
Nan::SetPrototypeMethod(ctor, "medianBlur", MedianBlur);
Nan::SetPrototypeMethod(ctor, "bilateralFilter", BilateralFilter);
Nan::SetPrototypeMethod(ctor, "sobel", Sobel);
Nan::SetPrototypeMethod(ctor, "copy", Copy);
Nan::SetPrototypeMethod(ctor, "flip", Flip);
Nan::SetPrototypeMethod(ctor, "roi", ROI);
Nan::SetPrototypeMethod(ctor, "ptr", Ptr);
Nan::SetPrototypeMethod(ctor, "absDiff", AbsDiff);
Nan::SetPrototypeMethod(ctor, "dct", Dct);
Nan::SetPrototypeMethod(ctor, "idct", Idct);
Nan::SetPrototypeMethod(ctor, "addWeighted", AddWeighted);
Nan::SetPrototypeMethod(ctor, "add", Add);
Nan::SetPrototypeMethod(ctor, "bitwiseXor", BitwiseXor);
Nan::SetPrototypeMethod(ctor, "bitwiseNot", BitwiseNot);
Nan::SetPrototypeMethod(ctor, "bitwiseAnd", BitwiseAnd);
Nan::SetPrototypeMethod(ctor, "countNonZero", CountNonZero);
Nan::SetPrototypeMethod(ctor, "moments", Moments);
Nan::SetPrototypeMethod(ctor, "canny", Canny);
Nan::SetPrototypeMethod(ctor, "dilate", Dilate);
Nan::SetPrototypeMethod(ctor, "erode", Erode);
Nan::SetPrototypeMethod(ctor, "findContours", FindContours);
Nan::SetPrototypeMethod(ctor, "drawContour", DrawContour);
Nan::SetPrototypeMethod(ctor, "drawAllContours", DrawAllContours);
Nan::SetPrototypeMethod(ctor, "goodFeaturesToTrack", GoodFeaturesToTrack);
#ifdef HAVE_OPENCV_VIDEO
Nan::SetPrototypeMethod(ctor, "calcOpticalFlowPyrLK", CalcOpticalFlowPyrLK);
#endif
Nan::SetPrototypeMethod(ctor, "houghLinesP", HoughLinesP);
Nan::SetPrototypeMethod(ctor, "houghCircles", HoughCircles);
Nan::SetPrototypeMethod(ctor, "inRange", inRange);
Nan::SetPrototypeMethod(ctor, "adjustROI", AdjustROI);
Nan::SetPrototypeMethod(ctor, "locateROI", LocateROI);
Nan::SetPrototypeMethod(ctor, "threshold", Threshold);
Nan::SetPrototypeMethod(ctor, "adaptiveThreshold", AdaptiveThreshold);
Nan::SetPrototypeMethod(ctor, "meanStdDev", MeanStdDev);
Nan::SetPrototypeMethod(ctor, "cvtColor", CvtColor);
Nan::SetPrototypeMethod(ctor, "split", Split);
Nan::SetPrototypeMethod(ctor, "merge", Merge);
Nan::SetPrototypeMethod(ctor, "equalizeHist", EqualizeHist);
Nan::SetPrototypeMethod(ctor, "floodFill", FloodFill);
Nan::SetPrototypeMethod(ctor, "matchTemplate", MatchTemplate);
Nan::SetPrototypeMethod(ctor, "matchTemplateByMatrix", MatchTemplateByMatrix);
Nan::SetPrototypeMethod(ctor, "templateMatches", TemplateMatches);
Nan::SetPrototypeMethod(ctor, "minMaxLoc", MinMaxLoc);
Nan::SetPrototypeMethod(ctor, "pushBack", PushBack);
Nan::SetPrototypeMethod(ctor, "putText", PutText);
Nan::SetPrototypeMethod(ctor, "getPerspectiveTransform", GetPerspectiveTransform);
Nan::SetPrototypeMethod(ctor, "warpPerspective", WarpPerspective);
Nan::SetMethod(ctor, "Zeros", Zeros);
Nan::SetMethod(ctor, "Ones", Ones);
Nan::SetMethod(ctor, "Eye", Eye);
Nan::SetMethod(ctor, "getRotationMatrix2D", GetRotationMatrix2D);
Nan::SetPrototypeMethod(ctor, "copyWithMask", CopyWithMask);
Nan::SetPrototypeMethod(ctor, "setWithMask", SetWithMask);
Nan::SetPrototypeMethod(ctor, "meanWithMask", MeanWithMask);
Nan::SetPrototypeMethod(ctor, "mean", Mean);
Nan::SetPrototypeMethod(ctor, "shift", Shift);
Nan::SetPrototypeMethod(ctor, "reshape", Reshape);
// leave this out - can't see a way it could be useful to us, as release() always completely forgets the data
// Nan::SetPrototypeMethod(ctor, "addref", Addref);
Nan::SetPrototypeMethod(ctor, "release", Release);
Nan::SetPrototypeMethod(ctor, "getrefCount", GetrefCount);
Nan::SetPrototypeMethod(ctor, "subtract", Subtract);
Nan::SetPrototypeMethod(ctor, "compare", Compare);
Nan::SetPrototypeMethod(ctor, "mul", Mul);
target->Set(Nan::New("Matrix").ToLocalChecked(), ctor->GetFunction());
};
NAN_METHOD(Matrix::New) {
Nan::HandleScope scope;
if (info.This()->InternalFieldCount() == 0) {
Nan::ThrowTypeError("Cannot instantiate without new");
}
Matrix *mat;
if (info.Length() == 0) {
mat = new Matrix;
} else if (info.Length() == 2 && info[0]->IsInt32() && info[1]->IsInt32()) {
mat = new Matrix(info[0]->IntegerValue(), info[1]->IntegerValue());
} else if (info.Length() == 3 && info[0]->IsInt32() && info[1]->IsInt32()
&& info[2]->IsInt32()) {
mat = new Matrix(info[0]->IntegerValue(), info[1]->IntegerValue(),
info[2]->IntegerValue());
} else if (info.Length() == 4 && info[0]->IsInt32() && info[1]->IsInt32() &&
info[2]->IsInt32() && info[3]->IsArray()) {
mat = new Matrix(info[0]->IntegerValue(), info[1]->IntegerValue(),
info[2]->IntegerValue(), info[3]->ToObject());
} else { // if (info.Length() == 5) {
Matrix *other = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
int x = info[1]->IntegerValue();
int y = info[2]->IntegerValue();
int w = info[3]->IntegerValue();
int h = info[4]->IntegerValue();
mat = new Matrix(other->mat, cv::Rect(x, y, w, h));
}
mat->Wrap(info.Holder());
info.GetReturnValue().Set(info.Holder());
}
Matrix::Matrix() :
node_opencv::Matrix() {
mat = cv::Mat();
}
Matrix::Matrix(int rows, int cols) :
node_opencv::Matrix() {
mat = cv::Mat(rows, cols, CV_32FC3);
}
Matrix::Matrix(int rows, int cols, int type) :
node_opencv::Matrix() {
mat = cv::Mat(rows, cols, type);
}
Matrix::Matrix(cv::Mat m, cv::Rect roi) :
node_opencv::Matrix() {
mat = cv::Mat(m, roi);
}
Matrix::Matrix(int rows, int cols, int type, Local<Object> scalarObj) {
mat = cv::Mat(rows, cols, type);
if (mat.channels() == 3) {
mat.setTo(cv::Scalar(scalarObj->Get(0)->IntegerValue(),
scalarObj->Get(1)->IntegerValue(),
scalarObj->Get(2)->IntegerValue()));
} else if (mat.channels() == 2) {
mat.setTo(cv::Scalar(scalarObj->Get(0)->IntegerValue(),
scalarObj->Get(1)->IntegerValue()));
} else if (mat.channels() == 1) {
mat.setTo(cv::Scalar(scalarObj->Get(0)->IntegerValue()));
} else {
Nan::ThrowError("Only 1-3 channels are supported");
}
}
NAN_METHOD(Matrix::Empty) {
SETUP_FUNCTION(Matrix)
info.GetReturnValue().Set(Nan::New<Boolean>(self->mat.empty()));
}
double Matrix::DblGet(cv::Mat mat, int i, int j) {
double val = 0;
cv::Vec3b pix;
unsigned int pint = 0;
switch (mat.type()) {
case CV_32FC3:
pix = mat.at<cv::Vec3f>(i, j);
pint |= (uchar) pix.val[2];
pint |= ((uchar) pix.val[1]) << 8;
pint |= ((uchar) pix.val[0]) << 16;
val = (double) pint;
break;
case CV_64FC1:
val = mat.at<double>(i, j);
break;
case CV_32FC1:
val = mat.at<float>(i, j);
break;
default:
val = mat.at<double>(i, j);
break;
}
return val;
}
NAN_METHOD(Matrix::Pixel) {
SETUP_FUNCTION(Matrix)
int y = info[0]->IntegerValue();
int x = info[1]->IntegerValue();
// cv::Scalar scal = self->mat.at<uchar>(y, x);
if (info.Length() == 3) {
Local < Object > objColor = info[2]->ToObject();
if (self->mat.channels() == 3) {
self->mat.at<cv::Vec3b>(y, x)[0] =
(uchar) objColor->Get(0)->IntegerValue();
self->mat.at<cv::Vec3b>(y, x)[1] =
(uchar) objColor->Get(1)->IntegerValue();
self->mat.at<cv::Vec3b>(y, x)[2] =
(uchar) objColor->Get(2)->IntegerValue();
} else if (self->mat.channels() == 1)
self->mat.at<uchar>(y, x) = (uchar) objColor->Get(0)->IntegerValue();
info.GetReturnValue().Set(info[2]->ToObject());
} else {
if (self->mat.channels() == 3) {
cv::Vec3b intensity = self->mat.at<cv::Vec3b>(y, x);
v8::Local < v8::Array > arr = Nan::New<v8::Array>(3);
arr->Set(0, Nan::New<Number>(intensity[0]));
arr->Set(1, Nan::New<Number>(intensity[1]));
arr->Set(2, Nan::New<Number>(intensity[2]));
info.GetReturnValue().Set(arr);
} else if (self->mat.channels() == 1) {
uchar intensity = self->mat.at<uchar>(y, x);
info.GetReturnValue().Set(Nan::New<Number>(intensity));
}
}
return;
// double val = Matrix::DblGet(t, i, j);
// info.GetReturnValue().Set(Nan::New<Number>(val));
}
NAN_METHOD(Matrix::Get) {
SETUP_FUNCTION(Matrix)
int i = info[0]->IntegerValue();
int j = info[1]->IntegerValue();
double val = Matrix::DblGet(self->mat, i, j);
info.GetReturnValue().Set(Nan::New<Number>(val));
}
NAN_METHOD(Matrix::GetPixel) {
SETUP_FUNCTION(Matrix)
int y = info[0]->IntegerValue();
int x = info[1]->IntegerValue();
if (self->mat.channels() == 4) {
v8::Local < v8::Array > arr = Nan::New<Array>(4);
cv::Vec4b pixel = self->mat.at<cv::Vec4b>(y, x);
arr->Set(0, Nan::New<Number>((double) pixel.val[0]));
arr->Set(1, Nan::New<Number>((double) pixel.val[1]));
arr->Set(2, Nan::New<Number>((double) pixel.val[2]));
arr->Set(3, Nan::New<Number>((double) pixel.val[3]));
info.GetReturnValue().Set(arr);
} else if (self->mat.channels() == 3) {
v8::Local < v8::Array > arr = Nan::New<Array>(3);
cv::Vec3b pixel = self->mat.at<cv::Vec3b>(y, x);
arr->Set(0, Nan::New<Number>((double) pixel.val[0]));
arr->Set(1, Nan::New<Number>((double) pixel.val[1]));
arr->Set(2, Nan::New<Number>((double) pixel.val[2]));
info.GetReturnValue().Set(arr);
} else if(self->mat.channels() == 1) {
int pixel = (int)self->mat.at<unsigned char>(y, x);
info.GetReturnValue().Set(pixel);
} else {
Nan::ThrowTypeError("Only 4, 3 and 1 channel matrix are supported");
}
}
NAN_METHOD(Matrix::Set) {
SETUP_FUNCTION(Matrix)
int i = info[0]->IntegerValue();
int j = info[1]->IntegerValue();
double val = info[2]->NumberValue();
int vint = 0;
if (info.Length() == 4) {
self->mat.at<cv::Vec3b>(i, j)[info[3]->NumberValue()] = val;
} else if (info.Length() == 3) {
switch (self->mat.type()) {
case CV_32FC3:
vint = static_cast<unsigned int>(val + 0.5);
self->mat.at<cv::Vec3f>(i, j)[0] = (uchar) (vint >> 16) & 0xff;
self->mat.at<cv::Vec3f>(i, j)[1] = (uchar) (vint >> 8) & 0xff;
self->mat.at<cv::Vec3f>(i, j)[2] = (uchar) (vint) & 0xff;
// printf("!!!i %x, %x, %x", (vint >> 16) & 0xff, (vint >> 8) & 0xff, (vint) & 0xff);
break;
case CV_32FC1:
self->mat.at<float>(i, j) = val;
break;
default:
self->mat.at<double>(i, j) = val;
}
} else {
Nan::ThrowTypeError("Invalid number of arguments");
}
return;
}
// @author tualo
// put node buffer directly into the image data
// img.put(new Buffer([0,100,0,100,100...]));
NAN_METHOD(Matrix::Put) {
SETUP_FUNCTION(Matrix)
if (!Buffer::HasInstance(info[0])) {
Nan::ThrowTypeError("Not a buffer");
}
const char* buffer_data = Buffer::Data(info[0]);
size_t buffer_length = Buffer::Length(info[0]);
memcpy(self->mat.data, buffer_data, buffer_length);
return;
}
// @author tualo
// getData getting node buffer of image data
NAN_METHOD(Matrix::GetData) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int size = self->mat.rows * self->mat.cols * self->mat.elemSize();
Local<Object> buf = Nan::NewBuffer(size).ToLocalChecked();
uchar* data = (uchar*) Buffer::Data(buf);
// if there is padding after each row, clone first to get rid of it
if (self->mat.dims == 2 && self->mat.step[0] != size_t(self->mat.size[1])) {
cv::Mat copy = self->mat.clone();
memcpy(data, copy.data, size);
} else {
memcpy(data, self->mat.data, size);
}
v8::Local<v8::Object> globalObj = Nan::GetCurrentContext()->Global();
v8::Local<v8::Function> bufferConstructor = v8::Local<v8::Function>::Cast(globalObj->Get(Nan::New<String>("Buffer").ToLocalChecked()));
v8::Local<v8::Value> constructorArgs[3] = {buf, Nan::New<v8::Integer>((unsigned) size), Nan::New<v8::Integer>(0)};
v8::Local<v8::Object> actualBuffer = Nan::NewInstance(bufferConstructor, 3, constructorArgs).ToLocalChecked();
info.GetReturnValue().Set(actualBuffer);
}
NAN_METHOD(Matrix::Brightness) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (info.Length() == 2) {
cv::Mat image;
if (self->mat.channels() == 3) {
image = self->mat;
} else if (self->mat.channels() == 1) {
cv::Mat myimg = self->mat;
cv::cvtColor(myimg, image, CV_GRAY2RGB);
} else {
Nan::ThrowError("those channels are not supported");
}
cv::Mat new_image = cv::Mat::zeros( image.size(), image.type() );
double alpha = info[0]->NumberValue();
int beta = info[1]->IntegerValue();
// Do the operation new_image(i,j) = alpha*image(i,j) + beta
for (int y = 0; y < image.rows; y++ ) {
for (int x = 0; x < image.cols; x++ ) {
for (int c = 0; c < 3; c++ ) {
new_image.at<cv::Vec3b>(y,x)[c] =
cv::saturate_cast<uchar>(alpha*( image.at<cv::Vec3b>(y,x)[c] ) + beta);
}
}
}
if (self->mat.channels() == 3) {
new_image.copyTo(self->mat);
} else if (self->mat.channels() == 1) {
cv::Mat gray;
cv::cvtColor(new_image, gray, CV_BGR2GRAY);
gray.copyTo(self->mat);
}
} else {
if (info.Length() == 1) {
int diff = info[0]->IntegerValue();
cv::Mat img = self->mat + diff;
img.copyTo(self->mat);
} else {
info.GetReturnValue().Set(Nan::New("Insufficient or wrong arguments").ToLocalChecked());
}
}
info.GetReturnValue().Set(Nan::Null());
}
int getNormType(int type) {
if ((type != cv::NORM_MINMAX) && (type != cv::NORM_INF)
&& (type != cv::NORM_L1) && (type != cv::NORM_L2)
&& (type != cv::NORM_L2SQR) && (type != cv::NORM_HAMMING)
&& (type != cv::NORM_HAMMING2) && (type != cv::NORM_RELATIVE)
&& (type != cv::NORM_TYPE_MASK)) {
Nan::ThrowTypeError("type value must be NORM_INF=1, NORM_L1=2, NORM_L2=4,"
" NORM_L2SQR=5, NORM_HAMMING=6, NORM_HAMMING2=7, NORM_TYPE_MASK=7, "
"NORM_RELATIVE=8, NORM_MINMAX=32 ");
}
return type;
}
// @author tualo
// normalize wrapper
NAN_METHOD(Matrix::Normalize) {
if (!info[0]->IsNumber()) {
Nan::ThrowTypeError("min is required (argument 1)");
}
if (!info[1]->IsNumber()) {
Nan::ThrowTypeError("max is required (argument 2)");
}
int type = cv::NORM_MINMAX;
if (info[2]->IsNumber()) {
type = getNormType(info[2]->Uint32Value());
}
int dtype = -1;
if (info[3]->IsNumber()) {
dtype = info[3]->IntegerValue();
}
double min = info[0]->NumberValue();
double max = info[1]->NumberValue();
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
cv::Mat norm;
cv::Mat mask;
if (info[4]->IsObject()) {
Matrix *mmask = Nan::ObjectWrap::Unwrap<Matrix>(info[4]->ToObject());
mask = mmask->mat;
}
cv::normalize(self->mat, norm, min, max, type, dtype, mask);
norm.copyTo(self->mat);
info.GetReturnValue().Set(Nan::Null());
}
/**
* Calculates an absolute array norm, an absolute difference norm, or a relative
* difference norm.
*
* Reference: http://docs.opencv.org/2.4/modules/core/doc/
* operations_on_arrays.html?highlight=normalize#norm
*/
NAN_METHOD(Matrix::Norm) {
Matrix *src2 = NULL;
int normType = cv::NORM_L2;
cv::Mat mask;
int infoCount = 0;
Matrix *src1 = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
// If src2 is specified calculate absolute or relative difference norm
if (!info[infoCount]->IsUndefined() && info[infoCount]->IsObject()) {
src2 = Nan::ObjectWrap::Unwrap<Matrix>(info[infoCount]->ToObject());
infoCount++;
}
// NORM_TYPE
if (!info[infoCount]->IsUndefined() && info[infoCount]->IsInt32()) {
normType = getNormType(info[infoCount]->Uint32Value());
infoCount++;
}
// Mask
if (!info[infoCount]->IsUndefined() && info[infoCount]->IsObject()) {
Matrix *mmask = Nan::ObjectWrap::Unwrap<Matrix>(info[infoCount]->ToObject());
mask = mmask->mat;
infoCount++;
}
double res = 0;
if (src2) {
res = cv::norm(src1->mat, src2->mat, normType, mask);
} else {
res = cv::norm(src1->mat, normType, mask);
}
info.GetReturnValue().Set(Nan::New<Number>(res));
}
NAN_METHOD(Matrix::Size) {
SETUP_FUNCTION(Matrix)
v8::Local < v8::Array > arr = Nan::New<Array>(2);
arr->Set(0, Nan::New<Number>(self->mat.size().height));
arr->Set(1, Nan::New<Number>(self->mat.size().width));
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::Type) {
SETUP_FUNCTION(Matrix)
info.GetReturnValue().Set(Nan::New<Int32>(self->mat.type()));
}
NAN_METHOD(Matrix::Clone) {
SETUP_FUNCTION(Matrix)
Local < Object > im_h =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m = Nan::ObjectWrap::Unwrap<Matrix>(im_h);
m->mat = self->mat.clone();
info.GetReturnValue().Set(im_h);
}
NAN_METHOD(Matrix::Crop) {
SETUP_FUNCTION(Matrix)
if ((info.Length() == 4) && (info[0]->IsNumber()) && (info[1]->IsNumber())
&& (info[2]->IsNumber()) && (info[3]->IsNumber())) {
int x = info[0]->IntegerValue();
int y = info[1]->IntegerValue();
int width = info[2]->IntegerValue();
int height = info[3]->IntegerValue();
cv::Rect roi(x, y, width, height);
Local < Object > im_h =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m = Nan::ObjectWrap::Unwrap<Matrix>(im_h);
m->mat = self->mat(roi);
info.GetReturnValue().Set(im_h);
} else {
info.GetReturnValue().Set(Nan::New("Insufficient or wrong arguments").ToLocalChecked());
}
}
NAN_METHOD(Matrix::Row) {
SETUP_FUNCTION(Matrix)
int width = self->mat.size().width;
int y = info[0]->IntegerValue();
v8::Local < v8::Array > arr = Nan::New<Array>(width);
for (int x = 0; x < width; x++) {
double v = Matrix::DblGet(self->mat, y, x);
arr->Set(x, Nan::New<Number>(v));
}
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::PixelRow) {
SETUP_FUNCTION(Matrix)
int width = self->mat.size().width;
int y = info[0]->IntegerValue();
v8::Local < v8::Array > arr;
if (self->mat.channels() == 4) {
arr = Nan::New<Array>(width * 4);
for (int x = 0; x < width; x++) {
cv::Vec4b pixel = self->mat.at<cv::Vec4b>(y, x);
int offset = x * 4;
arr->Set(offset, Nan::New<Number>((double) pixel.val[0]));
arr->Set(offset + 1, Nan::New<Number>((double) pixel.val[1]));
arr->Set(offset + 2, Nan::New<Number>((double) pixel.val[2]));
arr->Set(offset + 3, Nan::New<Number>((double) pixel.val[3]));
}
} else if(self->mat.channels() == 3){
arr = Nan::New<Array>(width * 3);
for (int x = 0; x < width; x++) {
cv::Vec3b pixel = self->mat.at<cv::Vec3b>(y, x);
int offset = x * 3;
arr->Set(offset, Nan::New<Number>((double) pixel.val[0]));
arr->Set(offset + 1, Nan::New<Number>((double) pixel.val[1]));
arr->Set(offset + 2, Nan::New<Number>((double) pixel.val[2]));
}
} else if(self->mat.channels() == 1){
arr = Nan::New<Array>(width);
for (int x = 0; x < width; x++) {
int pixel = (int)self->mat.at<unsigned char>(y, x);
arr->Set(x, Nan::New<Number>(pixel));
}
} else {
Nan::ThrowTypeError("Only 4, 3 and 1 channel matrix are supported");
}
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::Col) {
SETUP_FUNCTION(Matrix)
int height = self->mat.size().height;
int x = info[0]->IntegerValue();
v8::Local < v8::Array > arr = Nan::New<Array>(height);
for (int y = 0; y < height; y++) {
double v = Matrix::DblGet(self->mat, y, x);
arr->Set(y, Nan::New<Number>(v));
}
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::PixelCol) {
SETUP_FUNCTION(Matrix)
int height = self->mat.size().height;
int x = info[0]->IntegerValue();
v8::Local < v8::Array > arr;
if (self->mat.channels() == 4) {
arr = Nan::New<Array>(height * 4);
for (int y = 0; y < height; y++) {
cv::Vec4b pixel = self->mat.at<cv::Vec4b>(y, x);
int offset = y * 4;
arr->Set(offset, Nan::New<Number>((double) pixel.val[0]));
arr->Set(offset + 1, Nan::New<Number>((double) pixel.val[1]));
arr->Set(offset + 2, Nan::New<Number>((double) pixel.val[2]));
arr->Set(offset + 3, Nan::New<Number>((double) pixel.val[3]));
}
} else if (self->mat.channels() == 3) {
arr = Nan::New<Array>(height * 3);
for (int y = 0; y < height; y++) {
cv::Vec3b pixel = self->mat.at<cv::Vec3b>(y, x);
int offset = y * 3;
arr->Set(offset, Nan::New<Number>((double) pixel.val[0]));
arr->Set(offset + 1, Nan::New<Number>((double) pixel.val[1]));
arr->Set(offset + 2, Nan::New<Number>((double) pixel.val[2]));
}
} else if(self->mat.channels() == 1) {
arr = Nan::New<Array>(height);
for (int y = 0; y < height; y++) {
int pixel = (int)self->mat.at<unsigned char>(y, x);
arr->Set(y, Nan::New<Number>(pixel));
}
} else {
Nan::ThrowTypeError("Only 4, 3 and 1 channel matrix are supported");
}
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::Width) {
SETUP_FUNCTION(Matrix)
info.GetReturnValue().Set(Nan::New<Number>(self->mat.size().width));
}
NAN_METHOD(Matrix::Height) {
SETUP_FUNCTION(Matrix)
info.GetReturnValue().Set(Nan::New<Number>(self->mat.size().height));
}
NAN_METHOD(Matrix::Channels) {
SETUP_FUNCTION(Matrix)
info.GetReturnValue().Set(Nan::New<Number>(self->mat.channels()));
}
NAN_METHOD(Matrix::ToBuffer) {
SETUP_FUNCTION(Matrix)
if ((info.Length() > 0) && (info[0]->IsFunction())) {
return Matrix::ToBufferAsync(info);
}
// SergeMv changes
// img.toBuffer({ext: ".png", pngCompression: 9}); // default png compression is 3
// img.toBuffer({ext: ".jpg", jpegQuality: 80});
// img.toBuffer(); // creates Jpeg with quality of 95 (Opencv default quality)
// via the ext you can do other image formats too (like tiff), see
// http://docs.opencv.org/modules/highgui/doc/reading_and_writing_images_and_video.html#imencode
//---------------------------
// Provide default value
const char *ext = ".jpg";
std::string optExt;
std::vector<int> params;
// See if the options argument is passed
if ((info.Length() > 0) && (info[0]->IsObject())) {
// Get this options argument
v8::Handle < v8::Object > options = v8::Local<v8::Object>::Cast(info[0]);
// If the extension (image format) is provided
if (options->Has(Nan::New<String>("ext").ToLocalChecked())) {
v8::String::Utf8Value str(
options->Get(Nan::New<String>("ext").ToLocalChecked())->ToString());
optExt = *str;
ext = (const char *) optExt.c_str();
}
if (options->Has(Nan::New<String>("jpegQuality").ToLocalChecked())) {
int compression =
options->Get(Nan::New<String>("jpegQuality").ToLocalChecked())->IntegerValue();
params.push_back(CV_IMWRITE_JPEG_QUALITY);
params.push_back(compression);
}
if (options->Has(Nan::New<String>("pngCompression").ToLocalChecked())) {
int compression =
options->Get(Nan::New<String>("pngCompression").ToLocalChecked())->IntegerValue();
params.push_back(CV_IMWRITE_PNG_COMPRESSION);
params.push_back(compression);
}
}
//---------------------------
std::vector<uchar> vec(0);
cv::imencode(ext, self->mat, vec, params);
Local < Object > buf = Nan::NewBuffer(vec.size()).ToLocalChecked();
uchar* data = (uchar*) Buffer::Data(buf);
memcpy(data, &vec[0], vec.size());
v8::Local < v8::Object > globalObj = Nan::GetCurrentContext()->Global();
v8::Local < v8::Function > bufferConstructor = v8::Local < v8::Function
> ::Cast(globalObj->Get(Nan::New<String>("Buffer").ToLocalChecked()));
v8::Local<v8::Value> constructorArgs[3] =
{buf, Nan::New<v8::Integer>((unsigned)vec.size()), Nan::New<v8::Integer>(0)};
v8::Local < v8::Object > actualBuffer = Nan::NewInstance(bufferConstructor, 3, constructorArgs).ToLocalChecked();
info.GetReturnValue().Set(actualBuffer);
}
class AsyncToBufferWorker: public Nan::AsyncWorker {
public:
AsyncToBufferWorker(Nan::Callback *callback, cv::Mat mat, std::string ext,
std::vector<int> params) :
Nan::AsyncWorker(callback),
mat(mat), // dulipcate mat, adding ref, but not copying data
ext(ext),
params(params) {
}
~AsyncToBufferWorker() {
// mat is released, decrementing refcount
}
void Execute() {
std::vector<uchar> vec(0);
// std::vector<int> params(0);//CV_IMWRITE_JPEG_QUALITY 90
cv::imencode(ext, this->mat, vec, this->params);
res = vec;
}
void HandleOKCallback() {
Nan::HandleScope scope;
Local<Object> buf = Nan::NewBuffer(res.size()).ToLocalChecked();
uchar* data = (uchar*) Buffer::Data(buf);
memcpy(data, &res[0], res.size());
v8::Local<v8::Object> globalObj = Nan::GetCurrentContext()->Global();
v8::Local<v8::Function> bufferConstructor = v8::Local<v8::Function>::Cast(globalObj->Get(Nan::New<String>("Buffer").ToLocalChecked()));
v8::Local<v8::Value> constructorArgs[3] = {buf, Nan::New<v8::Integer>((unsigned)res.size()), Nan::New<v8::Integer>(0)};
v8::Local<v8::Object> actualBuffer = Nan::NewInstance(bufferConstructor, 3, constructorArgs).ToLocalChecked();;
Local<Value> argv[] = {
Nan::Null(),
actualBuffer
};
Nan::TryCatch try_catch;
callback->Call(2, argv);
if (try_catch.HasCaught()) {
Nan::FatalException(try_catch);
}
}
private:
cv::Mat mat;
std::string ext;
std::vector<int> params;
std::vector<uchar> res;
};
NAN_METHOD(Matrix::ToBufferAsync) {
SETUP_FUNCTION(Matrix)
REQ_FUN_ARG(0, cb);
std::string ext = std::string(".jpg");
std::vector<int> params;
// See if the options argument is passed
if ((info.Length() > 1) && (info[1]->IsObject())) {
// Get this options argument
v8::Handle < v8::Object > options = v8::Local<v8::Object>::Cast(info[1]);
// If the extension (image format) is provided
if (options->Has(Nan::New<String>("ext").ToLocalChecked())) {
v8::String::Utf8Value str(
options->Get(Nan::New<String>("ext").ToLocalChecked())->ToString());
std::string str2 = std::string(*str);
ext = str2;
}
if (options->Has(Nan::New<String>("jpegQuality").ToLocalChecked())) {
int compression =
options->Get(Nan::New<String>("jpegQuality").ToLocalChecked())->IntegerValue();
params.push_back(CV_IMWRITE_JPEG_QUALITY);
params.push_back(compression);
}
if (options->Has(Nan::New<String>("pngCompression").ToLocalChecked())) {
int compression =
options->Get(Nan::New<String>("pngCompression").ToLocalChecked())->IntegerValue();
params.push_back(CV_IMWRITE_PNG_COMPRESSION);
params.push_back(compression);
}
}
Nan::Callback *callback = new Nan::Callback(cb.As<Function>());
Nan::AsyncQueueWorker(new AsyncToBufferWorker(callback, self->mat, ext, params));
return;
}
NAN_METHOD(Matrix::Ellipse) {
SETUP_FUNCTION(Matrix)
int x = 0;
int y = 0;
int width = 0;
int height = 0;
cv::Scalar color(0, 0, 255);
int thickness = 1;
double angle = 0;
double startAngle = 0;
double endAngle = 360;
int lineType = 8;
int shift = 0;
if (info[0]->IsObject()) {
v8::Handle < v8::Object > options = v8::Local<v8::Object>::Cast(info[0]);
if (options->Has(Nan::New<String>("center").ToLocalChecked())) {
Local < Object > center =
options->Get(Nan::New<String>("center").ToLocalChecked())->ToObject();
x = center->Get(Nan::New<String>("x").ToLocalChecked())->Uint32Value();
y = center->Get(Nan::New<String>("y").ToLocalChecked())->Uint32Value();
}
if (options->Has(Nan::New<String>("axes").ToLocalChecked())) {
Local < Object > axes = options->Get(Nan::New<String>("axes").ToLocalChecked())->ToObject();
width = axes->Get(Nan::New<String>("width").ToLocalChecked())->Uint32Value();
height = axes->Get(Nan::New<String>("height").ToLocalChecked())->Uint32Value();
}
if (options->Has(Nan::New<String>("thickness").ToLocalChecked())) {
thickness = options->Get(Nan::New<String>("thickness").ToLocalChecked())->Uint32Value();
}
if (options->Has(Nan::New<String>("angle").ToLocalChecked())) {
angle = options->Get(Nan::New<String>("angle").ToLocalChecked())->NumberValue();
}
if (options->Has(Nan::New<String>("startAngle").ToLocalChecked())) {
startAngle = options->Get(Nan::New<String>("startAngle").ToLocalChecked())->NumberValue();
}
if (options->Has(Nan::New<String>("endAngle").ToLocalChecked())) {
endAngle = options->Get(Nan::New<String>("endAngle").ToLocalChecked())->NumberValue();
}
if (options->Has(Nan::New<String>("lineType").ToLocalChecked())) {
lineType = options->Get(Nan::New<String>("lineType").ToLocalChecked())->Uint32Value();
}
if (options->Has(Nan::New<String>("shift").ToLocalChecked())) {
shift = options->Get(Nan::New<String>("shift").ToLocalChecked())->Uint32Value();
}
if (options->Has(Nan::New<String>("color").ToLocalChecked())) {
Local < Object > objColor =
options->Get(Nan::New<String>("color").ToLocalChecked())->ToObject();
color = setColor(objColor);
}
} else {
x = info[0]->Uint32Value();
y = info[1]->Uint32Value();
width = info[2]->Uint32Value();
height = info[3]->Uint32Value();
if (info[4]->IsArray()) {
Local < Object > objColor = info[4]->ToObject();
color = setColor(objColor);
}
if (info[5]->IntegerValue())
thickness = info[5]->IntegerValue();
}
cv::ellipse(self->mat, cv::Point(x, y), cv::Size(width, height), angle,
startAngle, endAngle, color, thickness, lineType, shift);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Rectangle) {
SETUP_FUNCTION(Matrix)
if (info[0]->IsArray() && info[1]->IsArray()) {
Local < Object > xy = info[0]->ToObject();
Local < Object > width_height = info[1]->ToObject();
cv::Scalar color(0, 0, 255);
if (info[2]->IsArray()) {
Local < Object > objColor = info[2]->ToObject();
color = setColor(objColor);
}
int x = xy->Get(0)->IntegerValue();
int y = xy->Get(1)->IntegerValue();
int width = width_height->Get(0)->IntegerValue();
int height = width_height->Get(1)->IntegerValue();
int thickness = 1;
if (info[3]->IntegerValue())
thickness = info[3]->IntegerValue();
cv::rectangle(self->mat, cv::Point(x, y), cv::Point(x + width, y + height),
color, thickness);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Line) {
SETUP_FUNCTION(Matrix)
if (info[0]->IsArray() && info[1]->IsArray()) {
Local < Object > xy1 = info[0]->ToObject();
Local < Object > xy2 = info[1]->ToObject();
cv::Scalar color(0, 0, 255);
if (info[2]->IsArray()) {
Local < Object > objColor = info[2]->ToObject();
color = setColor(objColor);
}
int x1 = xy1->Get(0)->IntegerValue();
int y1 = xy1->Get(1)->IntegerValue();
int x2 = xy2->Get(0)->IntegerValue();
int y2 = xy2->Get(1)->IntegerValue();
int thickness = 1;
if (info[3]->IntegerValue())
thickness = info[3]->IntegerValue();
cv::line(self->mat, cv::Point(x1, y1), cv::Point(x2, y2), color, thickness);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::FillPoly) {
SETUP_FUNCTION(Matrix)
if (info[0]->IsArray()) {
Local < Array > polyArray = Local < Array > ::Cast(info[0]->ToObject());
cv::Point **polygons = new cv::Point*[polyArray->Length()];
int *polySizes = new int[polyArray->Length()];
for (unsigned int i = 0; i < polyArray->Length(); i++) {
Local<Array> singlePoly = Local<Array> ::Cast(polyArray->Get(i)->ToObject());
polygons[i] = new cv::Point[singlePoly->Length()];
polySizes[i] = singlePoly->Length();
for (unsigned int j = 0; j < singlePoly->Length(); j++) {
Local<Array> point = Local<Array> ::Cast(singlePoly->Get(j)->ToObject());
polygons[i][j].x = point->Get(0)->IntegerValue();
polygons[i][j].y = point->Get(1)->IntegerValue();
}
}
cv::Scalar color(0, 0, 255);
if (info[1]->IsArray()) {
Local<Object> objColor = info[1]->ToObject();
color = setColor(objColor);
}
cv::fillPoly(self->mat, (const cv::Point **) polygons, polySizes,
polyArray->Length(), color);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Save) {
SETUP_FUNCTION(Matrix)
if (info.Length() > 1) {
return SaveAsync(info);
}
if (!info[0]->IsString()) {
Nan::ThrowTypeError("filename required");
}
Nan::Utf8String filename(info[0]);
int res = cv::imwrite(*filename, self->mat);
info.GetReturnValue().Set(Nan::New<Number>(res));
}
// All this is for async save, see here for nan example:
// https://github.com/rvagg/nan/blob/c579ae858ae3208d7e702e8400042ba9d48fa64b/examples/async_pi_estimate/async.cc
class AsyncSaveWorker: public Nan::AsyncWorker {
public:
AsyncSaveWorker(Nan::Callback *callback, cv::Mat mat, char* filename) :
Nan::AsyncWorker(callback),
mat(mat),
filename(filename) {
}
~AsyncSaveWorker() {
}
// Executed inside the worker-thread.
// It is not safe to access V8, or V8 data structures
// here, so everything we need for input and output
// should go on `this`.
void Execute() {
res = cv::imwrite(this->filename, this->mat);
}
// Executed when the async work is complete
// this function will be run inside the main event loop
// so it is safe to use V8 again
void HandleOKCallback() {
Nan::HandleScope scope;
Local<Value> argv[] = {
Nan::Null(),
Nan::New<Number>(res)
};
Nan::TryCatch try_catch;
callback->Call(2, argv);
if (try_catch.HasCaught()) {
Nan::FatalException(try_catch);
}
}
private:
cv::Mat mat;
std::string filename;
int res;
};
NAN_METHOD(Matrix::SaveAsync) {
SETUP_FUNCTION(Matrix)
if (!info[0]->IsString()) {
Nan::ThrowTypeError("filename required");
}
Nan::Utf8String filename(info[0]);
REQ_FUN_ARG(1, cb);
Nan::Callback *callback = new Nan::Callback(cb.As<Function>());
Nan::AsyncQueueWorker(new AsyncSaveWorker(callback, self->mat, *filename));
return;
}
NAN_METHOD(Matrix::Zeros) {
Nan::HandleScope scope;
int w = info[0]->Uint32Value();
int h = info[1]->Uint32Value();
int type = (info.Length() > 2) ? info[2]->IntegerValue() : CV_64FC1;
Local<Object> im_h = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(im_h);
cv::Mat mat = cv::Mat::zeros(w, h, type);
img->mat = mat;
info.GetReturnValue().Set(im_h);
}
NAN_METHOD(Matrix::Ones) {
Nan::HandleScope scope;
int w = info[0]->Uint32Value();
int h = info[1]->Uint32Value();
int type = (info.Length() > 2) ? info[2]->IntegerValue() : CV_64FC1;
Local<Object> im_h = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(im_h);
cv::Mat mat = cv::Mat::ones(w, h, type);
img->mat = mat;
info.GetReturnValue().Set(im_h);
}
NAN_METHOD(Matrix::Eye) {
Nan::HandleScope scope;
int w = info[0]->Uint32Value();
int h = info[1]->Uint32Value();
int type = (info.Length() > 2) ? info[2]->IntegerValue() : CV_64FC1;
Local<Object> im_h = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(im_h);
cv::Mat mat = cv::Mat::eye(w, h, type);
img->mat = mat;
info.GetReturnValue().Set(im_h);
}
NAN_METHOD(Matrix::ConvertGrayscale) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (self->mat.channels() != 3) {
Nan::ThrowError("Image is no 3-channel");
}
cv::cvtColor(self->mat, self->mat, CV_BGR2GRAY);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::ConvertHSVscale) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (self->mat.channels() != 3) {
Nan::ThrowError("Image is no 3-channel");
}
cv::Mat hsv;
cv::cvtColor(self->mat, hsv, CV_BGR2HSV);
hsv.copyTo(self->mat);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::GaussianBlur) {
Nan::HandleScope scope;
cv::Size ksize;
cv::Mat blurred;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
double sigma = 0;
if (info.Length() < 1) {
ksize = cv::Size(5, 5);
}
else {
if (!info[0]->IsArray()) {
Nan::ThrowTypeError("'ksize' argument must be a 2 double array");
}
Local<Object> array = info[0]->ToObject();
// TODO: Length check
Local<Value> x = array->Get(0);
Local<Value> y = array->Get(1);
if (!x->IsNumber() || !y->IsNumber()) {
Nan::ThrowTypeError("'ksize' argument must be a 2 double array");
}
ksize = cv::Size(x->NumberValue(), y->NumberValue());
if (info[1]->IsNumber()) {
sigma = Nan::To<double>(info[1]).FromJust();
}
}
cv::GaussianBlur(self->mat, blurred, ksize, sigma);
blurred.copyTo(self->mat);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::MedianBlur) {
Nan::HandleScope scope;
cv::Mat blurred;
int ksize = 3;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (info[0]->IsNumber()) {
ksize = info[0]->IntegerValue();
if ((ksize % 2) == 0) {
Nan::ThrowTypeError("'ksize' argument must be a positive odd integer");
}
} else {
Nan::ThrowTypeError("'ksize' argument must be a positive odd integer");
}
cv::medianBlur(self->mat, blurred, ksize);
blurred.copyTo(self->mat);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::BilateralFilter) {
Nan::HandleScope scope;
cv::Mat filtered;
int d = 15;
double sigmaColor = 80;
double sigmaSpace = 80;
int borderType = cv::BORDER_DEFAULT;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (info.Length() != 0) {
if (info.Length() < 3 || info.Length() > 4) {
Nan::ThrowTypeError("BilateralFilter takes 0, 3, or 4 arguments");
} else {
d = info[0]->IntegerValue();
sigmaColor = info[1]->NumberValue();
sigmaSpace = info[2]->NumberValue();
if (info.Length() == 4) {
borderType = info[3]->IntegerValue();
}
}
}
cv::bilateralFilter(self->mat, filtered, d, sigmaColor, sigmaSpace, borderType);
filtered.copyTo(self->mat);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Sobel) {
Nan::HandleScope scope;
if (info.Length() < 3)
Nan::ThrowError("Need more arguments: sobel(ddepth, xorder, yorder, ksize=3, scale=1.0, delta=0.0, borderType=CV_BORDER_DEFAULT)");
int ddepth = info[0]->IntegerValue();
int xorder = info[1]->IntegerValue();
int yorder = info[2]->IntegerValue();
int ksize = 3;
if (info.Length() > 3) ksize = info[3]->IntegerValue();
double scale = 1;
if (info.Length() > 4) scale = info[4]->NumberValue();
double delta = 0;
if (info.Length() > 5) delta = info[5]->NumberValue();
int borderType = cv::BORDER_DEFAULT;
if (info.Length() > 6) borderType = info[6]->IntegerValue();
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Local<Object> result_to_return =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *result = Nan::ObjectWrap::Unwrap<Matrix>(result_to_return);
cv::Sobel(self->mat, result->mat, ddepth, xorder, yorder, ksize, scale, delta, borderType);
info.GetReturnValue().Set(result_to_return);
}
NAN_METHOD(Matrix::Copy) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Local<Object> img_to_return =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
self->mat.copyTo(img->mat);
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::Flip) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if ( info.Length() < 1 || !info[0]->IsInt32() ) {
Nan::ThrowTypeError("Flip requires an integer flipCode argument "
"(0 = X axis, positive = Y axis, negative = both axis)");
}
int flipCode = Nan::To<int>(info[0]).FromJust();
Local<Object> img_to_return = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
cv::flip(self->mat, img->mat, flipCode);
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::ROI) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if ( info.Length() != 4 ) {
Nan::ThrowTypeError("ROI requires x,y,w,h arguments");
}
// Although it's an image to return, it is in fact a pointer to ROI of parent matrix
Local<Object> img_to_return = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
int x = info[0]->IntegerValue();
int y = info[1]->IntegerValue();
int w = info[2]->IntegerValue();
int h = info[3]->IntegerValue();
cv::Mat roi(self->mat, cv::Rect(x,y,w,h));
img->mat = roi;
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::Ptr) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int line = info[0]->Uint32Value();
char* data = self->mat.ptr<char>(line);
// uchar* data = self->mat.data;
// char *mydata = "Random raw data\0";
Local<Object> return_buffer = Nan::NewBuffer((char*)data, self->mat.step).ToLocalChecked();
info.GetReturnValue().Set( return_buffer );
// return;
}
NAN_METHOD(Matrix::AbsDiff) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *src1 = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Matrix *src2 = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
cv::absdiff(src1->mat, src2->mat, self->mat);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Dct) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int cols = self->mat.cols;
int rows = self->mat.rows;
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
m_out->mat.create(cols, rows, CV_32F);
cv::dct(self->mat, m_out->mat);
info.GetReturnValue().Set(out);
}
NAN_METHOD(Matrix::Idct) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int cols = self->mat.cols;
int rows = self->mat.rows;
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
m_out->mat.create(cols, rows, CV_32F);
cv::idct(self->mat, m_out->mat);
info.GetReturnValue().Set(out);
}
NAN_METHOD(Matrix::AddWeighted) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *src1 = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Matrix *src2 = Nan::ObjectWrap::Unwrap<Matrix>(info[2]->ToObject());
float alpha = info[1]->NumberValue();
float beta = info[3]->NumberValue();
int gamma = 0;
try {
cv::addWeighted(src1->mat, alpha, src2->mat, beta, gamma, self->mat);
} catch(cv::Exception& e ) {
const char* err_msg = e.what();
Nan::ThrowError(err_msg);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Add) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int cols = self->mat.cols;
int rows = self->mat.rows;
Matrix *src1 = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
m_out->mat.create(cols, rows, self->mat.type());
try {
cv::add(self->mat, src1->mat, m_out->mat);
} catch(cv::Exception& e ) {
const char* err_msg = e.what();
Nan::ThrowError(err_msg);
}
info.GetReturnValue().Set(out);
}
NAN_METHOD(Matrix::BitwiseXor) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *src1 = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Matrix *src2 = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
if (info.Length() == 3) {
Matrix *mask = Nan::ObjectWrap::Unwrap<Matrix>(info[2]->ToObject());
cv::bitwise_xor(src1->mat, src2->mat, self->mat, mask->mat);
} else {
cv::bitwise_xor(src1->mat, src2->mat, self->mat);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::BitwiseNot) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *dst = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
if (info.Length() == 2) {
Matrix *mask = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
cv::bitwise_not(self->mat, dst->mat, mask->mat);
} else {
cv::bitwise_not(self->mat, dst->mat);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::BitwiseAnd) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *src1 = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Matrix *src2 = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
if (info.Length() == 3) {
Matrix *mask = Nan::ObjectWrap::Unwrap<Matrix>(info[2]->ToObject());
cv::bitwise_and(src1->mat, src2->mat, self->mat, mask->mat);
} else {
cv::bitwise_and(src1->mat, src2->mat, self->mat);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::CountNonZero) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
double count = (double)cv::countNonZero(self->mat);
info.GetReturnValue().Set(Nan::New<Number>(count));
}
/*
NAN_METHOD(Matrix::Split) {
Nan::HandleScope scope;
//Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
info.GetReturnValue().Set(Nan::Null());
} */
NAN_METHOD(Matrix::Moments) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
cv::Moments mo = moments( self->mat, false );
Local<Object> res = Nan::New<Object>();
res->Set(Nan::New("m00").ToLocalChecked(), Nan::New<Number>(mo.m00));
res->Set(Nan::New("m10").ToLocalChecked(), Nan::New<Number>(mo.m10));
res->Set(Nan::New("m01").ToLocalChecked(), Nan::New<Number>(mo.m01));
res->Set(Nan::New("m20").ToLocalChecked(), Nan::New<Number>(mo.m20));
res->Set(Nan::New("m11").ToLocalChecked(), Nan::New<Number>(mo.m11));
res->Set(Nan::New("m02").ToLocalChecked(), Nan::New<Number>(mo.m02));
res->Set(Nan::New("m30").ToLocalChecked(), Nan::New<Number>(mo.m30));
res->Set(Nan::New("m21").ToLocalChecked(), Nan::New<Number>(mo.m21));
res->Set(Nan::New("m12").ToLocalChecked(), Nan::New<Number>(mo.m12));
res->Set(Nan::New("m03").ToLocalChecked(), Nan::New<Number>(mo.m03));
res->Set(Nan::New("mu20").ToLocalChecked(), Nan::New<Number>(mo.mu20));
res->Set(Nan::New("mu11").ToLocalChecked(), Nan::New<Number>(mo.mu11));
res->Set(Nan::New("mu02").ToLocalChecked(), Nan::New<Number>(mo.mu02));
res->Set(Nan::New("mu30").ToLocalChecked(), Nan::New<Number>(mo.mu30));
res->Set(Nan::New("mu21").ToLocalChecked(), Nan::New<Number>(mo.mu21));
res->Set(Nan::New("mu12").ToLocalChecked(), Nan::New<Number>(mo.mu12));
res->Set(Nan::New("mu03").ToLocalChecked(), Nan::New<Number>(mo.mu03));
res->Set(Nan::New("nu20").ToLocalChecked(), Nan::New<Number>(mo.nu20));
res->Set(Nan::New("nu11").ToLocalChecked(), Nan::New<Number>(mo.nu11));
res->Set(Nan::New("nu02").ToLocalChecked(), Nan::New<Number>(mo.nu02));
res->Set(Nan::New("nu30").ToLocalChecked(), Nan::New<Number>(mo.nu30));
res->Set(Nan::New("nu21").ToLocalChecked(), Nan::New<Number>(mo.nu21));
res->Set(Nan::New("nu12").ToLocalChecked(), Nan::New<Number>(mo.nu12));
res->Set(Nan::New("nu03").ToLocalChecked(), Nan::New<Number>(mo.nu03));
info.GetReturnValue().Set(res);
}
NAN_METHOD(Matrix::Canny) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int lowThresh = info[0]->NumberValue();
int highThresh = info[1]->NumberValue();
cv::Canny(self->mat, self->mat, lowThresh, highThresh);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Dilate) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int niters = info[0]->NumberValue();
cv::Mat kernel = cv::Mat();
if (info.Length() == 2) {
Matrix *kernelMatrix = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
kernel = kernelMatrix->mat;
}
cv::dilate(self->mat, self->mat, kernel, cv::Point(-1, -1), niters);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::Erode) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int niters = info[0]->NumberValue();
cv::Mat kernel = cv::Mat();
if (info.Length() == 2) {
Matrix *kernelMatrix = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
kernel = kernelMatrix->mat;
}
cv::erode(self->mat, self->mat, kernel, cv::Point(-1, -1), niters);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::FindContours) {
Nan::HandleScope scope;
int mode = CV_RETR_LIST;
int chain = CV_CHAIN_APPROX_SIMPLE;
if (info.Length() > 0) {
if (info[0]->IsNumber()) mode = info[0]->IntegerValue();
}
if (info.Length() > 1) {
if (info[1]->IsNumber()) chain = info[1]->IntegerValue();
}
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Local<Object> conts_to_return = Nan::NewInstance(Nan::GetFunction(Nan::New(Contour::constructor)).ToLocalChecked()).ToLocalChecked();
Contour *contours = Nan::ObjectWrap::Unwrap<Contour>(conts_to_return);
cv::findContours(self->mat, contours->contours, contours->hierarchy, mode, chain);
info.GetReturnValue().Set(conts_to_return);
}
NAN_METHOD(Matrix::DrawContour) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Contour *cont = Nan::ObjectWrap::Unwrap<Contour>(info[0]->ToObject());
int pos = info[1]->NumberValue();
cv::Scalar color(0, 0, 255);
if (info[2]->IsArray()) {
Local<Object> objColor = info[2]->ToObject();
color = setColor(objColor);
}
int thickness = info.Length() < 4 ? 1 : info[3]->NumberValue();
int lineType = info.Length() < 5 ? 8 : info[4]->NumberValue();
int maxLevel = info.Length() < 6 ? 0 : info[5]->NumberValue();
cv::Point offset;
if (info.Length() == 6) {
Local<Array> _offset = Local<Array>::Cast(info[5]);
offset = cv::Point(
Nan::To<int>(Nan::Get(_offset, 0).ToLocalChecked()).FromJust(),
Nan::To<int>(Nan::Get(_offset, 1).ToLocalChecked()).FromJust()
);
}
cv::drawContours(self->mat, cont->contours, pos, color, thickness, lineType, cont->hierarchy, maxLevel, offset);
return;
}
NAN_METHOD(Matrix::DrawAllContours) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Contour *cont = Nan::ObjectWrap::Unwrap<Contour>(info[0]->ToObject());
cv::Scalar color(0, 0, 255);
if (info[1]->IsArray()) {
Local<Object> objColor = info[1]->ToObject();
color = setColor(objColor);
}
int thickness = info.Length() < 3 ? 1 : info[2]->NumberValue();
cv::drawContours(self->mat, cont->contours, -1, color, thickness);
return;
}
NAN_METHOD(Matrix::GoodFeaturesToTrack) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int maxCorners = info.Length() >= 1 ? info[0]->IntegerValue() : 500;
double qualityLevel = info.Length() >= 2 ? (double) info[1]->NumberValue() : 0.01;
double minDistance = info.Length() >= 3 ? (double) info[2]->NumberValue() : 10;
int blockSize = info.Length() >= 4 ? info[3]->IntegerValue() : 3;
bool useHarrisDetector = info.Length() >= 5 ? info[4]->BooleanValue() : false;
double k = info.Length() >= 6 ? (double) info[5]->NumberValue() : 0.04;
std::vector<cv::Point2f> corners;
cv::Mat gray;
if (self->mat.channels() == 1) {
gray = self->mat;
} else {
cvtColor(self->mat, gray, CV_BGR2GRAY);
equalizeHist(gray, gray);
}
cv::goodFeaturesToTrack(gray, corners, maxCorners, qualityLevel, minDistance, cv::noArray(), blockSize, useHarrisDetector, k);
v8::Local<v8::Array> arr = Nan::New<Array>(corners.size());
for (unsigned int i=0; i<corners.size(); i++) {
v8::Local<v8::Array> pt = Nan::New<Array>(2);
pt->Set(0, Nan::New<Number>((double) corners[i].x));
pt->Set(1, Nan::New<Number>((double) corners[i].y));
arr->Set(i, pt);
}
info.GetReturnValue().Set(arr);
}
#ifdef HAVE_OPENCV_VIDEO
NAN_METHOD(Matrix::CalcOpticalFlowPyrLK) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *newMatrix = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Local<Array> points = Local<Array>::Cast(info[1]->ToObject());
std::vector<cv::Point2f> old_points;
for (unsigned int i=0; i<points->Length(); i++) {
Local<Object> pt = points->Get(i)->ToObject();
old_points.push_back(cv::Point2f(pt->Get(0)->NumberValue(), pt->Get(1)->NumberValue()));
}
cv::Size winSize;
if (info.Length() >= 3 && info[2]->IsArray()) {
Local<Object> winSizeObj = info[2]->ToObject();
winSize = cv::Size(winSizeObj->Get(0)->IntegerValue(), winSizeObj->Get(1)->IntegerValue());
} else {
winSize = cv::Size(21, 21);
}
int maxLevel = info.Length() >= 4 ? info[3]->IntegerValue() : 3;
cv::TermCriteria criteria;
if (info.Length() >= 5 && info[4]->IsArray()) {
Local<Object> criteriaObj = info[4]->ToObject();
criteria = cv::TermCriteria(criteriaObj->Get(0)->IntegerValue(), criteriaObj->Get(1)->IntegerValue(), (double) criteriaObj->Get(2)->NumberValue());
} else {
criteria = cv::TermCriteria(cv::TermCriteria::COUNT + cv::TermCriteria::EPS, 30, 0.01);
}
int flags = info.Length() >= 6 ? info[5]->IntegerValue() : 0;
double minEigThreshold = info.Length() >= 7 ? info[6]->NumberValue() : 1e-4;
cv::Mat old_gray;
cv::cvtColor(self->mat, old_gray, CV_BGR2GRAY);
cv::Mat new_gray;
cv::cvtColor(newMatrix->mat, new_gray, CV_BGR2GRAY);
std::vector<cv::Point2f> new_points;
std::vector<uchar> status;
std::vector<float> err;
cv::calcOpticalFlowPyrLK(old_gray, new_gray, old_points, new_points, status, err, winSize, maxLevel, criteria, flags, minEigThreshold);
v8::Local<v8::Array> old_arr = Nan::New<Array>(old_points.size());
v8::Local<v8::Array> new_arr = Nan::New<Array>(new_points.size());
v8::Local<v8::Array> found = Nan::New<Array>(status.size());
for (unsigned int i=0; i<old_points.size(); i++) {
v8::Local<v8::Array> pt = Nan::New<Array>(2);
pt->Set(0, Nan::New<Number>((double) old_points[i].x));
pt->Set(1, Nan::New<Number>((double) old_points[i].y));
old_arr->Set(i, pt);
}
for (unsigned int i=0; i<new_points.size(); i++) {
v8::Local<v8::Array> pt = Nan::New<Array>(2);
pt->Set(0, Nan::New<Number>((double) new_points[i].x));
pt->Set(1, Nan::New<Number>((double) new_points[i].y));
new_arr->Set(i, pt);
}
for (unsigned int i=0; i<status.size(); i++) {
v8::Local<v8::Integer> pt = Nan::New<Integer>((int)status[i]);
found->Set(i, pt);
}
Local<Object> data = Nan::New<Object>();
data->Set(Nan::New<String>("old_points").ToLocalChecked(), old_arr);
data->Set(Nan::New<String>("new_points").ToLocalChecked(), new_arr);
data->Set(Nan::New<String>("found").ToLocalChecked(), found);
info.GetReturnValue().Set(data);
}
#endif
NAN_METHOD(Matrix::HoughLinesP) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
double rho = info.Length() < 1 ? 1 : info[0]->NumberValue();
double theta = info.Length() < 2 ? CV_PI/180 : info[1]->NumberValue();
int threshold = info.Length() < 3 ? 80 : info[2]->Uint32Value();
double minLineLength = info.Length() < 4 ? 30 : info[3]->NumberValue();
double maxLineGap = info.Length() < 5 ? 10 : info[4]->NumberValue();
std::vector<cv::Vec4i> lines;
cv::Mat gray;
equalizeHist(self->mat, gray);
// cv::Canny(gray, gray, 50, 200, 3);
cv::HoughLinesP(gray, lines, rho, theta, threshold, minLineLength, maxLineGap);
v8::Local<v8::Array> arr = Nan::New<Array>(lines.size());
for (unsigned int i=0; i<lines.size(); i++) {
v8::Local<v8::Array> pt = Nan::New<Array>(4);
pt->Set(0, Nan::New<Number>((double) lines[i][0]));
pt->Set(1, Nan::New<Number>((double) lines[i][1]));
pt->Set(2, Nan::New<Number>((double) lines[i][2]));
pt->Set(3, Nan::New<Number>((double) lines[i][3]));
arr->Set(i, pt);
}
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::HoughCircles) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
double dp = info.Length() < 1 ? 1 : info[0]->NumberValue();
double minDist = info.Length() < 2 ? 1 : info[1]->NumberValue();
double higherThreshold = info.Length() < 3 ? 100 : info[2]->NumberValue();
double accumulatorThreshold = info.Length() < 4 ? 100 : info[3]->NumberValue();
int minRadius = info.Length() < 5 ? 0 : info[4]->Uint32Value();
int maxRadius = info.Length() < 6 ? 0 : info[5]->Uint32Value();
std::vector<cv::Vec3f> circles;
cv::Mat gray;
equalizeHist(self->mat, gray);
cv::HoughCircles(gray, circles, CV_HOUGH_GRADIENT, dp, minDist,
higherThreshold, accumulatorThreshold, minRadius, maxRadius);
v8::Local<v8::Array> arr = Nan::New<Array>(circles.size());
for (unsigned int i=0; i < circles.size(); i++) {
v8::Local<v8::Array> pt = Nan::New<Array>(3);
pt->Set(0, Nan::New<Number>((double) circles[i][0])); // center x
pt->Set(1, Nan::New<Number>((double) circles[i][1]));// center y
pt->Set(2, Nan::New<Number>((double) circles[i][2]));// radius
arr->Set(i, pt);
}
info.GetReturnValue().Set(arr);
}
cv::Scalar setColor(Local<Object> objColor) {
int64_t channels[4] = { 0, 0, 0, 0 };
// We'll accomodate a channel count up to 4 and fall back to the old
// "assume it's always 3" in the default case
if (!objColor->HasRealIndexedProperty(1)) {
channels[0] = objColor->Get(0)->IntegerValue();
} else if (!objColor->HasRealIndexedProperty(2)) {
channels[0] = objColor->Get(0)->IntegerValue();
channels[1] = objColor->Get(1)->IntegerValue();
} else if (!objColor->HasRealIndexedProperty(4)) {
channels[0] = objColor->Get(0)->IntegerValue();
channels[1] = objColor->Get(1)->IntegerValue();
channels[2] = objColor->Get(2)->IntegerValue();
channels[3] = objColor->Get(3)->IntegerValue();
} else {
channels[0] = objColor->Get(0)->IntegerValue();
channels[1] = objColor->Get(1)->IntegerValue();
channels[2] = objColor->Get(2)->IntegerValue();
}
return cv::Scalar(channels[0], channels[1], channels[2], channels[3]);
}
cv::Point setPoint(Local<Object> objPoint) {
return cv::Point(objPoint->Get(0)->IntegerValue(),
objPoint->Get(1)->IntegerValue());
}
cv::Rect* setRect(Local<Object> objRect, cv::Rect &result) {
if (!objRect->IsArray() || !objRect->Get(0)->IsArray()
|| !objRect->Get(0)->IsArray()) {
printf("error");
return 0;
};
Local < Object > point = objRect->Get(0)->ToObject();
Local < Object > size = objRect->Get(1)->ToObject();
result.x = point->Get(0)->IntegerValue();
result.y = point->Get(1)->IntegerValue();
result.width = size->Get(0)->IntegerValue();
result.height = size->Get(1)->IntegerValue();
return &result;
}
class ResizeASyncWorker: public Nan::AsyncWorker {
public:
ResizeASyncWorker(Nan::Callback *callback, cv::Mat image, cv::Size size, double fx, double fy, int interpolation) :
Nan::AsyncWorker(callback),
image(image), // here, the cv::Mat is duplicated, adding to refcount without data copy
dest(NULL),
size(size),
fx(fx),
fy(fy),
interpolation(interpolation),
success(0) {
}
~ResizeASyncWorker() {
// don't leave this if it was allocated
// could happen if NaN does not call HandleSuccess?
delete dest;
dest = NULL;
// cv::Mat image will be deleted, which will reduce refcount
}
void Execute() {
try {
dest = new Matrix();
cv::resize(image, dest->mat, size, fx, fy, interpolation);
success = 1;
} catch(...){
success = 0;
}
}
void HandleOKCallback() {
Nan::HandleScope scope;
if (success){
try{
Local<Object> im_to_return= Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(im_to_return);
img->mat = dest->mat;
delete dest;
dest = NULL;
Local<Value> argv[] = {
Nan::Null(), // err
im_to_return //result
};
Nan::TryCatch try_catch;
callback->Call(2, argv);
if (try_catch.HasCaught()) {
Nan::FatalException(try_catch);
}
} catch (...){
delete dest;
dest = NULL;
Local<Value> argv[] = {
Nan::New("C++ exception wrapping response").ToLocalChecked(), // err
Nan::Null() // result
};
Nan::TryCatch try_catch;
callback->Call(2, argv);
if (try_catch.HasCaught()) {
Nan::FatalException(try_catch);
}
}
} else {
delete dest;
dest = NULL;
Local<Value> argv[] = {
Nan::New("C++ exception").ToLocalChecked(), // err
Nan::Null() //result
};
Nan::TryCatch try_catch;
callback->Call(2, argv);
if (try_catch.HasCaught()) {
Nan::FatalException(try_catch);
}
}
}
private:
cv::Mat image;
Matrix *dest;
cv::Size size;
double fx;
double fy;
int interpolation;
int success;
};
NAN_METHOD(Matrix::Resize) {
SETUP_FUNCTION(Matrix)
if (info.Length() < 2) {
return Nan::ThrowError("Matrix.resize requires at least 2 argument2");
}
//im.resize( width, height );
//im.resize( width, height, fx, fy );
//im.resize( width, height, interpolation );
//im.resize( width, height, fx, fy, interpolation );
// if fn is added on the end, makes it Async
int numargs = info.Length();
int isAsync = 0;
if (info[numargs-1]->IsFunction()){
isAsync = 1;
}
if (info.Length() < 2+isAsync) {
return Nan::ThrowError("Matrix.resize requires at least x and y size argument2");
}
int x = info[0]->Uint32Value();
int y = info[1]->Uint32Value();
cv::Size size(x, y);
if (size.area() == 0) {
return Nan::ThrowError("Area of size must be > 0");
}
double fx = 0;
double fy = 0;
int interpolation = cv::INTER_LINEAR;
// if 4 or more args, then expect fx, fy next
if (numargs >= 4+isAsync) {
DOUBLE_FROM_ARGS(fx, 2)
DOUBLE_FROM_ARGS(fy, 3)
if (numargs == 5+isAsync) {
INT_FROM_ARGS(interpolation, 5)
}
} else {
// if 3 args after possible function, expect interpolation
if (numargs == 3+isAsync) {
INT_FROM_ARGS(interpolation, 3)
}
}
// if async
if (isAsync){
REQ_FUN_ARG(numargs-1, cb);
Nan::Callback *callback = new Nan::Callback(cb.As<Function>());
Nan::AsyncQueueWorker(new ResizeASyncWorker(callback, self->mat, size, fx, fy, interpolation));
info.GetReturnValue().Set(Nan::Null());
} else {
try{
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
cv::Mat res = cv::Mat(x, y, CV_32FC3);
cv::resize(self->mat, res, cv::Size(x, y), 0, 0, interpolation);
~self->mat;
self->mat = res;
} catch (...){
return Nan::ThrowError("c++ Exception processing resize");
}
}
}
NAN_METHOD(Matrix::Rotate) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
cv::Mat rotMatrix(2, 3, CV_32FC1);
cv::Mat res;
float angle = Nan::To<double>(info[0]).FromJust();
// Modification by SergeMv
//-------------
// If you provide only the angle argument and the angle is multiple of 90, then
// we do a fast thing
bool rightOrStraight = (ceil(angle) == angle) && (!((int)angle % 90))
&& (info.Length() == 1);
if (rightOrStraight) {
int angle2 = ((int)angle) % 360;
if (!angle2) {return;}
if (angle2 < 0) {angle2 += 360;}
// See if we do right angle rotation, we transpose the matrix:
if (angle2 % 180) {
cv::transpose(self->mat, res);
~self->mat;
self->mat = res;
}
// Now flip the image
int mode = -1;// flip around both axes
// If counterclockwise, flip around the x-axis
if (angle2 == 90) {mode = 0;}
// If clockwise, flip around the y-axis
if (angle2 == 270) {mode = 1;}
cv::flip(self->mat, self->mat, mode);
return;
}
//-------------
int x = info[1]->IsUndefined() ? round(self->mat.size().width / 2) :
info[1]->Uint32Value();
int y = info[1]->IsUndefined() ? round(self->mat.size().height / 2) :
info[2]->Uint32Value();
cv::Point center = cv::Point(x,y);
rotMatrix = getRotationMatrix2D(center, angle, 1.0);
cv::warpAffine(self->mat, res, rotMatrix, self->mat.size());
~self->mat;
self->mat = res;
return;
}
NAN_METHOD(Matrix::GetRotationMatrix2D) {
Nan::HandleScope scope;
if (info.Length() < 3) {
JSTHROW("Invalid number of arguments");
}
float angle = Nan::To<double>(info[0]).FromJust();
int x = Nan::To<uint32_t>(info[1]).FromJust();
int y = Nan::To<uint32_t>(info[2]).FromJust();
double scale = Nan::To<double>(info[3]).FromMaybe(1.0);
Local<Object> img_to_return =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
cv::Point center = cv::Point(x,y);
img->mat = getRotationMatrix2D(center, angle, scale);
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::WarpAffine) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
cv::Mat res;
Matrix *rotMatrix = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
// Resize the image if size is specified
int dstRows = info[1]->IsUndefined() ? self->mat.rows : info[1]->Uint32Value();
int dstCols = info[2]->IsUndefined() ? self->mat.cols : info[2]->Uint32Value();
cv::Size resSize = cv::Size(dstRows, dstCols);
cv::warpAffine(self->mat, res, rotMatrix->mat, resSize);
~self->mat;
self->mat = res;
return;
}
NAN_METHOD(Matrix::PyrDown) {
SETUP_FUNCTION(Matrix)
cv::pyrDown(self->mat, self->mat);
return;
}
NAN_METHOD(Matrix::PyrUp) {
SETUP_FUNCTION(Matrix)
cv::pyrUp(self->mat, self->mat);
return;
}
NAN_METHOD(Matrix::inRange) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
/*if (self->mat.channels() != 3)
Nan::ThrowError(String::New("Image is no 3-channel"));*/
if (info[0]->IsArray() && info[1]->IsArray()) {
Local<Object> args_lowerb = info[0]->ToObject();
Local<Object> args_upperb = info[1]->ToObject();
cv::Scalar lowerb(0, 0, 0);
cv::Scalar upperb(0, 0, 0);
lowerb = setColor(args_lowerb);
upperb = setColor(args_upperb);
cv::Mat mask;
cv::inRange(self->mat, lowerb, upperb, mask);
mask.copyTo(self->mat);
}
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::AdjustROI) {
SETUP_FUNCTION(Matrix)
int dtop = info[0]->Uint32Value();
int dbottom = info[1]->Uint32Value();
int dleft = info[2]->Uint32Value();
int dright = info[3]->Uint32Value();
self->mat.adjustROI(dtop, dbottom, dleft, dright);
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::LocateROI) {
SETUP_FUNCTION(Matrix)
cv::Size wholeSize;
cv::Point ofs;
self->mat.locateROI(wholeSize, ofs);
v8::Local < v8::Array > arr = Nan::New<Array>(4);
arr->Set(0, Nan::New<Number>(wholeSize.width));
arr->Set(1, Nan::New<Number>(wholeSize.height));
arr->Set(2, Nan::New<Number>(ofs.x));
arr->Set(3, Nan::New<Number>(ofs.y));
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::Threshold) {
SETUP_FUNCTION(Matrix)
double threshold = info[0]->NumberValue();
double maxVal = info[1]->NumberValue();
int typ = cv::THRESH_BINARY;
if (info.Length() >= 3) {
Nan::Utf8String typstr(info[2]);
if (strcmp(*typstr, "Binary") == 0) {
// Uses default value
}
else if (strcmp(*typstr, "Binary Inverted") == 0) {
typ = cv::THRESH_BINARY_INV;
}
else if (strcmp(*typstr, "Threshold Truncated") == 0) {
typ = cv::THRESH_TRUNC;
}
else if (strcmp(*typstr, "Threshold to Zero") == 0) {
typ = cv::THRESH_TOZERO;
}
else if (strcmp(*typstr, "Threshold to Zero Inverted") == 0) {
typ = cv::THRESH_TOZERO_INV;
}
else {
char *typeString = *typstr;
char text[] = "\" is no supported binarization technique. "
"Use \"Binary\" (default), \"Binary Inverted\", "
"\"Threshold Truncated\", \"Threshold to Zero\" "
"or \"Threshold to Zero Inverted\"";
char *errorMessage;
errorMessage = new char[strlen(typeString) + strlen(text) + 2];
strcpy(errorMessage, "\"");
strcat(errorMessage, typeString);
strcat(errorMessage, text);
Nan::ThrowError(errorMessage);
return;
}
}
if (info.Length() >= 4) {
Nan::Utf8String algorithm(info[3]);
if (strcmp(*algorithm, "Simple") == 0) {
// Uses default
}
else if (strcmp(*algorithm, "Otsu") == 0) {
typ += 8;
}
else {
char *algo = *algorithm;
char text[] = "\" is no supported threshold algorithm. "
"Use \"Simple\" (default) or \"Otsu\".";
char *errorMessage;
errorMessage = new char[strlen(algo) + strlen(text) + 2];
strcpy(errorMessage, "\"");
strcat(errorMessage, algo);
strcat(errorMessage, text);
Nan::ThrowError(errorMessage);
return;
}
}
Local < Object > img_to_return =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
self->mat.copyTo(img->mat);
cv::threshold(self->mat, img->mat, threshold, maxVal, typ);
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::AdaptiveThreshold) {
SETUP_FUNCTION(Matrix)
double maxVal = info[0]->NumberValue();
double adaptiveMethod = info[1]->NumberValue();
double thresholdType = info[2]->NumberValue();
double blockSize = info[3]->NumberValue();
double C = info[4]->NumberValue();
Local < Object > img_to_return =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
self->mat.copyTo(img->mat);
cv::adaptiveThreshold(self->mat, img->mat, maxVal, adaptiveMethod,
thresholdType, blockSize, C);
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::MeanStdDev) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Local<Object> mean = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_mean = Nan::ObjectWrap::Unwrap<Matrix>(mean);
Local<Object> stddev = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_stddev = Nan::ObjectWrap::Unwrap<Matrix>(stddev);
cv::meanStdDev(self->mat, m_mean->mat, m_stddev->mat);
Local<Object> data = Nan::New<Object>();
data->Set(Nan::New<String>("mean").ToLocalChecked(), mean);
data->Set(Nan::New<String>("stddev").ToLocalChecked(), stddev);
info.GetReturnValue().Set(data);
}
// @author SergeMv
// Copies our (small) image into a ROI of another (big) image
// @param Object another image (destination)
// @param Number Destination x (where our image is to be copied)
// @param Number Destination y (where our image is to be copied)
// Example: smallImg.copyTo(bigImg, 50, 50);
// Note, x,y and width and height of our image must be so that
// our.width + x <= destination.width (and the same for y and height)
// both x and y must be >= 0
NAN_METHOD(Matrix::CopyTo) {
Nan::HandleScope scope;
Matrix * self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int width = self->mat.size().width;
int height = self->mat.size().height;
// param 0 - destination image:
Matrix *dest = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
// param 1 - x coord of the destination
int x = info[1]->IntegerValue();
// param 2 - y coord of the destination
int y = info[2]->IntegerValue();
cv::Mat dstROI = cv::Mat(dest->mat, cv::Rect(x, y, width, height));
self->mat.copyTo(dstROI);
return;
}
/**
* Converts an array to another data type with optional scaling
* Reference: http://docs.opencv.org/2.4/modules/core/doc/basic_structures.html#mat-convertto
*/
NAN_METHOD(Matrix::ConvertTo) {
SETUP_FUNCTION(Matrix)
if (info.Length() < 2) {
JSTHROW("Invalid number of arguments");
}
// param 0 - destination image
Matrix *dest = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
// param 1 - desired matrix type
int rtype = -1;
INT_FROM_ARGS(rtype, 1);
// param 2 - alpha
double alpha = 1;
if (info.Length() >= 3) {
DOUBLE_FROM_ARGS(alpha, 2);
}
// param 3 - beta
double beta = 0;
if (info.Length() >= 4) {
DOUBLE_FROM_ARGS(beta, 3);
}
self->mat.convertTo(dest->mat, rtype, alpha, beta);
return;
}
// @author SergeMv
// Does in-place color transformation
// img.cvtColor('CV_BGR2YCrCb');
NAN_METHOD(Matrix::CvtColor) {
Nan::HandleScope scope;
Matrix * self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (info.Length() < 1) {
Nan::ThrowTypeError("Invalid number of arguments");
}
// Get transform string
v8::String::Utf8Value str (info[0]->ToString());
std::string str2 = std::string(*str);
const char * sTransform = (const char *) str2.c_str();
int iTransform;
if (!strcmp(sTransform, "CV_BGR2GRAY")) {
iTransform = CV_BGR2GRAY;
} else if (!strcmp(sTransform, "CV_GRAY2BGR")) {
iTransform = CV_GRAY2BGR;
} else if (!strcmp(sTransform, "CV_BGR2XYZ")) {
iTransform = CV_BGR2XYZ;
} else if (!strcmp(sTransform, "CV_XYZ2BGR")) {
iTransform = CV_XYZ2BGR;
} else if (!strcmp(sTransform, "CV_BGR2YCrCb")) {
iTransform = CV_BGR2YCrCb;
} else if (!strcmp(sTransform, "CV_YCrCb2BGR")) {
iTransform = CV_YCrCb2BGR;
} else if (!strcmp(sTransform, "CV_BGR2HSV")) {
iTransform = CV_BGR2HSV;
} else if (!strcmp(sTransform, "CV_HSV2BGR")) {
iTransform = CV_HSV2BGR;
} else if (!strcmp(sTransform, "CV_BGR2HLS")) {
iTransform = CV_BGR2HLS;
} else if (!strcmp(sTransform, "CV_HLS2BGR")) {
iTransform = CV_HLS2BGR;
} else if (!strcmp(sTransform, "CV_BGR2Lab")) {
iTransform = CV_BGR2Lab;
} else if (!strcmp(sTransform, "CV_Lab2BGR")) {
iTransform = CV_Lab2BGR;
} else if (!strcmp(sTransform, "CV_BGR2Luv")) {
iTransform = CV_BGR2Luv;
} else if (!strcmp(sTransform, "CV_Luv2BGR")) {
iTransform = CV_Luv2BGR;
} else if (!strcmp(sTransform, "CV_BayerBG2BGR")) {
iTransform = CV_BayerBG2BGR;
} else if (!strcmp(sTransform, "CV_BayerGB2BGR")) {
iTransform = CV_BayerGB2BGR;
} else if (!strcmp(sTransform, "CV_BayerRG2BGR")) {
iTransform = CV_BayerRG2BGR;
} else if (!strcmp(sTransform, "CV_BayerGR2BGR")) {
iTransform = CV_BayerGR2BGR;
} else if (!strcmp(sTransform, "CV_BGR2RGB")) {
iTransform = CV_BGR2RGB;
} else {
iTransform = 0; // to avoid compiler warning
Nan::ThrowTypeError("Conversion code is unsupported");
}
cv::cvtColor(self->mat, self->mat, iTransform);
return;
}
// @author SergeMv
// arrChannels = img.split();
NAN_METHOD(Matrix::Split) {
Nan::HandleScope scope;
Matrix * self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
unsigned int size = self->mat.channels();
std::vector<cv::Mat> channels;
// Split doesn't seem to work on empty vectors
for (unsigned int i = 0; i < size; i++) {
channels.push_back(cv::Mat());
}
cv::split(self->mat, channels);
size = channels.size();
v8::Local<v8::Array> arrChannels = Nan::New<Array>(size);
for (unsigned int i = 0; i < size; i++) {
Local<Object> matObject =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix * m = Nan::ObjectWrap::Unwrap<Matrix>(matObject);
m->mat = channels[i];
arrChannels->Set(i, matObject);
}
info.GetReturnValue().Set(arrChannels);
}
// @author SergeMv
// img.merge(arrChannels);
NAN_METHOD(Matrix::Merge) {
Nan::HandleScope scope;
Matrix * self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
if (!info[0]->IsArray()) {
Nan::ThrowTypeError("The argument must be an array");
}
v8::Local<v8::Array> jsChannels = v8::Local<v8::Array>::Cast(info[0]);
unsigned int L = jsChannels->Length();
std::vector<cv::Mat> vChannels(L);
for (unsigned int i = 0; i < L; i++) {
Matrix * matObject = Nan::ObjectWrap::Unwrap<Matrix>(jsChannels->Get(i)->ToObject());
vChannels[i] = matObject->mat;
}
cv::merge(vChannels, self->mat);
return;
}
// @author SergeMv
// Equalizes histogram
// img.equalizeHist()
NAN_METHOD(Matrix::EqualizeHist) {
Nan::HandleScope scope;
Matrix * self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
cv::equalizeHist(self->mat, self->mat);
return;
}
NAN_METHOD(Matrix::FloodFill) {
SETUP_FUNCTION(Matrix)
// obj->Get(Nan::New<String>("x").ToLocalChecked())
// int cv::floodFill(cv::InputOutputArray, cv::Point, cv::Scalar, cv::Rect*, cv::Scalar, cv::Scalar, int)
/* mat.floodFill( {seedPoint: [1,1] ,
newColor: [255,0,0] ,
rect:[[0,2],[30,40]] ,
loDiff : [8,90,60],
upDiff:[10,100,70]
}); */
if (info.Length() < 1 || !info[0]->IsObject()) {
// error
}
Local < Object > obj = info[0]->ToObject();
cv::Rect rect;
int ret = cv::floodFill(self->mat,
setPoint(obj->Get(Nan::New<String>("seedPoint").ToLocalChecked())->ToObject()),
setColor(obj->Get(Nan::New<String>("newColor").ToLocalChecked())->ToObject()),
obj->Get(Nan::New<String>("rect").ToLocalChecked())->IsUndefined() ?
0 : setRect(obj->Get(Nan::New<String>("rect").ToLocalChecked())->ToObject(), rect),
setColor(obj->Get(Nan::New<String>("loDiff").ToLocalChecked())->ToObject()),
setColor(obj->Get(Nan::New<String>("upDiff").ToLocalChecked())->ToObject()), 4);
info.GetReturnValue().Set(Nan::New<Number>(ret));
}
// @author olfox
// Returns an array of the most probable positions
// Usage: output = input.templateMatches(min_probability, max_probability, limit, ascending, min_x_distance, min_y_distance);
NAN_METHOD(Matrix::TemplateMatches) {
SETUP_FUNCTION(Matrix)
bool filter_min_probability =
(info.Length() >= 1) ? info[0]->IsNumber() : false;
bool filter_max_probability =
(info.Length() >= 2) ? info[1]->IsNumber() : false;
double min_probability = filter_min_probability ? info[0]->NumberValue() : 0;
double max_probability = filter_max_probability ? info[1]->NumberValue() : 0;
int limit = (info.Length() >= 3) ? info[2]->IntegerValue() : 0;
bool ascending = (info.Length() >= 4) ? info[3]->BooleanValue() : false;
int min_x_distance = (info.Length() >= 5) ? info[4]->IntegerValue() : 0;
int min_y_distance = (info.Length() >= 6) ? info[5]->IntegerValue() : 0;
cv::Mat_<int> indices;
if (ascending) {
cv::sortIdx(self->mat.reshape(0, 1), indices,
CV_SORT_ASCENDING + CV_SORT_EVERY_ROW);
} else {
cv::sortIdx(self->mat.reshape(0, 1), indices,
CV_SORT_DESCENDING + CV_SORT_EVERY_ROW);
}
cv::Mat hit_mask = cv::Mat::zeros(self->mat.size(), CV_64F);
v8::Local < v8::Array > probabilites_array = Nan::New<v8::Array>(limit);
cv::Mat_<float>::const_iterator begin = self->mat.begin<float>();
cv::Mat_<int>::const_iterator it = indices.begin();
cv::Mat_<int>::const_iterator end = indices.end();
int index = 0;
for (; (limit == 0 || index < limit) && it != end; ++it) {
cv::Point pt = (begin + *it).pos();
float probability = self->mat.at<float>(pt.y, pt.x);
if (filter_min_probability && probability < min_probability) {
if (ascending) {
continue;
}
else {
break;
}
}
if (filter_max_probability && probability > max_probability) {
if (ascending)
break;
else
continue;
}
if (min_x_distance != 0 || min_y_distance != 0) {
// Check hit mask color for for every corner
cv::Size maxSize = hit_mask.size();
int max_x = maxSize.width - 1;
int max_y = maxSize.height - 1;
cv::Point top_left = cv::Point(std::max(0, pt.x - min_x_distance),
std::max(0, pt.y - min_y_distance));
cv::Point top_right = cv::Point(std::min(max_x, pt.x + min_x_distance),
std::max(0, pt.y - min_y_distance));
cv::Point bottom_left = cv::Point(std::max(0, pt.x - min_x_distance),
std::min(max_y, pt.y + min_y_distance));
cv::Point bottom_right = cv::Point(std::min(max_x, pt.x + min_x_distance),
std::min(max_y, pt.y + min_y_distance));
if (hit_mask.at<double>(top_left.y, top_left.x) > 0)
continue;
if (hit_mask.at<double>(top_right.y, top_right.x) > 0)
continue;
if (hit_mask.at<double>(bottom_left.y, bottom_left.x) > 0)
continue;
if (hit_mask.at<double>(bottom_right.y, bottom_right.x) > 0)
continue;
cv::Scalar color(255.0);
cv::rectangle(hit_mask, top_left, bottom_right, color, CV_FILLED);
}
Local<Value> x_value = Nan::New<Number>(pt.x);
Local<Value> y_value = Nan::New<Number>(pt.y);
Local<Value> probability_value = Nan::New<Number>(probability);
Local < Object > probability_object = Nan::New<Object>();
probability_object->Set(Nan::New<String>("x").ToLocalChecked(), x_value);
probability_object->Set(Nan::New<String>("y").ToLocalChecked(), y_value);
probability_object->Set(Nan::New<String>("probability").ToLocalChecked(), probability_value);
probabilites_array->Set(index, probability_object);
index++;
}
info.GetReturnValue().Set(probabilites_array);
}
// @author Evilcat325
// MatchTemplate accept a Matrix
// Usage: output = input.matchTemplateByMatrix(matrix. method);
NAN_METHOD(Matrix::MatchTemplateByMatrix) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *templ = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
int cols = self->mat.cols - templ->mat.cols + 1;
int rows = self->mat.rows - templ->mat.rows + 1;
m_out->mat.create(cols, rows, CV_32FC1);
/*
TM_SQDIFF =0
TM_SQDIFF_NORMED =1
TM_CCORR =2
TM_CCORR_NORMED =3
TM_CCOEFF =4
TM_CCOEFF_NORMED =5
*/
int method = (info.Length() < 2) ? (int)cv::TM_CCORR_NORMED : info[1]->Uint32Value();
if (!(method >= 0 && method <= 5)) method = (int)cv::TM_CCORR_NORMED;
cv::matchTemplate(self->mat, templ->mat, m_out->mat, method);
info.GetReturnValue().Set(out);
}
// @author ytham
// Match Template filter
// Usage: output = input.matchTemplate("templateFileString", method);
NAN_METHOD(Matrix::MatchTemplate) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
v8::String::Utf8Value args0(info[0]->ToString());
std::string filename = std::string(*args0);
cv::Mat templ;
templ = cv::imread(filename, -1);
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
int cols = self->mat.cols - templ.cols + 1;
int rows = self->mat.rows - templ.rows + 1;
m_out->mat.create(cols, rows, CV_32FC1);
/*
TM_SQDIFF =0
TM_SQDIFF_NORMED =1
TM_CCORR =2
TM_CCORR_NORMED =3
TM_CCOEFF =4
TM_CCOEFF_NORMED =5
*/
int method = (info.Length() < 2) ? (int)cv::TM_CCORR_NORMED : info[1]->Uint32Value();
cv::matchTemplate(self->mat, templ, m_out->mat, method);
cv::normalize(m_out->mat, m_out->mat, 0, 1, cv::NORM_MINMAX, -1, cv::Mat());
double minVal;
double maxVal;
cv::Point minLoc;
cv::Point maxLoc;
cv::Point matchLoc;
minMaxLoc(m_out->mat, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat());
if(method == CV_TM_SQDIFF || method == CV_TM_SQDIFF_NORMED) {
matchLoc = minLoc;
}
else {
matchLoc = maxLoc;
}
//detected ROI
unsigned int roi_x = matchLoc.x;
unsigned int roi_y = matchLoc.y;
unsigned int roi_width = templ.cols;
unsigned int roi_height = templ.rows;
//draw rectangle
if(info.Length() >= 3) {
cv::Rect roi(roi_x,roi_y,roi_width,roi_height);
cv::rectangle(self->mat, roi, cv::Scalar(0,0,255));
}
m_out->mat.convertTo(m_out->mat, CV_8UC1, 255, 0);
v8::Local <v8::Array> arr = Nan::New<v8::Array>(5);
arr->Set(0, out);
arr->Set(1, Nan::New<Number>(roi_x));
arr->Set(2, Nan::New<Number>(roi_y));
arr->Set(3, Nan::New<Number>(roi_width));
arr->Set(4, Nan::New<Number>(roi_height));
info.GetReturnValue().Set(arr);
}
// @author ytham
// Min/Max location
NAN_METHOD(Matrix::MinMaxLoc) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
double minVal; double maxVal; cv::Point minLoc; cv::Point maxLoc;
cv::minMaxLoc(self->mat, &minVal, &maxVal, &minLoc, &maxLoc, cv::Mat() );
Local<Value> v_minVal = Nan::New<Number>(minVal);
Local<Value> v_maxVal = Nan::New<Number>(maxVal);
Local<Value> v_minLoc_x = Nan::New<Number>(minLoc.x);
Local<Value> v_minLoc_y = Nan::New<Number>(minLoc.y);
Local<Value> v_maxLoc_x = Nan::New<Number>(maxLoc.x);
Local<Value> v_maxLoc_y = Nan::New<Number>(maxLoc.y);
Local<Object> o_minLoc = Nan::New<Object>();
o_minLoc->Set(Nan::New<String>("x").ToLocalChecked(), v_minLoc_x);
o_minLoc->Set(Nan::New<String>("y").ToLocalChecked(), v_minLoc_y);
Local<Object> o_maxLoc = Nan::New<Object>();
o_maxLoc->Set(Nan::New<String>("x").ToLocalChecked(), v_maxLoc_x);
o_maxLoc->Set(Nan::New<String>("y").ToLocalChecked(), v_maxLoc_y);
// Output result object
Local<Object> result = Nan::New<Object>();
result->Set(Nan::New<String>("minVal").ToLocalChecked(), v_minVal);
result->Set(Nan::New<String>("maxVal").ToLocalChecked(), v_maxVal);
result->Set(Nan::New<String>("minLoc").ToLocalChecked(), o_minLoc);
result->Set(Nan::New<String>("maxLoc").ToLocalChecked(), o_maxLoc);
info.GetReturnValue().Set(result);
}
// @author ytham
// Pushes some matrix (argument) the back of a matrix (self)
NAN_METHOD(Matrix::PushBack) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Matrix *m_input = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
self->mat.push_back(m_input->mat);
info.GetReturnValue().Set(info.This());
}
NAN_METHOD(Matrix::PutText) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
Nan::Utf8String textString(info[0]); //FIXME: might cause issues, see here https://github.com/rvagg/nan/pull/152
char *text = *textString;//(char *) malloc(textString.length() + 1);
//strcpy(text, *textString);
int x = info[1]->IntegerValue();
int y = info[2]->IntegerValue();
Nan::Utf8String fontString(info[3]);
char *font = *fontString;//(char *) malloc(fontString.length() + 1);
//strcpy(font, *fontString);
int constFont = cv::FONT_HERSHEY_SIMPLEX;
if (!strcmp(font, "HERSEY_SIMPLEX")) {constFont = cv::FONT_HERSHEY_SIMPLEX;}
else if (!strcmp(font, "HERSEY_PLAIN")) {constFont = cv::FONT_HERSHEY_PLAIN;}
else if (!strcmp(font, "HERSEY_DUPLEX")) {constFont = cv::FONT_HERSHEY_DUPLEX;}
else if (!strcmp(font, "HERSEY_COMPLEX")) {constFont = cv::FONT_HERSHEY_COMPLEX;}
else if (!strcmp(font, "HERSEY_TRIPLEX")) {constFont = cv::FONT_HERSHEY_TRIPLEX;}
else if (!strcmp(font, "HERSEY_COMPLEX_SMALL")) {constFont = cv::FONT_HERSHEY_COMPLEX_SMALL;}
else if (!strcmp(font, "HERSEY_SCRIPT_SIMPLEX")) {constFont = cv::FONT_HERSHEY_SCRIPT_SIMPLEX;}
else if (!strcmp(font, "HERSEY_SCRIPT_COMPLEX")) {constFont = cv::FONT_HERSHEY_SCRIPT_COMPLEX;}
else if (!strcmp(font, "HERSEY_SCRIPT_SIMPLEX")) {constFont = cv::FONT_HERSHEY_SCRIPT_SIMPLEX;}
cv::Scalar color(0, 0, 255);
if (info[4]->IsArray()) {
Local<Object> objColor = info[4]->ToObject();
color = setColor(objColor);
}
double scale = info.Length() < 6 ? 1 : info[5]->NumberValue();
double thickness = info.Length() < 7 ? 1 : info[6]->NumberValue();
cv::putText(self->mat, text, cv::Point(x, y), constFont, scale, color, thickness);
return;
}
NAN_METHOD(Matrix::GetPerspectiveTransform) {
Nan::HandleScope scope;
// extract quad info
Local<Object> srcArray = info[0]->ToObject();
Local<Object> tgtArray = info[1]->ToObject();
std::vector<cv::Point2f> src_corners(4);
std::vector<cv::Point2f> tgt_corners(4);
for (unsigned int i = 0; i < 4; i++) {
src_corners[i] = cvPoint(srcArray->Get(i*2)->IntegerValue(),srcArray->Get(i*2+1)->IntegerValue());
tgt_corners[i] = cvPoint(tgtArray->Get(i*2)->IntegerValue(),tgtArray->Get(i*2+1)->IntegerValue());
}
Local<Object> xfrm = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *xfrmmat = Nan::ObjectWrap::Unwrap<Matrix>(xfrm);
xfrmmat->mat = cv::getPerspectiveTransform(src_corners, tgt_corners);
info.GetReturnValue().Set(xfrm);
}
NAN_METHOD(Matrix::WarpPerspective) {
SETUP_FUNCTION(Matrix)
Matrix *xfrm = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
int width = info[1]->IntegerValue();
int height = info[2]->IntegerValue();
int flags = cv::INTER_LINEAR;
int borderMode = cv::BORDER_REPLICATE;
cv::Scalar borderColor(0, 0, 255);
if (info[3]->IsArray()) {
Local < Object > objColor = info[3]->ToObject();
borderColor = setColor(objColor);
}
cv::Mat res = cv::Mat(width, height, CV_32FC3);
cv::warpPerspective(self->mat, res, xfrm->mat, cv::Size(width, height), flags,
borderMode, borderColor);
~self->mat;
self->mat = res;
info.GetReturnValue().Set(Nan::Null());
}
NAN_METHOD(Matrix::CopyWithMask) {
SETUP_FUNCTION(Matrix)
// param 0 - destination image:
Matrix *dest = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
// param 1 - mask. same size as src and dest
Matrix *mask = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
self->mat.copyTo(dest->mat, mask->mat);
return;
}
NAN_METHOD(Matrix::SetWithMask) {
SETUP_FUNCTION(Matrix)
// param 0 - target value:
Local < Object > valArray = info[0]->ToObject();
cv::Scalar newvals;
newvals.val[0] = valArray->Get(0)->NumberValue();
newvals.val[1] = valArray->Get(1)->NumberValue();
newvals.val[2] = valArray->Get(2)->NumberValue();
// param 1 - mask. same size as src and dest
Matrix *mask = Nan::ObjectWrap::Unwrap<Matrix>(info[1]->ToObject());
self->mat.setTo(newvals, mask->mat);
return;
}
NAN_METHOD(Matrix::MeanWithMask) {
SETUP_FUNCTION(Matrix)
// param 0 - mask. same size as src and dest
Matrix *mask = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
cv::Scalar means = cv::mean(self->mat, mask->mat);
v8::Local < v8::Array > arr = Nan::New<Array>(4);
arr->Set(0, Nan::New<Number>(means[0]));
arr->Set(1, Nan::New<Number>(means[1]));
arr->Set(2, Nan::New<Number>(means[2]));
arr->Set(3, Nan::New<Number>(means[3]));
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::Mean) {
SETUP_FUNCTION(Matrix)
cv::Scalar means = cv::mean(self->mat);
v8::Local<v8::Array> arr = Nan::New<Array>(4);
arr->Set(0, Nan::New<Number>(means[0]));
arr->Set(1, Nan::New<Number>(means[1]));
arr->Set(2, Nan::New<Number>(means[2]));
arr->Set(3, Nan::New<Number>(means[3]));
info.GetReturnValue().Set(arr);
}
NAN_METHOD(Matrix::Shift) {
SETUP_FUNCTION(Matrix)
cv::Mat res;
double tx = info[0]->NumberValue();
double ty = info[1]->NumberValue();
// get the integer values of info
cv::Point2i deltai(ceil(tx), ceil(ty));
int fill = cv::BORDER_REPLICATE;
cv::Scalar value = cv::Scalar(0, 0, 0, 0);
// INTEGER SHIFT
// first create a border around the parts of the Mat that will be exposed
int t = 0, b = 0, l = 0, r = 0;
if (deltai.x > 0) {
l = deltai.x;
}
if (deltai.x < 0) {
r = -deltai.x;
}
if (deltai.y > 0) {
t = deltai.y;
}
if (deltai.y < 0) {
b = -deltai.y;
}
cv::Mat padded;
cv::copyMakeBorder(self->mat, padded, t, b, l, r, fill, value);
// construct the region of interest around the new matrix
cv::Rect roi = cv::Rect(std::max(-deltai.x, 0), std::max(-deltai.y, 0), 0, 0)
+ self->mat.size();
res = padded(roi);
~self->mat;
self->mat = res;
return;
}
/**
* Changes the shape and/or the number of channels of a 2D matrix without
* copying the data.
* Reference:http://docs.opencv.org/2.4/modules/core/doc/basic_structures.html#mat-reshape
*/
NAN_METHOD(Matrix::Reshape) {
SETUP_FUNCTION(Matrix)
int cn = 0;
int rows = 0;
if (info.Length() == 2) {
INT_FROM_ARGS(cn, 0);
INT_FROM_ARGS(rows, 1);
} else if (info.Length() == 1) {
INT_FROM_ARGS(cn, 0);
} else {
JSTHROW("Invalid number of arguments");
}
Local<Object> img_to_return =
Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *img = Nan::ObjectWrap::Unwrap<Matrix>(img_to_return);
img->mat = self->mat.reshape(cn, rows);
info.GetReturnValue().Set(img_to_return);
}
NAN_METHOD(Matrix::Release) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
self->mat.release();
return;
}
// leave this out - can't see a way it could be useful to us, as release() always completely forgets the data
//NAN_METHOD(Matrix::Addref) {
// Nan::HandleScope scope;
//
// Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
// self->mat.addref();
//
// return;
//}
NAN_METHOD(Matrix::GetrefCount) {
Nan::HandleScope scope;
Matrix *self = Nan::ObjectWrap::Unwrap<Matrix>(info.This());
int refcount = -1;
#if CV_MAJOR_VERSION >= 3
if (self->mat.u){
refcount = self->mat.u->refcount;
} else {
refcount = -1; // indicates no reference ptr
}
#else
if (self->mat.refcount){
refcount = *(self->mat.refcount);
} else {
refcount = -1; // indicates no reference ptr
}
#endif
info.GetReturnValue().Set(Nan::New<Number>(refcount));
return;
}
NAN_METHOD(Matrix::Subtract) {
SETUP_FUNCTION(Matrix)
if (info.Length() < 1) {
Nan::ThrowTypeError("Invalid number of arguments");
}
Matrix *other = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
self->mat -= other->mat;
return;
}
NAN_METHOD(Matrix::Compare) {
SETUP_FUNCTION(Matrix)
if (info.Length() < 2) {
Nan::ThrowTypeError("Invalid number of arguments");
}
Matrix *other = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
int cmpop = info[1]->IntegerValue();
int width = self->mat.size().width;
int height = self->mat.size().height;
cv::Mat res = cv::Mat(width, height, CV_8UC1);
cv::compare(self->mat, other->mat, res, cmpop);
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
m_out->mat = res;
info.GetReturnValue().Set(out);
return;
}
NAN_METHOD(Matrix::Mul) {
SETUP_FUNCTION(Matrix)
if (info.Length() < 1) {
Nan::ThrowTypeError("Invalid number of arguments");
}
Matrix *other = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
double scale = 1;
if (info.Length() > 1) scale = info[1]->NumberValue();
cv::Mat res = self->mat.mul(other->mat, scale);
Local<Object> out = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
Matrix *m_out = Nan::ObjectWrap::Unwrap<Matrix>(out);
m_out->mat = res;
info.GetReturnValue().Set(out);
return;
}
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