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#include "CascadeClassifierWrap.h"
#include "OpenCV.h"
#include "Matrix.h"
#include <nan.h>
#ifdef HAVE_OPENCV_OBJDETECT
Nan::Persistent<FunctionTemplate> CascadeClassifierWrap::constructor;
void CascadeClassifierWrap::Init(Local<Object> target) {
Nan::HandleScope scope;
Local<FunctionTemplate> ctor = Nan::New<FunctionTemplate> (CascadeClassifierWrap::New);
constructor.Reset(ctor);
ctor->InstanceTemplate()->SetInternalFieldCount(1);
ctor->SetClassName(Nan::New("CascadeClassifier").ToLocalChecked());
// Prototype
// Local<ObjectTemplate> proto = constructor->PrototypeTemplate();
Nan::SetPrototypeMethod(ctor, "detectMultiScale", DetectMultiScale);
target->Set(Nan::New("CascadeClassifier").ToLocalChecked(), ctor->GetFunction());
}
NAN_METHOD(CascadeClassifierWrap::New) {
Nan::HandleScope scope;
if (info.This()->InternalFieldCount() == 0) {
Nan::ThrowTypeError("Cannot instantiate without new");
}
CascadeClassifierWrap *pt = new CascadeClassifierWrap(*info[0]);
pt->Wrap(info.This());
info.GetReturnValue().Set( info.This() );
}
CascadeClassifierWrap::CascadeClassifierWrap(v8::Value* fileName) {
std::string filename;
filename = std::string(*Nan::Utf8String(fileName->ToString()));
if (!cc.load(filename.c_str())) {
Nan::ThrowTypeError("Error loading file");
}
}
class AsyncDetectMultiScale: public Nan::AsyncWorker {
public:
AsyncDetectMultiScale(Nan::Callback *callback, CascadeClassifierWrap *cc,
Matrix* im, double scale, int neighbors, int minw, int minh) :
Nan::AsyncWorker(callback),
cc(cc),
im(new Matrix(im)), //copy the matrix so we aren't affected if the original is released
scale(scale),
neighbors(neighbors),
minw(minw),
minh(minh) {
}
~AsyncDetectMultiScale() {
}
void Execute() {
try {
std::vector < cv::Rect > objects;
cv::Mat gray;
if (this->im->mat.channels() != 1) {
cvtColor(this->im->mat, gray, CV_BGR2GRAY);
equalizeHist(gray, gray);
} else {
gray = this->im->mat;
}
this->cc->cc.detectMultiScale(gray, objects, this->scale, this->neighbors,
0 | CV_HAAR_SCALE_IMAGE, cv::Size(this->minw, this->minh));
res = objects;
} catch (cv::Exception& e) {
SetErrorMessage(e.what());
}
}
void HandleOKCallback() {
Nan::HandleScope scope;
delete im;
im = NULL;
Local < Value > argv[2];
v8::Local < v8::Array > arr = Nan::New < v8::Array > (this->res.size());
for (unsigned int i = 0; i < this->res.size(); i++) {
v8::Local < v8::Object > x = Nan::New<v8::Object>();
x->Set(Nan::New("x").ToLocalChecked(), Nan::New < Number > (this->res[i].x));
x->Set(Nan::New("y").ToLocalChecked(), Nan::New < Number > (this->res[i].y));
x->Set(Nan::New("width").ToLocalChecked(), Nan::New < Number > (this->res[i].width));
x->Set(Nan::New("height").ToLocalChecked(), Nan::New < Number > (this->res[i].height));
arr->Set(i, x);
}
argv[0] = Nan::Null();
argv[1] = arr;
Nan::TryCatch try_catch;
callback->Call(2, argv);
if (try_catch.HasCaught()) {
Nan::FatalException(try_catch);
}
}
private:
CascadeClassifierWrap *cc;
Matrix* im;
double scale;
int neighbors;
int minw;
int minh;
std::vector<cv::Rect> res;
};
NAN_METHOD(CascadeClassifierWrap::DetectMultiScale) {
Nan::HandleScope scope;
CascadeClassifierWrap *self = Nan::ObjectWrap::Unwrap<CascadeClassifierWrap> (info.This());
if (info.Length() < 2) {
Nan::ThrowTypeError("detectMultiScale takes at least 2 info");
}
Matrix *im = Nan::ObjectWrap::Unwrap < Matrix > (info[0]->ToObject());
REQ_FUN_ARG(1, cb);
double scale = 1.1;
if (info.Length() > 2 && info[2]->IsNumber()) {
scale = info[2]->NumberValue();
}
int neighbors = 2;
if (info.Length() > 3 && info[3]->IsInt32()) {
neighbors = info[3]->IntegerValue();
}
int minw = 30;
int minh = 30;
if (info.Length() > 5 && info[4]->IsInt32() && info[5]->IsInt32()) {
minw = info[4]->IntegerValue();
minh = info[5]->IntegerValue();
}
Nan::Callback *callback = new Nan::Callback(cb.As<Function>());
Nan::AsyncQueueWorker( new AsyncDetectMultiScale(callback, self, im, scale,
neighbors, minw, minh));
return;
}
#endif
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