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https://github.com/peterbraden/node-opencv.git
synced 2025-12-08 19:45:55 +00:00
Histogram now takes multiple dimensions
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Pierre Colle
parent
2839bce325
commit
1bb61fc38a
@ -9,19 +9,59 @@ cv.readImage('./files/car1.jpg', function(err, im) {
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var bgrPlanes = im.split();
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var size = 4,
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var size = 256,
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range = [0, 256],
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uniform = true,
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accumulate = true,
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histFile = 'files/chart.png';
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histFile = 'files/chart2.png';
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/// Compute the histograms:
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var bHist = cv.histogram.calcHist( bgrPlanes[0], size, range, uniform, accumulate );
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var gHist = cv.histogram.calcHist( bgrPlanes[1], size, range, uniform, accumulate );
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var rHist = cv.histogram.calcHist( bgrPlanes[2], size, range, uniform, accumulate );
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console.log("Histograms are \n Blue : ", bHist, "\n Green : ", gHist, "\n Red : ", rHist);
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var hist64 = cv.histogram.calcHist( im, [0, 1, 2], [4, 4, 4], [[0, 256], [0, 256], [0, 256]], uniform, accumulate );
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var bHist = cv.histogram.calcHist( im, [0], [size], [range], uniform, accumulate );
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var gHist = cv.histogram.calcHist( im, [1], [size], [range], uniform, accumulate );
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var rHist = cv.histogram.calcHist( im, [2], [size], [range], uniform, accumulate );
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//////
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// Uncommentand run `npm install chartjs-node` to draw the histogram !
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///
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/*
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var ChartjsNode = require('chartjs-node');
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var chartNode = new ChartjsNode(1200, 1200);
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chartNode.drawChart({
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type: 'bar',
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data: {
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labels: bHist.map(function(a,i){return i.toString()}),
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datasets : [{
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data : bHist,
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backgroundColor : "#4183c4",
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borderColor : "#0c4b8a",
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label : 'Blue'
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},{
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data : gHist,
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backgroundColor : "#83c441",
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borderColor : "#0c4b8a",
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label : 'Green'
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},{
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data : rHist,
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backgroundColor : "#c44183",
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borderColor : "#0c4b8a",
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label : 'Red'
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}]
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},
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options: {
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title: {
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display: true,
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text: 'RGB Histograms'
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}
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}
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}).then(function(){
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return chartNode.writeImageToFile('image/png', histFile);
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}).then(function(){
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console.log("result has been written in "+histFile)
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}).catch(function(e){
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console.log("error",e)
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});
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*/
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});
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107
src/Histogram.cc
107
src/Histogram.cc
@ -20,43 +20,102 @@ NAN_METHOD(Histogram::CalcHist) {
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Matrix* m0 = Nan::ObjectWrap::Unwrap<Matrix>(info[0]->ToObject());
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cv::Mat inputImage = m0->mat;
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// Arg 1 is histogram sizes in first dimension
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/// Establish the number of bins
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int histSize = info[1]->IntegerValue();
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// Arg 2 is array of the histogram bin boundaries in each dimension
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Local<Array> nodeRange = Local<Array>::Cast(info[2]->ToObject());
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unsigned int num_range = nodeRange->Length();
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/// Set the ranges ( for B,G,R) )
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float range[num_range];
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for (unsigned int i = 0; i < num_range; i++) {
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range[i] = nodeRange->Get(i)->NumberValue();
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//int dims = 3;
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// Arg 1 is the channel
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Local<Array> nodeChannels = Local<Array>::Cast(info[1]->ToObject());
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const unsigned int dims = nodeChannels->Length();
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int channels[dims];
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for (unsigned int i = 0; i < dims; i++) {
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channels[i] = nodeChannels->Get(i)->IntegerValue();
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}
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const float* histRange = { range };
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// Arg 3 is uniform flag
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bool uniform = info[3]->BooleanValue();
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//int channels[] = {0, 1, 2};
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// Arg 4 is accumulate flag
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bool accumulate = info[4]->BooleanValue();
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// Arg 2 is histogram sizes in each dimension
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Local<Array> nodeHistSizes = Local<Array>::Cast(info[2]->ToObject());
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int histSize[dims];
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for (unsigned int i = 0; i < dims; i++) {
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histSize[i] = nodeHistSizes->Get(i)->IntegerValue();
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}
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// Arg 3 is array of the histogram bin boundaries in each dimension
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Local<Array> nodeRanges = Local<Array>::Cast(info[3]->ToObject());
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/// Set the ranges ( for B,G,R) )
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float histRanges[dims][2];
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for (unsigned int i = 0; i < dims; i++) {
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Local<Array> nodeRange = Local<Array>::Cast(nodeRanges->Get(i)->ToObject());
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float lower = nodeRange->Get(0)->NumberValue();
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float higher = nodeRange->Get(1)->NumberValue();
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histRanges[i][0] = lower;
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histRanges[i][1] = higher;
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}
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float first_range[] = { histRanges[0][0], histRanges[0][1] };
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float second_range[] = { 0, 0};
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float third_range[] = { 0, 0};
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if(dims >= 2){
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second_range[0] = histRanges[1][0];
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second_range[1] = histRanges[1][1];
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}
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if(dims >= 3){
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third_range[0] = histRanges[2][0];
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third_range[1] = histRanges[2][1];
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}
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const float* histRanges1[] = {first_range, second_range, third_range};
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// Arg 4 is uniform flag
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bool uniform = info[4]->BooleanValue();
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// Arg 5 is accumulate flag
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bool accumulate = info[5]->BooleanValue();
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/*
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float rranges[] = { 0, 256 };
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float granges[] = { 0, 256 };
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float branges[] = { 0, 256 };
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const float* histRange[] = { rranges, granges, branges};
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*/
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// Make a mat to hold the result image
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cv::Mat outputHist;
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// Perform calcHist
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cv::calcHist(&inputImage, 1, 0, cv::Mat(), outputHist, 1, &histSize, &histRange, uniform, accumulate);
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cv::calcHist(&inputImage, 1, channels, cv::Mat(), outputHist, dims, histSize, histRanges1, uniform, accumulate);
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// Wrap the output image
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//Local<Object> outMatrixWrap = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
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//Matrix *outMatrix = Nan::ObjectWrap::Unwrap<Matrix>(outMatrixWrap);
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//outMatrix->mat = outputHist;
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/*Local<Object> outMatrixWrap = Nan::NewInstance(Nan::GetFunction(Nan::New(Matrix::constructor)).ToLocalChecked()).ToLocalChecked();
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Matrix *outMatrix = Nan::ObjectWrap::Unwrap<Matrix>(outMatrixWrap);
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outMatrix->mat = outputHist;
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v8::Local<v8::Array> arr = Nan::New<Array>(histSize);
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info.GetReturnValue().Set(outMatrixWrap);*/
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for (unsigned int i=0; i < (unsigned int) histSize; i++) {
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v8::Local<v8::Array> arr = Nan::New<Array>(histSize[0]);
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if(dims < 1 || dims > 3){
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return Nan::ThrowTypeError("OPENCV nodejs binding error : only dimensions from 1 to 3 are allowed");
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}
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for (unsigned int i=0; i < (unsigned int) histSize[0]; i++) {
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if(dims <= 1){
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arr->Set(i, Nan::New<Number>(outputHist.at<float>(i)));
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} else {
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v8::Local<v8::Array> arr2 = Nan::New<Array>(dims);
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for (unsigned int j=0; j < (unsigned int) histSize[1]; j++) {
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if(dims <= 2){
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arr2->Set(j, Nan::New<Number>(outputHist.at<float>(i,j)));
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} else {
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v8::Local<v8::Array> arr3 = Nan::New<Array>(dims);
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for (unsigned int k=0; k < (unsigned int) histSize[1]; k++) {
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arr3->Set(k, Nan::New<Number>(outputHist.at<float>(i,j,k)));
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}
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arr2->Set(j, arr3);
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}
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}
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arr->Set(i, arr2);
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}
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}
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info.GetReturnValue().Set(arr);
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