Francesco Gatti
69 lines
2.0 KiB
C++
69 lines
2.0 KiB
C++
#include <opencv2/core/core.hpp>
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#include <opencv2/highgui/highgui.hpp>
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#include <opencv2/videoio.hpp>
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#include <opencv2/imgproc/imgproc.hpp>
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#include "tkDNN/NetworkViz.h"
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namespace tk { namespace dnn {
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cv::Mat vizFloat2colorMap(cv::Mat map) {
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double min;
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double max;
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cv::minMaxIdx(map, &min, &max);
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cv::Mat adjMap;
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// expand your range to 0..255. Similar to histEq();
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map.convertTo(adjMap,CV_8UC1, 255 / (max-min), -min);
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//return adjMap;
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cv::Mat falseColorsMap;
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applyColorMap(adjMap, falseColorsMap, cv::COLORMAP_HOT);
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return falseColorsMap;
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}
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cv::Mat vizData2Mat(dnnType *dataInput, tk::dnn::dataDim_t dim, int imgdim) {
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dnnType *data = nullptr;
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// copy to CPU
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if(isCudaPointer(dataInput)) {
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data = new dnnType[dim.tot()];
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checkCuda( cudaMemcpy(data, dataInput, dim.tot()*sizeof(dnnType), cudaMemcpyDeviceToHost) );
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} else {
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data = dataInput;
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}
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int gridDim = ceil(sqrt(dim.c));
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cv::Size gridSize(dim.w*gridDim, dim.h*gridDim);
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cv::Mat grid = cv::Mat(gridSize, CV_8UC3, cv::Scalar(0));
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for(int i=0; i<dim.c;i++) {
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cv::Mat raw = vizFloat2colorMap(cv::Mat(cv::Size(dim.w, dim.h),CV_32FC1, data + dim.w*dim.h*i));
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int r = i / gridDim;
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int c = i - r * gridDim;
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raw.copyTo(grid.rowRange(r*dim.h, r*dim.h + dim.h).colRange(c*dim.w, c*dim.w + dim.w));
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}
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float ar = float(dim.w)/dim.h;
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cv::Size vdim(ar*imgdim, imgdim);
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cv::Mat viz;
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cv::resize(grid, viz, vdim, 0, 0, 0);
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// free memory
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if(isCudaPointer(dataInput)) {
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delete [] data;
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}
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return viz;
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}
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cv::Mat vizLayer2Mat(tk::dnn::Network *net, int layer, int imgdim) {
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if(layer >= net->num_layers)
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FatalError("Could not viz layer\n");
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return vizData2Mat(net->layers[layer]->dstData, net->layers[layer]->output_dim, imgdim);
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//cv::imwrite("viz/layer" + std::to_string(layer) + ".png", viz);
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//cv::imshow("layer", viz);
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//cv::waitKey(0);
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}
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}} |