Francesco Gatti
54 lines
1.6 KiB
C++
54 lines
1.6 KiB
C++
#include<iostream>
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#include<vector>
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#include <opencv2/highgui/highgui.hpp>
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#include "tkdnn.h"
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#include "test.h"
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#include "DarknetParser.h"
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#include "NetworkViz.h"
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int main() {
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std::string bin_path = "yolo3";
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std::vector<std::string> input_bins = {
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bin_path + "/layers/input.bin"
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};
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std::string wgs_path = bin_path + "/layers";
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std::string cfg_path = std::string(TKDNN_PATH) + "/tests/darknet/cfg/yolo3.cfg";
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std::string name_path = std::string(TKDNN_PATH) + "/tests/darknet/names/coco.names";
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downloadWeightsifDoNotExist(input_bins[0], bin_path, "https://cloud.hipert.unimore.it/s/jPXmHyptpLoNdNR/download");
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// parse darknet network
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tk::dnn::Network *net = tk::dnn::darknetParser(cfg_path, wgs_path, name_path);
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net->print();
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// Load input and infer
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dnnType *input_d;
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dnnType *input_h;
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readBinaryFile(input_bins[0], net->input_dim.tot(), &input_h, &input_d);
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tk::dnn::dataDim_t dim = net->input_dim;
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dim.print();
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std::cout<<"infer\n";
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net->infer(dim, input_d);
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// output directory
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std::string output_viz = "viz/";
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system( (std::string("mkdir -p ") + output_viz).c_str() );
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for(int i=0; i<net->num_layers; i++) {
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std::string output_png = output_viz + "/layer" + std::to_string(i) + ".png";
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std::cout<<"saving "<<output_png<<"\n";
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cv::Mat viz = vizLayer2Mat(net, i);
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cv::imwrite(output_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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delete [] input_h;
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checkCuda(cudaFree(input_d));
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net->releaseLayers();
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delete net;
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return 0;
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}
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