97 lines
4.3 KiB
C++
97 lines
4.3 KiB
C++
#include <opencv2/core/core.hpp>
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#include <opencv2/freetype.hpp>
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#include <string>
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#include <vector>
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#include "../models/vehicle_feature_encoder.h"
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using namespace std;
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/*
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* vehicle comparision demo, 1:1
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*/
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// compare two features
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// dis_type 0 means cosine distance, bigger means more similiar
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// dis_type 1 means L2 distance, smaller means more similiar
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double match(std::vector<float>& feature1, std::vector<float>& feature2, int dis_type) {
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auto _face_feature1 = cv::Mat(1, feature1.size(), CV_32F, feature1.data());
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auto _face_feature2 = cv::Mat(1, feature2.size(), CV_32F, feature2.data());
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cv::normalize(_face_feature1, _face_feature1);
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cv::normalize(_face_feature2, _face_feature2);
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if(dis_type == 0) {
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return cv::sum(_face_feature1.mul(_face_feature2))[0];
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}
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else if(dis_type == 1) {
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return cv::norm(_face_feature1, _face_feature2);
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}
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else {
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return 0;
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}
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}
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int main() {
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std::string featureModelPath = "./vp_data/models/trt/vehicle/vehicle_embedding_v8.5.trt";
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auto image = cv::imread("./vp_data/test_images/vehicle_feature/2_001.jpg"); // first vehicle
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auto image2 = cv::imread("./vp_data/test_images/vehicle_feature/2_003.jpg"); // second vehicle to compare(the same vehicle with different angle)
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auto image3 = cv::imread("./vp_data/test_images/vehicle_feature/5_002.jpg"); // third vehicle to compare(not the same vehicle)
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auto vehicleEncoder = new trt_vehicle::VehicleFeatureEncoder(featureModelPath);
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auto ft2 = cv::freetype::createFreeType2();
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ft2->loadFontData("./vp_data/font/NotoSansCJKsc-Medium.otf", 0);
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std::vector<std::vector<float>> results;
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std::vector<cv::Mat> img_datas = {image, image2, image3};
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vehicleEncoder->encode(img_datas, results); // encode
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auto feature1 = results[0];
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auto feature2 = results[1];
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auto feature3 = results[2];
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// print features, 256 dims
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auto print_features = [](std::vector<float> features, std::string name) {
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std::cout << name << ": " << features.size() << " dims " << "[" << std::endl;
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for (auto& i: features) {
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std::cout << i << ",";
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}
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std::cout << "]" << std::endl;
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};
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print_features(feature1, "feature1");
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print_features(feature2, "feature2");
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print_features(feature3, "feature3");
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auto dis_type = 0;
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auto dis_1_2 = match(feature1, feature2, dis_type); // compare feature1 and feature2
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auto dis_1_3 = match(feature1, feature3, dis_type); // compare feature1 and feature3
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std::cout << "distance between feature1 and feature2: " << dis_1_2 << std::endl;
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std::cout << "distance between feature1 and feature3: " << dis_1_3 << std::endl;
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// convert to similarity
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auto similiarity_1_2 = dis_type == 0 ? dis_1_2 : (1 - dis_1_2);
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similiarity_1_2 = std::max(similiarity_1_2, 0.0);
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auto similiarity_1_3 = dis_type == 0 ? dis_1_3 : (1 - dis_1_3);
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similiarity_1_3 = std::max(similiarity_1_3, 0.0);
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// display
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auto h = image.rows + std::max(image2.rows, image3.rows) + 50 + 10 + 10;
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auto w = std::max(image2.cols, image3.cols) * 2 + 50 + 10 + 10;
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cv::Mat canvas(h, w, CV_8UC3,cv::Scalar(127, 127, 127));
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cv::Mat roi_(canvas,cv::Rect(canvas.cols / 2 - image.cols / 2, 10, image.cols, image.rows));
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cv::Mat roi_2(canvas, cv::Rect(canvas.cols / 2 - image2.cols - 25, 10 + image.rows + 25, image2.cols, image2.rows));
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cv::Mat roi_3(canvas, cv::Rect(canvas.cols / 2 + 25, 10 + image.rows + 25, image3.cols, image3.rows));
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image.copyTo(roi_);
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image2.copyTo(roi_2);
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image3.copyTo(roi_3);
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cv::line(canvas, cv::Point(canvas.cols / 2, 10 + image.rows), cv::Point(10 + image2.cols / 2, 10 + image.rows + 50), cv::Scalar(255, 0, 0));
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cv::line(canvas, cv::Point(canvas.cols / 2, 10 + image.rows), cv::Point(canvas.cols / 2 + 25 + image3.cols / 2, 10 + image.rows + 50), cv::Scalar(255, 0, 0));
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ft2->putText(canvas, "相似度：" + std::to_string(similiarity_1_2), cv::Point(10, 10 + image.rows + 25), 20, cv::Scalar(255, 0, 0), cv::FILLED, cv::LINE_AA, true);
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ft2->putText(canvas, "相似度：" + std::to_string(similiarity_1_3), cv::Point(10 + image2.cols + 50, 10 + image.rows + 25), 20, cv::Scalar(255, 0, 0), cv::FILLED, cv::LINE_AA, true);
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cv::imshow("compare result", canvas);
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cv::waitKey(0);
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delete vehicleEncoder;
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return 0;
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} |