forked from floratest1/SpireCV
113 lines
2.6 KiB
C++
113 lines
2.6 KiB
C++
#include "veri_det_intel_impl.h"
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#include <cmath>
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#include <fstream>
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#define SV_MODEL_DIR "/SpireCV/models/"
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#define SV_ROOT_DIR "/SpireCV/"
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#include <iostream>
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#include <cmath>
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int BAT = 1;
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float cosineSimilarity(float *vec1, float *vec2, int size)
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{
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// 计算向量的点积
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float dotProduct = 0.0f;
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for (int i = 0; i < size; ++i)
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{
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dotProduct += vec1[i] * vec2[i];
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}
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// 计算向量的模长
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float magnitudeVec1 = 0.0f;
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float magnitudeVec2 = 0.0f;
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for (int i = 0; i < size; ++i)
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{
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magnitudeVec1 += vec1[i] * vec1[i];
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magnitudeVec2 += vec2[i] * vec2[i];
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}
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magnitudeVec1 = std::sqrt(magnitudeVec1);
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magnitudeVec2 = std::sqrt(magnitudeVec2);
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// 计算余弦相似性
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float similarity = dotProduct / (magnitudeVec1 * magnitudeVec2);
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return similarity;
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}
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namespace sv
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{
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#ifdef WITH_INTEL
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using namespace cv;
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using namespace std;
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using namespace dnn;
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#endif
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VeriDetectorIntelImpl::VeriDetectorIntelImpl()
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{
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}
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VeriDetectorIntelImpl::~VeriDetectorIntelImpl()
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{
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}
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bool VeriDetectorIntelImpl::intelSetup()
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{
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#ifdef WITH_INTEL
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std::string onnx_model_fn = get_home() + SV_MODEL_DIR + "veri.onnx";
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if (!is_file_exist(onnx_model_fn))
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{
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throw std::runtime_error("SpireCV (104) Error loading the VeriDetector openVINO model (File Not Exist)");
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}
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// OpenVINO
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ov::Core core;
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this->compiled_model = core.compile_model(onnx_model_fn, "GPU");
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this->infer_request = compiled_model.create_infer_request();
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return true;
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#endif
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return false;
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}
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void VeriDetectorIntelImpl::intelRoiCNN(
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std::vector<cv::Mat> &input_rois_,
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std::vector<float> &output_labels_)
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{
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#ifdef WITH_INTEL
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Mat blobs;
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blobFromImages(input_rois_, blobs, 1 / 255.0, Size(224, 224), Scalar(0, 0, 0), true, true);
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auto input_port = compiled_model.input();
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ov::Tensor input_tensor(input_port.get_element_type(), input_port.get_shape(), blobs.ptr(0));
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infer_request.infer();
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const ov::Tensor &label_pre = infer_request.get_output_tensor(0);
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this->_p_prob1 = label_pre.data<float>();
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const ov::Tensor &proto_pre = infer_request.get_output_tensor(1);
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this->_p_prob2 = proto_pre.data<float>();
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// Find max index
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double max = 0;
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int label = 0;
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for (int i = 0; i < 576; ++i)
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{
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if (max < this->_p_prob1[i])
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{
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max = this->_p_prob1[i];
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label = i;
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}
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}
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float similarity = cosineSimilarity(this->_p_prob2, this->_p_prob2 + 1280, 1280);
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output_labels_.push_back(label);
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output_labels_.push_back(similarity);
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#endif
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}
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}
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