46 lines
1.6 KiB
C++
46 lines
1.6 KiB
C++
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//
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// Created by DefTruth on 2021/4/3.
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//
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#include "gender_googlenet.h"
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#include "lite/ort/core/ort_utils.h"
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#include "lite/utils.h"
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using ortcv::GenderGoogleNet;
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Ort::Value GenderGoogleNet::transform(const cv::Mat &mat)
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{
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cv::Mat canvas;
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cv::cvtColor(mat, canvas, cv::COLOR_BGR2RGB);
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cv::resize(canvas, canvas, cv::Size(input_node_dims.at(3),
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input_node_dims.at(2)));
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// (1,3,224,224)
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ortcv::utils::transform::normalize_inplace(canvas, mean_val, scale_val); // float32
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return ortcv::utils::transform::create_tensor(
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canvas, input_node_dims, memory_info_handler,
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input_values_handler, ortcv::utils::transform::CHW);
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}
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void GenderGoogleNet::detect(const cv::Mat &mat, types::Gender &gender)
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{
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if (mat.empty()) return;
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// 1. make input tensor
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Ort::Value input_tensor = this->transform(mat);
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// 2. inference.
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auto output_tensors = ort_session->Run(
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Ort::RunOptions{nullptr}, input_node_names.data(),
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&input_tensor, 1, output_node_names.data(), num_outputs
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);
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Ort::Value &gender_logits = output_tensors.at(0); // (1,2)
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auto gender_dims = output_node_dims.at(0);
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const unsigned int num_genders = gender_dims.at(1); // 2
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unsigned int pred_gender = 0;
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const float *pred_logits = gender_logits.GetTensorMutableData<float>();
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auto softmax_probs = lite::utils::math::softmax<float>(pred_logits, num_genders, pred_gender);
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unsigned int gender_label = pred_gender == 1 ? 0 : 1;
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gender.label = gender_label;
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gender.text = gender_texts[gender_label];
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gender.score = softmax_probs[pred_gender];
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gender.flag = true;
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}
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