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pc端ncnn搭建与测试

目录

一、本文系统配置

二、编译

参考：

三、测试

1、配置ncnn、protobuf、opencv

2、模型文件拷贝

3、代码测试

在PC使用NCNN框架推理加速模型，需要先获取ncnn编译后的动静态库。

一、本文系统配置

windows10

VS2019

CMake 3.18.4

二、编译

编译前需要先下载protobuf和ncnn源码。

参考：

Windows下ncnn环境配置（VS2019）_逮仔的博客-CSDN博客_ncnn vs2019

（一）ncnn | Windows（VS2019）编译_Silence_Zzz的博客-CSDN博客_vs2019编译ncnn

ncnn和opencv在vs2022上创建工程推理示例_三叔家的猫的博客-CSDN博客_ncnn

如果不想编译也可以使用官方编译好的文件：Releases · Tencent/ncnn · GitHub

三、测试

1、配置ncnn、protobuf、opencv

新建VS空项目工程。

以上编译是release版本，VS配置器选择Realease x64平台

VC++目录-包含目录：

VC++目录-库目录

链接器-输入-附加依赖项：

2、模型文件拷贝

将ncnn下的example文件加下的模型及标签文件拷贝到VS创建的工程下，找一张分类图片做测试

3、代码测试

// Tencent is pleased to support the open source community by making ncnn available.
//
// Copyright (C) 2017 THL A29 Limited, a Tencent company. All rights reserved.
//
// Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
// in compliance with the License. You may obtain a copy of the License at
//
// 
//
// Unless required by applicable law or agreed to in writing, software distributed
// under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
// CONDITIONS OF ANY KIND, either express or implied. See the License for the
// specific language governing permissions and limitations under the License.#include "net.h"#include <algorithm>
#if defined(USE_NCNN_SIMPLEOCV)
#include "simpleocv.h"
#else
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include<opencv2/opencv.hpp>
#endif
#include <stdio.h>
#include <vector>static int detect_squeezenet(const cv::Mat& bgr, std::vector<float>& cls_scores)
{ncnn::Net squeezenet;squeezenet.opt.use_vulkan_compute = true;// the ncnn model .load_param("squeezenet_v1.1.param");squeezenet.load_model("squeezenet_v1.1.bin");ncnn::Mat in = ncnn::Mat::from_pixels_resize(bgr.data, ncnn::Mat::PIXEL_BGR, bgr.cols, bgr.rows, 227, 227);const float mean_vals[3] = {104.f, 117.f, 123.f};in.substract_mean_normalize(mean_vals, 0);ncnn::Extractor ex = squeezenet.create_extractor();ex.input("data", in);ncnn::Mat out;ex.extract("prob", out);cls_scores.resize(out.w);for (int j = 0; j < out.w; j++){cls_scores[j] = out[j];}return 0;
}static int print_topk(const std::vector<float>& cls_scores, int topk, std::vector<int>& indexs, std::vector<float>& scores)
{// partial sort topk with indexint size = cls_scores.size();std::vector<std::pair<float, int> > vec;vec.resize(size);for (int i = 0; i < size; i++){vec[i] = std::make_pair(cls_scores[i], i);}std::partial_sort(vec.begin(), vec.begin() + topk, vec.end(),std::greater<std::pair<float, int> >());// print topk and scorefor (int i = 0; i < topk; i++){float score = vec[i].first;int index = vec[i].second;fprintf(stderr, "%d = %f\n", index, score);indexs.push_back(index);scores.push_back(score);}return 0;
}static int load_labels(std::string path, std::vector<std::string>& labels)
{FILE* fp = fopen(path.c_str(), "r");while (!feof(fp)){char str[1024];fgets(str, 1024, fp);std::string str_s(str);if (str_s.length() > 0){for (int i = 0; i < str_s.length(); i++){if (str_s[i] == ' '){std::string strr = str_s.substr(i, str_s.length() - i - 1);labels.push_back(strr);i = str_s.length();}}}}
}int main(int argc, char** argv)
{/*if (argc != 2){fprintf(stderr, "Usage: %s [imagepath]\n", argv[0]);return -1;}*/clock_t start = clock();std::vector<std::string>labels;load_labels("synset_words.txt", labels);const char* imagepath = "rabbit.jpg";cv::Mat m = cv::imread(imagepath, 1);if (m.empty()){fprintf(stderr, "cv::imread %s failed\n", imagepath);return -1;}std::vector<int>index;std::vector<float>score;std::vector<float> cls_scores;detect_squeezenet(m, cls_scores);print_topk(cls_scores, 3,index,score);for (int i = 0; i < index.size(); i++){cv::putText(m, labels[index[i]], cv::Point(10, 10 + i * 30), 0, 0.5, cv::Scalar(255, 100, 100), 2, 2);}clock_t end = clock();std::cout << "运行时间：" << (double)(end - start) / CLOCKS_PER_SEC << std::endl;cv::imshow("m", m);//imwrite("dog_result.jpg", m);cv::waitKey(0);return 0;
}

运行结果：