人脸检测+人体检测C++ Android项目

太过爱你忘了你带给我的痛 2022-09-15 06:08 233阅读 0赞

# 人脸检测+人体检测C++ Android项目 #

本博客将实现C++版本的人脸检测，人脸关键点检测，人体检测，人脸+人体检测，推理框架采用TNN，在普通Android手机，CPU和GPU都可以达到实时检测的效果

> 人脸检测+人脸关键点检测+人体检测Android Demo APP(是APP Demo，完整项目可微信联系，仅供学习交)：
> 
> 链接: https://pan.baidu.com/s/1By43I1DbMa0gBPLObtPZMQ 提取码: msnr

尊重原创，转载请注明出处：[https://panjinquan.blog.csdn.net/article/details/120688804][https_panjinquan.blog.csdn.net_article_details_120688804]

--------------------

**目录**

人脸检测+人体检测C++ Android实现

1.项目说明

（1）训练

（2）端上部署

（3）依赖库

2. 人脸人体检测Demo

3. Android Demo效果

4.人体关键点Demo（Android版本）

--------------------

## 1.项目说明 ##

### （1）训练 ###

训练代码请参考：[https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB ][https_github.com_Linzaer_Ultra-Light-Fast-Generic-Face-Detector-1MB]，一个基于SSD简化的人脸检测模型，很轻量化，整个模型仅仅1.7M左右，在普通Android手机都可以实时检测。

原始代码使用WiderFace人脸数据集进行训练，仅支持了人脸检测，后经鄙人优化后，提高了人脸检测效果，并支持人脸关键点检测，人体检测。数据集是WiderFace,VOC和COCO。

### （2）端上部署 ###

> 原始代码已经支持MNN和NCNN

### （3）依赖库 ###

*  TNN：[https://github.com/Tencent/TNN][https_github.com_Tencent_TNN]
 *  OpenCV: [Releases - OpenCV][] （推荐opencv-4.3.0）
 *  OpenCL: [Choose & Download Intel® SDK for OpenCL™ Applications][Choose _ Download Intel_ SDK for OpenCL_ Applications] (GPU的支持)
 *  base-utils：[https://github.com/PanJinquan/base-utils][https_github.com_PanJinquan_base-utils] (一些文件和图像处理的相关工具)
 *  拉取子模块submodule(TNN,base-utils)库

# pull 3rdparty(TNN,base-utils) submodule
    git submodule init
    git submodule update

*  配置OpenCV

> 推荐opencv-4.3.0

mkdir build
    cd build
    cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local ..
    sudo make install

*  配置OpenCL（可选）

> Android系统一般都支持OpenCL，Linux系统可参考如下配置：

# 参考安装OpenCL： https://blog.csdn.net/qq_28483731/article/details/68235383，作为测试，安装`intel cpu版本的OpenCL`即可
    # 安装clinfo，clinfo是一个显示OpenCL平台和设备的软件
    sudo apt-get install clinfo
    # 安装依赖
    sudo apt install dkms xz-utils openssl libnuma1 libpciaccess0 bc curl libssl-dev lsb-core libicu-dev
    sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 3FA7E0328081BFF6A14DA29AA6A19B38D3D831EF
    echo "deb http://download.mono-project.com/repo/debian wheezy main" | sudo tee /etc/apt/sources.list.d/mono-xamarin.list
    sudo apt-get update
    sudo apt-get install mono-complete
    # 在intel官网上下载了intel SDK的tgz文件，并且解压
    sudo sh install.sh

*  CMake配置说明

> Linux OR Windows测试，`CMakeLists.txt`

# TNN set
        set(TNN_OPENCL_ENABLE ON CACHE BOOL "" FORCE)
        set(TNN_CPU_ENABLE ON CACHE BOOL "" FORCE)
        set(TNN_X86_ENABLE ON CACHE BOOL "" FORCE)
        set(TNN_QUANTIZATION_ENABLE OFF CACHE BOOL "" FORCE)
        set(TNN_OPENMP_ENABLE ON CACHE BOOL "" FORCE)  # Multi-Thread
        add_definitions(-DTNN_OPENCL_ENABLE)           # for OpenCL GPU
        add_definitions(-DDEBUG_ON)                    # for WIN/Linux Log
        add_definitions(-DDEBUG_LOG_ON)                # for WIN/Linux Log
        add_definitions(-DDEBUG_IMSHOW_OFF)            # for OpenCV show
        add_definitions(-DPLATFORM_LINUX)
        # add_definitions(-DPLATFORM_WINDOWS)

--------------------

## 2. 人脸人体检测Demo ##

推理框架使用TNN进行部署，手撸Python转C++实现人脸人体检测推理过程，

下面是测试代码demo部分代码

void test_face_person_detector() {
        const int num_thread = 1;
        DeviceType device = CPU;
        // 人脸和关键点检测
        // const char *model_file = (char *) "../data/tnn/face_ldmks/rfb_landm_face_320_320_sim.opt.tnnmodel";
        // const char *proto_file = (char *) "../data/tnn/face_ldmks/rfb_landm_face_320_320_sim.opt.tnnproto";
        // ObjectDetectiobParam model_param = FACE_LANDMARK_MODEL;
    
        // 人脸+人体检测
        // const char *model_file = (char *) "../data/tnn/face_person/rfb1.0_face_person_300_300_sim.opt.tnnmodel";
        // const char *proto_file = (char *) "../data/tnn/face_person/rfb1.0_face_person_300_300_sim.opt.tnnproto";
        // ObjectDetectiobParam model_param = FACE_PERSON_MODEL;//模型参数
        // 人脸检测
        const char *model_file = (char *) "../data/tnn/face/rfb1.0_face_320_320.opt.tnnmodel";
        const char *proto_file = (char *) "../data/tnn/face/rfb1.0_face_320_320.opt.tnnproto";
        ObjectDetectiobParam model_param = FACE_MODEL;//模型参数
    
    
        // 设置检测阈值
        const float scoreThresh = 0.5;
        const float iouThresh = 0.3;
        ObjectDetection *detector = new ObjectDetection(model_file,
                                                        proto_file,
                                                        model_param,
                                                        num_thread,
                                                        device);
    
        string image_dir = "../data/test_image/person";
        std::vector<string> image_list = get_files_list(image_dir);
        for (string image_path:image_list) {
            cv::Mat bgr_image = cv::imread(image_path);
            if (bgr_image.empty()) continue;
            FrameInfo resultInfo;
            printf("init frame\n");
            // 开始检测
            detector->detect(bgr_image, &resultInfo, scoreThresh, iouThresh);
            // 可视化代码
            detector->visualizeResult(bgr_image, &resultInfo);
        }
        delete detector;
        detector = nullptr;
        printf("FINISHED.\n");
    }

--------------------

## 3. Android Demo效果 ##

可以轻松移植到Android系统，在普通手机，CPU和GPU都可以达到实时检测

> 人脸检测+人脸关键点检测+人体检测Android Demo APP(非源码，仅供学习交流)：
> 
> 链接: https://pan.baidu.com/s/1By43I1DbMa0gBPLObtPZMQ 提取码: msnr 
> 
> 需要源码请微信联系，仅供学习交流

这是APP的检测效果：

<table> 
 <tbody> 
  <tr> 
   <td style="text-align:center;">APP</td> 
   <td style="text-align:center;">模型选择</td> 
   <td style="text-align:center;">人脸检测</td> 
  </tr> 
  <tr> 
   <td style="text-align:center;"><img alt="" height="1200" src="https://img-blog.csdnimg.cn/20211010172631426.png?x-oss-process=image/watermark,type_ZHJvaWRzYW5zZmFsbGJhY2s,shadow_50,text_Q1NETiBAcGFuX2ppbnF1YW4=,size_20,color_FFFFFF,t_70,g_se,x_16" width="1080"></td> 
   <td style="text-align:center;"><img alt="" height="1200" src="https://img-blog.csdnimg.cn/20211010172654773.png?x-oss-process=image/watermark,type_ZHJvaWRzYW5zZmFsbGJhY2s,shadow_50,text_Q1NETiBAcGFuX2ppbnF1YW4=,size_20,color_FFFFFF,t_70,g_se,x_16" width="1080"></td> 
   <td style="text-align:center;"><img alt="" height="1200" src="https://img-blog.csdnimg.cn/20211010172739815.png?x-oss-process=image/watermark,type_ZHJvaWRzYW5zZmFsbGJhY2s,shadow_50,text_Q1NETiBAcGFuX2ppbnF1YW4=,size_20,color_FFFFFF,t_70,g_se,x_16" width="1080"></td> 
  </tr> 
  <tr> 
   <td style="text-align:center;">人脸关键点检测</td> 
   <td style="text-align:center;">人体检测</td> 
   <td style="text-align:center;">人脸+人体检测</td> 
  </tr> 
  <tr> 
   <td style="text-align:center;"><img alt="" height="1200" src="https://img-blog.csdnimg.cn/2021101017295120.png?x-oss-process=image/watermark,type_ZHJvaWRzYW5zZmFsbGJhY2s,shadow_50,text_Q1NETiBAcGFuX2ppbnF1YW4=,size_20,color_FFFFFF,t_70,g_se,x_16" width="1080"></td> 
   <td style="text-align:center;"><img alt="" height="1200" src="https://img-blog.csdnimg.cn/20211010172852940.png?x-oss-process=image/watermark,type_ZHJvaWRzYW5zZmFsbGJhY2s,shadow_50,text_Q1NETiBAcGFuX2ppbnF1YW4=,size_20,color_FFFFFF,t_70,g_se,x_16" width="1080"></td> 
   <td style="text-align:center;"><img alt="" src="https://img-blog.csdnimg.cn/204df95dc2ad4f9483e1d91eb9e83644.jpg?x-oss-process=image/watermark,type_ZHJvaWRzYW5zZmFsbGJhY2s,shadow_50,text_Q1NETiBAcGFuX2ppbnF1YW4=,size_20,color_FFFFFF,t_70,g_se,x_16"></td> 
  </tr> 
  <tr> 
   <td></td> 
   <td></td> 
   <td></td> 
  </tr> 
 </tbody> 
</table>

## 4.人体关键点Demo（Android版本） ##

人体关键点检测需要用到人体检测，请查看鄙人另一篇博客：[2D Pose人体关键点实时检测(Python/Android /C++ Demo)\_pan\_jinquan的博客-CSDN博客][2D Pose_Python_Android _C_ Demo_pan_jinquan_-CSDN]

![20210723091643896.gif][]

如果你觉得该帖子帮到你，还望贵人多多支持，鄙人会再接再厉，继续努力的~

![watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAcGFuX2ppbnF1YW4_size_20_color_FFFFFF_t_70_g_se_x_16][]

[https_panjinquan.blog.csdn.net_article_details_120688804]: https://panjinquan.blog.csdn.net/article/details/120688804
[https_github.com_Linzaer_Ultra-Light-Fast-Generic-Face-Detector-1MB]: https://github.com/Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB
[https_github.com_Tencent_TNN]: https://github.com/Tencent/TNN
[Releases - OpenCV]: https://opencv.org/releases
[Choose _ Download Intel_ SDK for OpenCL_ Applications]: https://software.intel.com/content/www/us/en/develop/tools/opencl-sdk/choose-download.html
[https_github.com_PanJinquan_base-utils]: https://github.com/PanJinquan/base-utils
[2D Pose_Python_Android _C_ Demo_pan_jinquan_-CSDN]: https://panjinquan.blog.csdn.net/article/details/115765863
[20210723091643896.gif]: /images/20220828/d3f805a07db144179077bfe5822cb889.png
[watermark_type_ZHJvaWRzYW5zZmFsbGJhY2s_shadow_50_text_Q1NETiBAcGFuX2ppbnF1YW4_size_20_color_FFFFFF_t_70_g_se_x_16]: /images/20220828/ca57ce9c3950410396c5c854f98242e7.png