pans

2016-12-20 8bfbca2b0ef708f12466c3b9a38b6c99a5c25268

git-svn-id: http://192.168.1.226/svn/proxy@23 454eff88-639b-444f-9e54-f578c98de674

 RtspFace/demo/demo.cpp

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#include <stdio.h>
#include <iostream>
#include <opencv2/opencv.hpp>
#include "time_helper.h"
#include "cv_face.h"
#include <windows.h>

#define DEFAULT_THRESHOLD (0.5)
using namespace std;
using namespace cv;

// @获取人脸特征值
// @param bgr_image 需要提取特征值的图片
// @param handle_verify 已经初始化的人脸验证句柄
cv_feature_t * getFeature(Mat bgr_image,cv_handle_t handle_verify) {

    cv_feature_t *p_feature = NULL;
    Mat image_color;
    image_color = bgr_image;

    //调用句柄。用于保存函数及数据的句柄
    cv_handle_t handle_detect = NULL;

    //人脸信息结构体
    cv_face_t *p_face = NULL;

    int face_count = 0;

    //函数返回的错误代码类型
    cv_result_t cv_result = CV_OK;
    char *string_feature;
    do 
    {
        // 创建静态图片人脸检测句柄
        cv_result = cv_face_create_detector(&handle_detect, NULL, CV_DETECT_ENABLE_ALIGN_21);
        if (cv_result != CV_OK) {
            fprintf(stderr, "fail to init detect handle, error code %d\n", cv_result);
            break;
        }

        // 人脸检测1.成功返回CV_OK，否则返回错误类型
        cv_result = cv_face_detect(handle_detect, image_color.data, CV_PIX_FMT_BGR888,
            image_color.cols, image_color.rows, image_color.step,
            CV_FACE_UP, &p_face, &face_count);
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_detect failed, error code : %d\n", cv_result);
            break;
        }

        if (face_count > 0) {
            //用于表示人脸特征信息
            float score;
            unsigned int feature_length = 0;

            // get feature
            __TIC__();
            //提取人脸特征1，可以把返回数组编码成字符串后存储起来以便以后使用
            cv_result = cv_verify_get_feature(handle_verify, image_color.data, CV_PIX_FMT_BGR888,
                image_color.cols, image_color.rows, image_color.step, p_face,
                &p_feature, &feature_length);
            __TOC__();
            if (cv_result != CV_OK) {
                fprintf(stderr, "cv_verify_get_feature failed, error code %d\n", cv_result);
                break;
            }

            if (feature_length > 0 ) {

                // test serial and deserial
                string_feature = new char[CV_ENCODE_FEATURE_SIZE(p_feature)];
                cv_verify_serialize_feature(p_feature, string_feature);

                //释放提取人脸特征时分配的空间
                cv_verify_release_feature(p_feature);
                break;
            } else {
                fprintf(stderr, "error, the feature length is 0!\n");
            }
            // 释放提取人脸特征时分配的空间
            cv_verify_release_feature(p_feature);

        } else {
            if (face_count == 0) {
                fprintf(stderr, "can't find face in \n");
            }
        }
    } while (0);
    cv_face_release_detector_result(p_face, face_count);
    return string_feature;
}


//测试确定人脸位置
int testface_detect(Mat bgr_image_color,char* output_image_path ){

    int points_size = 106;
    int config;
    if (points_size == 21) {
        config = CV_DETECT_ENABLE_ALIGN_21;
    }
    else if (points_size == 106) {
        config = CV_DETECT_ENABLE_ALIGN_106;
    }
    else {
        fprintf(stderr, "alignment point size error, must be 21 or 106\n");
        return -1;
    }

    // load image
    Mat image_color;


    //    cvtColor(bgr_image_color, image_color, CV_BGR2BGRA);    // CV_PIX_FMT_BGRA8888
    image_color = bgr_image_color;                          // CV_PIX_FMT_BGR888

    // init detect handle
    cv_handle_t handle_detect = NULL;
    cv_result_t cv_result = CV_OK;
    cv_face_t* p_face = NULL;
    int face_count = 0;
    do 
    {
        cv_result = cv_face_create_detector(&handle_detect, NULL, config);
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_create_detector failed, error code %d\n", cv_result);
            break;
        }

        /*
        * test get and set threshold
        */
        float default_threshold;
        cv_result = cv_face_detect_get_threshold(handle_detect, &default_threshold);
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_detect_get_threshold failed, error code %d\n", cv_result);
            break;
        }
        fprintf(stderr, "default threshold : %f\n", default_threshold);

        cv_result = cv_face_detect_set_threshold(handle_detect, default_threshold);
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_detect_set_threshold failed, error code %d\n", cv_result);
            break;
        }
        fprintf(stderr, "threshold set : %f\n", default_threshold);


        // detect
        __TIC__();
        cv_result = cv_face_detect(handle_detect, image_color.data, CV_PIX_FMT_BGR888,
            image_color.cols, image_color.rows, image_color.step,
            CV_FACE_UP, &p_face, &face_count);
        __TOC__();
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_detect error %d\n", cv_result);
            break;
        }

        if (face_count > 0) {
            // draw result
            for (int i = 0; i < face_count; i++) {
                rectangle(image_color, Point(p_face[i].rect.left, p_face[i].rect.top),
                    Point(p_face[i].rect.right, p_face[i].rect.bottom),
                    Scalar(0, 255, 0), 2, 8, 0);
                fprintf(stderr, "face number: %d\n", i + 1);
                fprintf(stderr, "face rect: [%d, %d, %d, %d]\n", p_face[i].rect.top,
                    p_face[i].rect.left,
                    p_face[i].rect.right, p_face[i].rect.bottom);
                fprintf(stderr, "score: %f\n", p_face[i].score);
                fprintf(stderr, "face pose: [yaw: %f, pitch: %f, roll: %f, eye distance: %f]\n",
                    p_face[i].yaw,
                    p_face[i].pitch, p_face[i].roll, p_face[i].eye_dist);
                fprintf(stderr, "face algin:\n");
                for (unsigned int j = 0; j < p_face[i].points_count; j++) {
                    float x = p_face[i].points_array[j].x;
                    float y = p_face[i].points_array[j].y;
                    fprintf(stderr, "(%.2f, %.2f)\n", x, y);
                    circle(image_color, Point2f(x, y), 2, Scalar(0, 0, 255), -1);
                }
                fprintf(stderr, "\n");
            }
            // save image
            imwrite(output_image_path, image_color);
        }
        else {
            fprintf(stderr, "can't find face in ");
        }

    } while (0);


    // release the memory of face
    cv_face_release_detector_result(p_face, face_count);
    // destroy detect handle
    cv_face_destroy_detector(handle_detect);


    fprintf(stderr, "test finish!\n");
    return 0;
}

// @brief 测试人脸对比
// @param bgr_image_1 图像1
// @param bgr_image_1 图像2
int testface_verify(Mat bgr_image_1,Mat bgr_image_2){

    // 保存两个图片的原始数据
    Mat image_color_1,image_color_2;
    //    cvtColor(bgr_image_1, image_color_color_1, CV_BGR2BGRA);    // CV_PIX_FMT_BGRA8888
    image_color_1 = bgr_image_1;                                // CV_PIX_FMT_BGR888
    //    cvtColor(bgr_image_2, image_color_2, CV_BGR2BGRA);
    image_color_2 = bgr_image_2;

    int main_return = -1;

    //调用句柄。用于保存函数及数据的句柄
    cv_handle_t handle_detect = NULL;
    cv_handle_t handle_verify = NULL;

    //人脸信息结构体
    cv_face_t *p_face_1 = NULL;
    cv_face_t *p_face_2 = NULL;

    int face_count_1 = 0;
    int face_count_2 = 0;

    //函数返回的错误代码类型
    cv_result_t cv_result = CV_OK;

    do {
        cout<<"a"<<endl;
        // 创建静态图片人脸检测句柄
        cv_result = cv_face_create_detector(&handle_detect, NULL, CV_DETECT_ENABLE_ALIGN_21);

        if (cv_result != CV_OK) {
            fprintf(stderr, "fail to init detect handle, error code %d\n", cv_result);
            break;
        }

        // 人脸检测1.成功返回CV_OK，否则返回错误类型
        cv_result = cv_face_detect(handle_detect, image_color_1.data, CV_PIX_FMT_BGR888,
            image_color_1.cols, image_color_1.rows, image_color_1.step,
            CV_FACE_UP, &p_face_1, &face_count_1);
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_detect failed, error code : %d\n", cv_result);
            break;
        }

        // 人脸检测2.成功返回CV_OK，否则返回错误类型
        cv_result = cv_face_detect(handle_detect, image_color_2.data, CV_PIX_FMT_BGR888,
            image_color_2.cols, image_color_2.rows, image_color_2.step,
            CV_FACE_UP, &p_face_2, &face_count_2);
        if (cv_result != CV_OK) {
            fprintf(stderr, "cv_face_detect failed, error code : %d\n", cv_result);
            break;
        }

        // 人脸验证
        if (face_count_1 > 0 && face_count_2 > 0) {
            // 创建人脸验证句柄
            cv_result = cv_verify_create_handle(&handle_verify, "../../../models/verify.model");
            if (cv_result != CV_OK)
            {
                fprintf(stderr, "fail to init verify handle, error code %d\n", cv_result);
                break;
            }

            if (handle_verify) {
                int model_version = cv_verify_get_version(handle_verify);
                fprintf(stderr, "verify model version : %d\n", model_version);
                int feature_length = cv_verify_get_feature_length(handle_verify);
                fprintf(stderr, "verify model feature length : %d\n", feature_length);

                //用于表示人脸特征信息
                cv_feature_t *p_feature_1 = NULL, *p_feature_2 = NULL;
                float score;
                unsigned int feature_length_1 = 0, feature_length_2 = 0;

                // get feature
                __TIC__();
                //提取人脸特征1，可以把返回数组编码成字符串后存储起来以便以后使用
                cv_result = cv_verify_get_feature(handle_verify, image_color_1.data, CV_PIX_FMT_BGR888,
                    image_color_1.cols, image_color_1.rows, image_color_1.step, p_face_1,
                    &p_feature_1, &feature_length_1);
                __TOC__();
                if (cv_result != CV_OK) {
                    fprintf(stderr, "cv_verify_get_feature failed, error code %d\n", cv_result);
                    break;
                }
                //提取人脸特征1，可以把返回数组编码成字符串后存储起来以便以后使用
                cv_result = cv_verify_get_feature(handle_verify, image_color_2.data, CV_PIX_FMT_BGR888,
                    image_color_2.cols, image_color_2.rows, image_color_2.step, p_face_2, 
                    &p_feature_2, &feature_length_2);
                if (cv_result != CV_OK) {
                    fprintf(stderr, "cv_verify_get_feature failed, error code %d\n", cv_result);
                    break;
                }

                if (feature_length_1 > 0 && feature_length_2 > 0) {
                    cv_feature_header_t *p_feature_header = CV_FEATURE_HEADER(p_feature_1);
                    fprintf(stderr, "Feature information:\n");
                    fprintf(stderr, "    ver:\t0x%08x\n", p_feature_header->ver);
                    fprintf(stderr, "    length:\t%d bytes\n", p_feature_header->len);

                    // 人脸验证
                    cv_result = cv_verify_compare_feature(handle_verify, p_feature_1,
                        p_feature_2, &score);
                    if (cv_result == CV_OK) {
                        fprintf(stderr, "score: %f\n", score);
                        // comapre score with DEFAULT_THRESHOLD
                        // > DEFAULT_THRESHOLD => the same person
                        // < DEFAULT_THRESHOLD => different people
                        if (score > DEFAULT_THRESHOLD)
                            fprintf(stderr, "the same person.\n");
                        else
                            fprintf(stderr, "different people.\n");

                        main_return = 0;  // success
                    }
                    else {
                        fprintf(stderr, "cv_verify_compare_feature failed, error code : %d\n", cv_result);
                    }

                    // test serial and deserial
                    char *string_feature_1 = new char[CV_ENCODE_FEATURE_SIZE(p_feature_1)];
                    cv_verify_serialize_feature(p_feature_1, string_feature_1);
                    cout<<string_feature_1<<endl;
                    cv_feature_t *p_feature_new_1 = cv_verify_deserialize_feature(string_feature_1);
                    delete[]string_feature_1;
                    char *string_feature_2;
                    string_feature_2 = new char[CV_ENCODE_FEATURE_SIZE(p_feature_2)];
                    cv_verify_serialize_feature(p_feature_2, string_feature_2);
                    cout<<string_feature_2<<endl;
                    cv_feature_t *p_feature_new_2 = cv_verify_deserialize_feature(string_feature_2);
                    delete[]string_feature_2;

                    score = 0.0;
                    cv_result = cv_verify_compare_feature(handle_verify, p_feature_1,
                        p_feature_2, &score);
                    fprintf(stderr, "after serial and deserial the feature compare score is %f  \n", score);
                    cin>>string_feature_2;
                    //释放提取人脸特征时分配的空间
                    cv_verify_release_feature(p_feature_new_1);
                    cv_verify_release_feature(p_feature_new_2);
                }
                else {
                    fprintf(stderr, "error, the feature length is 0!\n");
                }
                // 释放提取人脸特征时分配的空间
                cv_verify_release_feature(p_feature_1);
                cv_verify_release_feature(p_feature_2);

            }
        }
        else {
            if (face_count_1 == 0) {
                fprintf(stderr, "can't find face in \n");
            }
            if (face_count_2 == 0) {
                fprintf(stderr, "can't find face in \n");
            }
        }
    } while (0);


    // release the memory of face
    cv_face_release_detector_result(p_face_1, face_count_1);
    cv_face_release_detector_result(p_face_2, face_count_2);
    // destroy detect handle
    cv_face_destroy_detector(handle_detect);
    // destroy verify handle
    cv_verify_destroy_handle(handle_verify);
    fprintf(stderr, "test finish!\n");
    return 0;
}

int main() {

    //图片入口，现需经过OPENCV处理后被sdk使用。
    char* input_image_path = "../../test_image/face_06.jpg";
    char* output_image_path = "../../test_image/face_06out.jpg";

    // 创建人脸验证句柄并初始化
    //函数返回的错误代码类型
    cv_result_t cv_result = CV_OK;
    cv_handle_t handle_verify =NULL;
    cv_result = cv_verify_create_handle(&handle_verify, "../../../models/verify.model");
    if (cv_result != CV_OK)
    {
        fprintf(stderr, "fail to init verify handle, error code %d\n", cv_result);

    }

	
    //-------测试人脸 识别位置 start-------
    Mat bgr_image_1 = imread(input_image_path);
    if (!bgr_image_1.data) {
    fprintf(stderr, "fail to read %s\n", input_image_path);
    return -1;
    }else
    {
    testface_detect(bgr_image_1,output_image_path);
    }
    //-------测试人脸 识别位置 end-------
/*
    //-------测试人脸 验证 start-------
    output_image_path = "../../test_image/face_04.jpg";
    Mat bgr_image_2 = imread(output_image_path);
    if (!bgr_image_2.data) {
    fprintf(stderr, "fail to read %s\n", output_image_path);
    return -1;
    }else
    {
    testface_verify(bgr_image_color,bgr_image_2);
    }
    //-------测试人脸 验证 end-------
	

    //-------测试提取人脸特征值 start-------
    Mat bgr_image_1 = imread(input_image_path);
    char *string_feature;

    if (!bgr_image_1.data) {
        fprintf(stderr, "fail to read %s\n", input_image_path);
        return -1;
    }else
    {
        string_feature=getFeature(bgr_image_1,handle_verify);
    }
    cout<<string_feature<<endl;
    //-------测试提取人脸特征值 end-------
*/
    //




    cin>>cv_result;
    Sleep(100);
    return 0;
}