增加原图和美白图对比，支持色阶微调

opencv/cv07_cleanLight.cpp

@@ -0,0 +1,83 @@
+#include <opencv2/opencv.hpp>
+#include <iostream>
+
+#pragma comment(lib, "opencv_world4100.lib")
+
+
+using namespace cv;
+using namespace std;
+
+void removeShadow(const Mat& src, Mat& dst) {
+    // 1. 将图像转换为 HSV 色彩空间
+    Mat hsv;
+    cvtColor(src, hsv, COLOR_BGR2HSV);
+
+    // 分离通道
+    vector<Mat> hsvChannels;
+    split(hsv, hsvChannels);
+
+    // 2. 对 V 通道进行处理
+    Mat vChannel = hsvChannels[2];
+    Mat element = getStructuringElement(MORPH_RECT, Size(3, 3));
+    int iteration = 9;
+
+    // 3. 膨胀和腐蚀操作
+    Mat dilateMat;
+    morphologyEx(vChannel, dilateMat, MORPH_DILATE, element, Point(-1, -1), iteration);
+    Mat erodeMat;
+    morphologyEx(dilateMat, erodeMat, MORPH_ERODE, element, Point(-1, -1), iteration);
+
+    // 4. 计算去阴影效果
+    Mat calcMat = ~(erodeMat - vChannel);
+    normalize(calcMat, calcMat, 0, 255, NORM_MINMAX);
+
+    // 5. 将处理后的 V 通道与原始 H 和 S 通道合并
+    hsvChannels[2] = calcMat;
+    merge(hsvChannels, hsv);
+
+    // 6. 将 HSV 转换回 BGR 色彩空间
+    cvtColor(hsv, dst, COLOR_HSV2BGR);
+}
+
+
+int main(int argc, char** argv) {
+    // 读取输入图像
+    Mat src = imread("test.webp");
+    if (src.empty()) {
+        cerr << "无法加载图像\n";
+        return -1;
+    }
+
+    Mat result;
+    removeShadow(src, result);
+
+    // 调整对比度和亮度
+    double alpha = 1.1;  // 对比度因子
+    int beta = 5;       // 亮度偏移
+    convertScaleAbs(result, result, alpha, beta);
+
+
+    // 获取原始图像比例
+    Size srcSize = src.size();
+
+    // 计算显示尺寸，保持比例
+    int displayHeight = 1080;
+    int displayWidth = srcSize.width * displayHeight / srcSize.height;
+
+    // 调整图像大小以保持比例
+    Mat resizedSrc, resizedResult;
+    resize(src, resizedSrc, Size(displayWidth, displayHeight));
+    resize(result, resizedResult, Size(displayWidth, displayHeight));
+
+    // 拼接图像
+    Mat combined;
+    hconcat(resizedSrc, resizedResult, combined);
+
+    // 显示结果
+    imshow("原图和去除阴影后的图像对比", combined);
+    waitKey(0);
+    // 保存结果
+    imwrite("output.jpg", result);
+
+    return 0;
+}

opencv/cv08_cleanLight.cpp

@@ -0,0 +1,164 @@
+#include <opencv2/opencv.hpp>
+#include <windows.h>
+
+#include <stdio.h>
+#include <string.h>
+
+#pragma comment(lib, "opencv_world4100.lib")
+using namespace cv;
+using namespace std;
+
+void removeShadow(const Mat &src, Mat &dst);
+void resizeToFitScreen(const Mat &src, Mat &resized, int screenWidth, int screenHeight);
+void applyLevels(Mat &img, int black, int white);
+void readOrWriteConfig(const char *filename, double *alpha, int *beta, int *black, int *white);
+int  main(int argc, char *argv[])
+{
+
+    if (argc < 2) {
+        puts("文稿一键美白App  By 蘭雅    捞鱼吧 bbs.lyvba.com\n");
+        puts("Usage: cleanLight.exe  image  [new_image]\n");
+        int i = getchar();
+        return 8;
+    }
+
+    // 读取输入图像
+    Mat src = imread(argv[1]);
+    if (src.empty()) {
+        puts("Error: Could not open or find the image.\n");
+        return -1;
+    }
+
+    Mat result;
+    removeShadow(src, result);
+
+    // 设置对比度和亮度参数
+    double  alpha  = 1.2; // 对比度因子
+    int     beta   = 8;   // 亮度偏移
+    int     black  = 30;   // 色阶黑阈值
+    int     white  = 235;   // 色阶白阈值
+    
+    const char *inifile = "cleanLight.ini";
+    readOrWriteConfig(inifile, &alpha, &beta, &black, &white);
+
+    convertScaleAbs(result, result, alpha, beta);
+
+    // 应用色阶调整
+    applyLevels(result, black, white);
+
+    // 7. 将结果保存为图像
+    char filename[256] = "removeShadow_color.png";
+    if (argc == 3) strcpy(filename, argv[2]);
+    imwrite(filename, result);
+
+    // 屏幕分辨率
+    int screenWidth  = 1920;
+    int screenHeight = 1080;
+
+    // 调整图像大小
+    Mat resizedSrc, resizedResult;
+    resizeToFitScreen(src, resizedSrc, screenWidth / 2, screenHeight);
+    resizeToFitScreen(result, resizedResult, screenWidth / 2, screenHeight);
+
+    // 拼接图像
+    Mat combined;
+    hconcat(resizedSrc, resizedResult, combined);
+
+    // 显示结果
+    imshow("原图和文稿一键美白图像 By 蘭雅", combined);
+    waitKey(50);
+
+    MessageBoxA(NULL,"文稿一键美白完成，感谢您的试用!\n原创软件->捞鱼吧 bbs.lyvba.com\n对比度和色阶微调请修改 cleanLight.ini\n",
+        "文稿一键美白App  By 蘭雅", MB_ICONINFORMATION);
+
+    return 0;
+}
+
+void readOrWriteConfig(const char *filename, double *alpha, int *beta, int *black, int *white)
+{
+    // 尝试打开文件
+    FILE *file = fopen(filename, "r");
+    if (file) {
+        // 如果文件存在，从中读取变量
+        fscanf(file, "%lf %d %d %d", alpha, beta, black, white);
+        fclose(file);
+        printf("读取成功: alpha = %.2f, beta = %d\n色阶黑白阈值: black = %d, white = %d\n", *alpha, *beta, *black, *white);
+    }
+    else {
+        // 如果文件不存在，创建文件并写入变量
+        *alpha = 1.2;
+        *beta  = 8;
+        *black  = 30; 
+        *white  = 235;
+        file = fopen(filename, "w");
+        if (file) {
+            fprintf(file, "%.2f %d %d %d\n", *alpha, *beta, *black, *white);
+            fclose(file);
+            printf("文件未找到，已创建并写入: alpha = %.2f, beta = %d\n色阶黑白阈值: black = %d, white = %d\n", *alpha, *beta, *black, *white);
+        }
+        else {
+            perror("无法创建文件");
+            exit(EXIT_FAILURE);
+        }
+    }
+}
+
+void removeShadow(const Mat &src, Mat &dst)
+{
+    // 1. 将图像转换为 HSV 色彩空间
+    Mat hsv;
+    cvtColor(src, hsv, COLOR_BGR2HSV);
+
+    // 分离通道
+    vector<Mat> hsvChannels;
+    split(hsv, hsvChannels);
+
+    // 2. 对 V 通道进行处理
+    Mat vChannel  = hsvChannels[2];
+    Mat element   = getStructuringElement(MORPH_RECT, Size(3, 3));
+    int iteration = 9;
+
+    // 3. 膨胀和腐蚀操作
+    Mat dilateMat;
+    morphologyEx(vChannel, dilateMat, MORPH_DILATE, element, Point(-1, -1), iteration);
+    Mat erodeMat;
+    morphologyEx(dilateMat, erodeMat, MORPH_ERODE, element, Point(-1, -1), iteration);
+
+    // 4. 计算去阴影效果
+    Mat calcMat = ~(erodeMat - vChannel);
+    normalize(calcMat, calcMat, 0, 255, NORM_MINMAX);
+
+    // 5. 将处理后的 V 通道与原始 H 和 S 通道合并
+    hsvChannels[2] = calcMat;
+    merge(hsvChannels, hsv);
+
+    // 6. 将 HSV 转换回 BGR 色彩空间
+    cvtColor(hsv, dst, COLOR_HSV2BGR);
+}
+
+void resizeToFitScreen(const Mat &src, Mat &resized, int screenWidth, int screenHeight)
+{
+    Size srcSize = src.size();
+    int  newWidth, newHeight;
+
+    // 检测是宽大还是高大
+    if (srcSize.width > srcSize.height) {
+        // 按屏幕宽等比缩放
+        newWidth  = screenWidth;
+        newHeight = srcSize.height * screenWidth / srcSize.width;
+    }
+    else {
+        // 按屏幕高等比缩放
+        newHeight = screenHeight;
+        newWidth  = srcSize.width * screenHeight / srcSize.height;
+    }
+
+    resize(src, resized, Size(newWidth, newHeight));
+}
+
+void applyLevels(Mat &img, int black, int white)
+{
+    // 计算缩放因子
+    double scale = 255.0 / (white - black);
+    img.convertTo(img, CV_8U, scale, -black * scale);
+}