diff --git a/CMakeLists.txt b/CMakeLists.txt
index 542f20d..8e3cb76 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -68,4 +68,8 @@ target_link_libraries(onnx Qt6::Widgets ${MIL_LIBS})
 
 add_executable(opencv_onnx opencv_onnx.cpp)
 # 链接 OpenCV 和 Qt 库
-target_link_libraries(opencv_onnx Qt6::Widgets ${OpenCV_LIBS} comdlg32)
\ No newline at end of file
+target_link_libraries(opencv_onnx Qt6::Widgets ${OpenCV_LIBS} comdlg32)
+
+
+add_executable(create_mask Matrox/mask.cpp)
+target_link_libraries(create_mask Qt6::Widgets ${OpenCV_LIBS} ${MIL_LIBS})
\ No newline at end of file
diff --git a/Matrox/mask.cpp b/Matrox/mask.cpp
new file mode 100644
index 0000000..cf0ae1b
--- /dev/null
+++ b/Matrox/mask.cpp
@@ -0,0 +1,76 @@
+#include <opencv2/opencv.hpp>
+#include <vector>
+#include <iostream>
+
+// 读取二值化的单通道一位图片并生成掩膜
+std::vector<std::vector<bool>> generateMaskFromImage(const std::string& imagePath, int widthBlocks, int heightBlocks, int threshold = 10) {
+    // 读取图像
+    cv::Mat image = cv::imread(imagePath, cv::IMREAD_GRAYSCALE);
+
+    // 检查图像是否成功读取
+    if (image.empty()) {
+        std::cerr << "无法加载图像，请检查路径是否正确: " << imagePath << std::endl;
+        exit(EXIT_FAILURE);
+    }
+
+    // 确保图像是二值化的
+    cv::threshold(image, image, 128, 255, cv::THRESH_BINARY);
+
+    // 获取图像的宽度和高度
+    int imageWidth = image.cols;
+    int imageHeight = image.rows;
+
+    // 计算每个块的宽度和高度
+    int blockWidth = imageWidth / widthBlocks;
+    int blockHeight = imageHeight / heightBlocks;
+
+    // 创建掩膜矩阵
+    std::vector<std::vector<bool>> mask(heightBlocks, std::vector<bool>(widthBlocks, false));
+
+    // 遍历每个块并统计白色像素点的数量
+    for (int i = 0; i < heightBlocks; ++i) {
+        for (int j = 0; j < widthBlocks; ++j) {
+            // 计算块的起始和结束位置
+            int x_start = j * blockWidth;
+            int y_start = i * blockHeight;
+            int x_end = (j == widthBlocks - 1) ? imageWidth : (j + 1) * blockWidth;
+            int y_end = (i == heightBlocks - 1) ? imageHeight : (i + 1) * blockHeight;
+
+            // 提取当前块
+            cv::Mat block = image(cv::Rect(x_start, y_start, x_end - x_start, y_end - y_start));
+
+            // 统计块中白色像素的数量
+            int whitePixelCount = cv::countNonZero(block);
+
+            // 如果白色像素数大于阈值，将该块标记为 true
+            if (whitePixelCount > threshold) {
+                mask[i][j] = true;
+            }
+        }
+    }
+
+    return mask;
+}
+
+int main() {
+    // 指定图像路径
+    std::string imagePath = "C:\\Users\\zjc\\Desktop\\diguandai.png";
+
+    // 设置分块数量和白色像素点阈值
+    int widthBlocks = 24;
+    int heightBlocks = 24;
+    int threshold = 20;
+
+    // 生成掩膜
+    std::vector<std::vector<bool>> mask = generateMaskFromImage(imagePath, widthBlocks, heightBlocks, threshold);
+
+    // 打印掩膜结果
+    for (int i = 0; i < heightBlocks; ++i) {
+        for (int j = 0; j < widthBlocks; ++j) {
+            std::cout << (mask[i][j] ? "1 " : "0 ");
+        }
+        std::cout << std::endl;
+    }
+
+    return 0;
+}