没有高斯颜色的时候测试

apps/TextureMesh/TextureMesh.cpp

@@ -1098,7 +1098,9 @@ int main(int argc, LPCTSTR* argv)
 		return EXIT_FAILURE;
 	printf("Now\n");
 	VERBOSE(MAKE_PATH_SAFE(OPT::strMeshFileName));
-	if (!OPT::strMeshFileName.empty() && !scene.mesh.Load(MAKE_PATH_SAFE(OPT::strMeshFileName))) {
+	bool bVertexColorExists = false;
+	bool *pBExistVertexColor = &bVertexColorExists;
+	if (!OPT::strMeshFileName.empty() && !scene.mesh.Load(MAKE_PATH_SAFE(OPT::strMeshFileName), pBExistVertexColor)) {
 		VERBOSE("error: cannot load mesh file");
 		return EXIT_FAILURE;
 	}
@@ -1134,7 +1136,7 @@ int main(int argc, LPCTSTR* argv)
 	if (!scene.TextureMesh(OPT::nResolutionLevel, OPT::nMinResolution, OPT::minCommonCameras, OPT::fOutlierThreshold, OPT::fRatioDataSmoothness,
 						   OPT::bGlobalSeamLeveling, OPT::bLocalSeamLeveling, OPT::nTextureSizeMultiple, OPT::nRectPackingHeuristic, Pixel8U(OPT::nColEmpty),
 						   OPT::fSharpnessWeight, OPT::nIgnoreMaskLabel, OPT::nMaxTextureSize, views, baseFileName, OPT::bOriginFaceview, 
-						   OPT::strInputFileName, OPT::strMeshFileName))
+						   OPT::strInputFileName, OPT::strMeshFileName, *pBExistVertexColor))
 		return EXIT_FAILURE;
 	VERBOSE("Mesh texturing completed: %u vertices, %u faces (%s)", scene.mesh.vertices.GetSize(), scene.mesh.faces.GetSize(), TD_TIMER_GET_FMT().c_str());
 

libs/Common/Util.inl

@@ -579,6 +579,16 @@ inline TPoint3<TYPE> ComputeTriangleNormal(const TPoint3<TYPE>& v0, const TPoint
 } // ComputeTriangleNormal
 /*----------------------------------------------------------------*/
 
+template<typename ColorType>
+ColorType ComputeTriangleColor(const ColorType& c0, const ColorType& c1, const ColorType& c2) {
+    // 手动计算每个通道的平均值
+    ColorType result;
+    result.r = static_cast<uint8_t>((static_cast<int>(c0.r) + c1.r + c2.r) / 3 + 0.5f); // 整数运算避免溢出
+    result.g = static_cast<uint8_t>((c0.g + c1.g + c2.g) / 3 + 0.5f);
+    result.b = static_cast<uint8_t>((c0.b + c1.b + c2.b) / 3 + 0.5f);
+    return result;
+}
+
 // compute the area of a triangle using Heron's formula
 template <typename TYPE>
 TYPE ComputeTriangleAreaSqLen(TYPE lena, TYPE lenb, TYPE lenc) {

libs/MVS/ColorComparisonFace.cpp

@@ -0,0 +1,767 @@
+#include "ColorComparisonFace.h"
+#include "Mesh.h"  // 在cpp中包含完整定义
+#include <opencv2/opencv.hpp>
+
+#include <cstdlib>
+#include <cstdio>
+#include <algorithm>
+#include <sys/stat.h>
+#include <iomanip>
+#include <sstream>
+
+using namespace MVS;
+
+// 辅助函数：检查目录是否存在
+static bool directoryExists(const std::string& path) {
+    struct stat info;
+    if (stat(path.c_str(), &info) != 0) {
+        return false;
+    }
+    return (info.st_mode & S_IFDIR) != 0;
+}
+
+// 辅助函数：创建目录
+static bool createDirectory(const std::string& path) {
+    #ifdef _WIN32
+        return _mkdir(path.c_str()) == 0;
+    #else
+        return mkdir(path.c_str(), 0755) == 0;
+    #endif
+}
+
+// 辅助函数：递归创建目录
+static bool createDirectories(const std::string& path) {
+    size_t pos = 0;
+    std::string dir;
+    
+    while ((pos = path.find_first_of("/\\", pos + 1)) != std::string::npos) {
+        dir = path.substr(0, pos);
+        if (!directoryExists(dir)) {
+            if (!createDirectory(dir)) {
+                return false;
+            }
+        }
+    }
+    
+    // 创建最终目录
+    if (!directoryExists(path)) {
+        return createDirectory(path);
+    }
+    
+    return true;
+}
+
+// 构造函数
+ColorComparisonFace::ColorComparisonFace(const std::string& dir) : outputDir(dir) {
+    // 确保输出目录以斜杠结尾
+    if (!outputDir.empty() && outputDir.back() != '/' && outputDir.back() != '\\') {
+        outputDir += '/';
+    }
+    
+    // 创建输出目录
+    if (!createDirectories(outputDir)) {
+        printf("⚠️ 无法创建目录: %s\n", outputDir.c_str());
+    } else {
+        printf("✅ 输出目录: %s\n", outputDir.c_str());
+    }
+}
+
+void ColorComparisonFace::addExactTriangleInfo(int faceId, 
+                            MeshColor gaussianColor, 
+                            MeshColor originalColor,
+                            const cv::Mat& triangleRegionWithAlpha,  // 带透明通道
+                            const cv::Mat& visualization,  // 可视化图像
+                            float colorDistance,
+                            float threshold,
+                            const std::string& filename) {
+    // 存储信息
+    FaceColorInfo info;
+    info.faceId = faceId;
+    info.gaussianColor = gaussianColor;
+    info.originalColor = originalColor;
+    info.triangleRegion = triangleRegionWithAlpha.clone();  // 带透明通道
+    info.visualization = visualization.clone();  // 可视化图像
+    info.colorDistance = colorDistance;
+    info.threshold = threshold;
+    info.filename = filename;
+       
+    faceViewColorMap[faceId][filename].push_back(info);
+    printf("addExactTriangleInfo faceId=%d\n", faceId);
+}
+
+// 获取总face数
+int ColorComparisonFace::getTotalFaces() const {
+    return faceViewColorMap.size();
+}
+
+// 获取总记录数
+int ColorComparisonFace::getTotalRecords() const {
+    int total = 0;
+    for (const auto& faceEntry : faceViewColorMap) {
+        for (const auto& viewEntry : faceEntry.second) {
+            total += viewEntry.second.size();
+        }
+    }
+    return total;
+}
+
+// 获取faceid列表
+std::vector<int> ColorComparisonFace::getFaceIds() const {
+    std::vector<int> faceIds;
+    for (const auto& faceEntry : faceViewColorMap) {
+        faceIds.push_back(faceEntry.first);
+    }
+    return faceIds;
+}
+
+// 创建三角形区域对比图
+void ColorComparisonFace::createBatchComparison(int maxBlocksPerRow, int maxFacesPerImage) {
+    if (faceViewColorMap.empty()) {
+        printf("⚠️ 没有颜色信息可生成\n");
+        return;
+    }
+    
+    printf("正在创建三角形区域对比图...\n");
+    printf("总face数: %zu\n", faceViewColorMap.size());
+    printf("总记录数: %d\n", getTotalRecords());
+    
+    // 块参数
+    int triangleSize = 200;        // 三角形区域显示大小
+    int colorBlockSize = 100;      // 颜色块大小
+    int blockMargin = 20;          // 块之间的边距
+    int infoHeight = 100;          // 信息区域高度
+    
+    // 限制处理的face数
+    int facesToProcess = std::min((int)faceViewColorMap.size(), maxFacesPerImage);
+    
+    // 处理前N个face
+    int faceCount = 0;
+    for (const auto& faceEntry : faceViewColorMap) {
+        if (faceCount >= facesToProcess) break;
+        
+        int faceId = faceEntry.first;
+        const auto& viewMap = faceEntry.second;
+        
+        printf("处理 face %d (%zu 个视图)...\n", faceId, viewMap.size());
+        
+        // 计算需要的行数和列数
+        int numBlocks = 0;
+        for (const auto& viewEntry : viewMap) {
+            numBlocks += viewEntry.second.size();
+        }
+        
+        int numCols = std::min(maxBlocksPerRow, numBlocks);
+        int numRows = (numBlocks + numCols - 1) / numCols;
+        
+        // 计算每个块的宽度和高度
+        int blockWidth = colorBlockSize + triangleSize + blockMargin * 3;
+        int blockHeight = triangleSize + blockMargin + infoHeight;
+        
+        // 图片总尺寸
+        int totalWidth = numCols * (blockWidth + blockMargin) + blockMargin;
+        int totalHeight = 60 + (numRows * (blockHeight + blockMargin)) + blockMargin;
+        
+        // 创建大图
+        cv::Mat faceImage(totalHeight, totalWidth, CV_8UC3, cv::Scalar(245, 245, 245));
+        
+        // 添加标题
+        std::string title = cv::format("Face %d - Triangle Region Comparison", faceId);
+        cv::putText(faceImage, title, 
+                    cv::Point(20, 30), 
+                    cv::FONT_HERSHEY_SIMPLEX, 0.8, cv::Scalar(0, 0, 0), 2);
+        
+        // 添加统计信息
+        int totalRecords = 0;
+        int needFixCount = 0;
+        for (const auto& viewEntry : viewMap) {
+            totalRecords += viewEntry.second.size();
+            for (const auto& info : viewEntry.second) {
+                if (info.colorDistance > info.threshold) needFixCount++;
+            }
+        }
+        
+        std::string stats = cv::format("Views: %zu, Records: %d, Need Fix: %d", 
+                                       viewMap.size(), totalRecords, needFixCount);
+        cv::putText(faceImage, stats, 
+                    cv::Point(20, 55), 
+                    cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0), 1);
+        
+        int blockIndex = 0;
+        int currentRow = 0;
+        int currentCol = 0;
+        
+        // 遍历这个face的所有视图
+        for (const auto& viewEntry : viewMap) {
+            const std::string& viewName = viewEntry.first;
+            const std::vector<FaceColorInfo>& infos = viewEntry.second;
+            
+            for (const auto& info : infos) {
+                // 计算当前块的位置
+                int blockX = blockMargin + currentCol * (blockWidth + blockMargin);
+                int blockY = 60 + blockMargin + currentRow * (blockHeight + blockMargin);
+                
+                // 绘制块背景
+                cv::rectangle(faceImage, 
+                            cv::Rect(blockX, blockY, blockWidth, blockHeight), 
+                            cv::Scalar(255, 255, 255), -1);
+                cv::rectangle(faceImage, 
+                            cv::Rect(blockX, blockY, blockWidth, blockHeight), 
+                            cv::Scalar(200, 200, 200), 2);
+                
+                // 绘制高斯颜色块
+                int gaussianX = blockX + blockMargin;
+                int gaussianY = blockY + blockMargin;
+                
+                cv::Scalar gaussianBGR(info.gaussianColor[2], info.gaussianColor[1], info.gaussianColor[0]);
+                cv::rectangle(faceImage, 
+                            cv::Rect(gaussianX, gaussianY, colorBlockSize, colorBlockSize), 
+                            gaussianBGR, -1);
+                cv::rectangle(faceImage, 
+                            cv::Rect(gaussianX, gaussianY, colorBlockSize, colorBlockSize), 
+                            cv::Scalar(0, 0, 0), 2);
+                
+                // 添加高斯标签
+                cv::putText(faceImage, "GAUSSIAN", 
+                           cv::Point(gaussianX + 10, gaussianY - 5), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0), 1);
+                
+                // 绘制三角形区域
+                int triangleX = blockX + blockMargin + colorBlockSize + blockMargin;
+                int triangleY = blockY + blockMargin;
+                
+                if (!info.visualization.empty()) {
+                    // 调整三角形区域大小
+                    cv::Mat resizedTriangle;
+                    cv::resize(info.visualization, resizedTriangle, cv::Size(triangleSize, triangleSize));
+                    
+                    // 将三角形区域绘制到指定位置（已经是RGB顺序）
+                    resizedTriangle.copyTo(faceImage(cv::Rect(triangleX, triangleY, triangleSize, triangleSize)));
+                    
+                    cv::rectangle(faceImage, 
+                                cv::Rect(triangleX, triangleY, triangleSize, triangleSize), 
+                                cv::Scalar(0, 0, 0), 2);
+                    
+                    // 添加三角形标签
+                    cv::putText(faceImage, "TRIANGLE", 
+                            cv::Point(triangleX + 10, triangleY - 5), 
+                            cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0), 1);
+                } else {
+                    // 如果没有三角形区域，绘制占位符
+                    cv::rectangle(faceImage, 
+                                cv::Rect(triangleX, triangleY, triangleSize, triangleSize), 
+                                cv::Scalar(200, 200, 200), -1);
+                    cv::rectangle(faceImage, 
+                                cv::Rect(triangleX, triangleY, triangleSize, triangleSize), 
+                                cv::Scalar(150, 150, 150), 2);
+                    
+                    cv::putText(faceImage, "NO TRIANGLE", 
+                               cv::Point(triangleX + triangleSize/2 - 40, triangleY + triangleSize/2), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(100, 100, 100), 1);
+                }
+                
+                // 绘制信息区域
+                int infoY = blockY + blockMargin + triangleSize;
+                cv::rectangle(faceImage, 
+                            cv::Rect(blockX, infoY, blockWidth, infoHeight), 
+                            cv::Scalar(240, 240, 240), -1);
+                cv::rectangle(faceImage, 
+                            cv::Rect(blockX, infoY, blockWidth, infoHeight), 
+                            cv::Scalar(200, 200, 200), 1);
+                
+                // 添加视图信息
+                std::string displayName = viewName;
+                if (displayName.length() > 20) {
+                    displayName = displayName.substr(0, 18) + "...";
+                }
+                
+                cv::putText(faceImage, cv::format("View: %s", displayName.c_str()), 
+                           cv::Point(blockX + 10, infoY + 20), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+                
+                cv::putText(faceImage, cv::format("Face: %d", info.faceId), 
+                           cv::Point(blockX + 10, infoY + 40), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+                
+                // 添加颜色值
+                cv::putText(faceImage, 
+                           cv::format("Gauss: (%d,%d,%d)", 
+                                     info.gaussianColor[0], info.gaussianColor[1], info.gaussianColor[2]),
+                           cv::Point(blockX + 10, infoY + 60), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+                
+                cv::putText(faceImage, 
+                           cv::format("Orgin: (%d,%d,%d)", 
+                                     info.originalColor[0], info.originalColor[1], info.originalColor[2]),
+                           cv::Point(blockX + 140, infoY + 60), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+
+                // 添加距离和阈值
+                cv::putText(faceImage, 
+                           cv::format("Distance: %.4f", info.colorDistance),
+                           cv::Point(blockX + 10, infoY + 80), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+                
+                cv::putText(faceImage, 
+                           cv::format("Threshold: %.4f", info.threshold),
+                           cv::Point(blockX + 10, infoY + 95), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+                
+                // 添加判断结果
+                int resultX = blockX + blockWidth - 60;
+                int resultY = infoY + 25;
+                
+                std::string resultText = (info.colorDistance > info.threshold) ? "FIX" : "OK";
+                cv::Scalar resultColor = (info.colorDistance > info.threshold) ? cv::Scalar(0, 0, 255) : cv::Scalar(0, 180, 0);
+                
+                cv::putText(faceImage, resultText, 
+                           cv::Point(resultX, resultY), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.5, resultColor, 1);
+                
+                // 更新行和列索引
+                blockIndex++;
+                currentCol++;
+                if (currentCol >= numCols) {
+                    currentCol = 0;
+                    currentRow++;
+                }
+                
+                // 如果已经达到最大块数，跳出循环
+                if (blockIndex >= maxBlocksPerRow * numRows) {
+                    break;
+                }
+            }
+            
+            // 如果已经达到最大块数，跳出循环
+            if (blockIndex >= maxBlocksPerRow * numRows) {
+                break;
+            }
+        }
+        
+        // 保存图片
+        std::string outputPath = outputDir + cv::format("face_%d_triangle_comparison.png", faceId);
+        
+        if (!cv::imwrite(outputPath, faceImage)) {
+            printf("❌❌ 无法保存face %d的三角形对比图: %s\n", faceId, outputPath.c_str());
+        } else {
+            printf("✅ face %d三角形对比图已保存: %s\n", faceId, outputPath.c_str());
+            printf("   尺寸: %d x %d 像素, 视图数: %zu, 记录数: %d\n", 
+                   totalWidth, totalHeight, viewMap.size(), totalRecords);
+        }
+        
+        faceCount++;
+    }
+    
+    // 保存颜色信息到CSV文件
+    saveColorInfoToFile();
+}
+
+// 保存颜色信息到CSV文件
+void ColorComparisonFace::saveColorInfoToFile() {
+    // 为每个face保存单独的CSV
+    for (const auto& faceEntry : faceViewColorMap) {
+        int faceId = faceEntry.first;
+        const auto& viewMap = faceEntry.second;
+        
+        if (viewMap.empty()) {
+            continue;
+        }
+        
+        std::string filePath = outputDir + cv::format("face_%d_triangle_colors.csv", faceId);
+        FILE* fp = fopen(filePath.c_str(), "w");
+        
+        if (!fp) {
+            printf("❌❌ 无法创建文件: %s\n", filePath.c_str());
+            continue;
+        }
+        
+        // 写入CSV标题
+        fprintf(fp, "FaceID,View,Gaussian_R,Gaussian_G,Gaussian_B,Distance,Threshold,NeedsFix\n");
+        
+        for (const auto& viewEntry : viewMap) {
+            const std::string& viewName = viewEntry.first;
+            const std::vector<FaceColorInfo>& infos = viewEntry.second;
+            
+            for (int i = 0; i < (int)infos.size(); i++) {
+                const FaceColorInfo& info = infos[i];
+                bool needsFix = (info.colorDistance > info.threshold);
+                fprintf(fp, "%d,%s,%d,%d,%d,%.4f,%.4f,%s\n",
+                        faceId,
+                        viewName.c_str(),
+                        info.gaussianColor[0], info.gaussianColor[1], info.gaussianColor[2],
+                        info.colorDistance, info.threshold,
+                        needsFix ? "YES" : "NO");
+            }
+        }
+        
+        fclose(fp);
+        printf("✅ face %d三角形颜色信息已保存到: %s\n", faceId, filePath.c_str());
+    }
+    
+    // 保存汇总统计信息
+    std::string summaryPath = outputDir + "triangle_comparison_summary.csv";
+    FILE* summaryFp = fopen(summaryPath.c_str(), "w");
+    
+    if (summaryFp) {
+        fprintf(summaryFp, "FaceID,Views,TotalRecords,NeedFixRecords,NeedFix%%,MinDistance,MaxDistance,AvgDistance\n");
+        
+        for (const auto& faceEntry : faceViewColorMap) {
+            int faceId = faceEntry.first;
+            const auto& viewMap = faceEntry.second;
+            
+            int totalRecords = 0;
+            int needFixCount = 0;
+            float minDist = std::numeric_limits<float>::max();
+            float maxDist = 0.0f;
+            float sumDist = 0.0f;
+            
+            for (const auto& viewEntry : viewMap) {
+                const std::vector<FaceColorInfo>& infos = viewEntry.second;
+                totalRecords += infos.size();
+                
+                for (const auto& info : infos) {
+                    if (info.colorDistance > info.threshold) needFixCount++;
+                    minDist = std::min(minDist, info.colorDistance);
+                    maxDist = std::max(maxDist, info.colorDistance);
+                    sumDist += info.colorDistance;
+                }
+            }
+            
+            float avgDist = (totalRecords > 0) ? (sumDist / totalRecords) : 0.0f;
+            float fixPercentage = (totalRecords > 0) ? (needFixCount * 100.0f / totalRecords) : 0.0f;
+            
+            fprintf(summaryFp, "%d,%zu,%d,%d,%.2f%%,%.4f,%.4f,%.4f\n",
+                    faceId,
+                    viewMap.size(),
+                    totalRecords,
+                    needFixCount,
+                    fixPercentage,
+                    minDist,
+                    maxDist,
+                    avgDist);
+        }
+        
+        fclose(summaryFp);
+        printf("✅ 三角形汇总统计信息已保存到: %s\n", summaryPath.c_str());
+    }
+}
+
+// 在ColorComparisonFace.cpp中添加以下函数实现
+
+// 添加连续区域信息
+void ColorComparisonFace::addContinuousRegionInfo(int regionId,
+                                                const std::set<unsigned int>& faceIds,  // 修改为 unsigned int
+                                                MeshColor regionGaussianColor) {
+    if (continuousRegions.find(regionId) == continuousRegions.end()) {
+        ContinuousRegionInfo regionInfo;
+        regionInfo.regionId = regionId;
+        regionInfo.faceIds = faceIds;  // 这里类型匹配
+        regionInfo.regionGaussianColor = regionGaussianColor;
+        regionInfo.totalPixels = 0;
+        continuousRegions[regionId] = regionInfo;
+        
+        printf("添加连续区域 %d: 包含 %zu 个面\n", regionId, faceIds.size());
+    }
+}
+
+// 添加连续区域在特定视图中的信息
+void ColorComparisonFace::addRegionViewInfo(int regionId,
+                                          const std::string& filename,
+                                          MeshColor viewColor,
+                                          const cv::Mat& regionImage,
+                                          const cv::Mat& visualization,
+                                          float colorDistance) {
+    if (continuousRegions.find(regionId) != continuousRegions.end()) {
+        ContinuousRegionInfo& regionInfo = continuousRegions[regionId];
+        regionInfo.viewColors[filename] = viewColor;
+        regionInfo.viewRegions[filename] = regionImage.clone();
+        regionInfo.viewVisualizations[filename] = visualization.clone();
+        regionInfo.viewDistances[filename] = colorDistance;
+        
+        printf("  视图 %s: 颜色(R=%d,G=%d,B=%d), 距离=%.4f\n", 
+               filename.c_str(), viewColor.r, viewColor.g, viewColor.b, colorDistance);
+    }
+}
+
+// 获取连续区域数
+int ColorComparisonFace::getTotalRegions() const {
+    return continuousRegions.size();
+}
+
+// 创建连续区域跨视图比较图
+void ColorComparisonFace::createContinuousRegionComparison(int maxBlocksPerRow, int maxRegionsPerImage) {
+    if (continuousRegions.empty()) {
+        printf("⚠️ 没有连续区域信息可生成\n");
+        return;
+    }
+    
+    printf("正在创建连续区域跨视图比较图...\n");
+    printf("总连续区域数: %zu\n", continuousRegions.size());
+    
+    // 限制处理的区域数
+    int regionsToProcess = std::min((int)continuousRegions.size(), maxRegionsPerImage);
+    
+    // 处理前N个区域
+    int regionCount = 0;
+    for (const auto& regionEntry : continuousRegions) {
+        if (regionCount >= regionsToProcess) break;
+        
+        int regionId = regionEntry.first;
+        const ContinuousRegionInfo& regionInfo = regionEntry.second;
+        
+        printf("处理连续区域 %d: 在 %zu 个视图中可见\n", regionId, regionInfo.viewColors.size());
+        
+        if (regionInfo.viewColors.size() < 2) {
+            printf("  区域 %d 在少于2个视图中可见，跳过跨视图比较\n", regionId);
+            regionCount++;
+            continue;
+        }
+        
+        // 块参数
+        int regionSize = 200;        // 区域显示大小
+        int colorBlockSize = 100;    // 颜色块大小
+        int blockMargin = 20;        // 块之间的边距
+        int infoHeight = 120;        // 信息区域高度
+        
+        // 计算需要的行数和列数
+        int numBlocks = regionInfo.viewColors.size();
+        int numCols = std::min(maxBlocksPerRow, numBlocks);
+        int numRows = (numBlocks + numCols - 1) / numCols;
+        
+        // 计算每个块的宽度和高度
+        int blockWidth = colorBlockSize + regionSize + blockMargin * 3;
+        int blockHeight = regionSize + blockMargin + infoHeight;
+        
+        // 图片总尺寸
+        int totalWidth = numCols * (blockWidth + blockMargin) + blockMargin;
+        int totalHeight = 100 + (numRows * (blockHeight + blockMargin)) + blockMargin;
+        
+        // 创建大图
+        cv::Mat regionImage(totalHeight, totalWidth, CV_8UC3, cv::Scalar(240, 240, 240));
+        
+        // 添加标题
+        std::string title = cv::format("Continuous Region %d - Cross-View Comparison", regionId);
+        cv::putText(regionImage, title, 
+                    cv::Point(20, 30), 
+                    cv::FONT_HERSHEY_SIMPLEX, 1.0, cv::Scalar(0, 0, 0), 2);
+        
+        // 添加区域统计信息
+        std::string regionStats = cv::format("Contains %zu faces, Visible in %zu views", 
+                                           regionInfo.faceIds.size(), regionInfo.viewColors.size());
+        cv::putText(regionImage, regionStats, 
+                    cv::Point(20, 60), 
+                    cv::FONT_HERSHEY_SIMPLEX, 0.6, cv::Scalar(0, 0, 0), 1);
+        
+        std::string gaussStats = cv::format("Region Gaussian Color: R=%d, G=%d, B=%d", 
+                                          regionInfo.regionGaussianColor.r,
+                                          regionInfo.regionGaussianColor.g,
+                                          regionInfo.regionGaussianColor.b);
+        cv::putText(regionImage, gaussStats, 
+                    cv::Point(20, 85), 
+                    cv::FONT_HERSHEY_SIMPLEX, 0.6, cv::Scalar(255, 0, 0), 1);
+        
+        int blockIndex = 0;
+        int currentRow = 0;
+        int currentCol = 0;
+        
+        // 计算统计数据
+        float sumDistances = 0.0f;
+        float maxDistance = 0.0f;
+        std::string worstView;
+        
+        // 遍历这个区域的所有视图
+        for (const auto& viewEntry : regionInfo.viewColors) {
+            const std::string& viewName = viewEntry.first;
+            const MeshColor& viewColor = viewEntry.second;
+            float colorDistance = regionInfo.viewDistances.at(viewName);
+            
+            sumDistances += colorDistance;
+            if (colorDistance > maxDistance) {
+                maxDistance = colorDistance;
+                worstView = viewName;
+            }
+            
+            // 计算当前块的位置
+            int blockX = blockMargin + currentCol * (blockWidth + blockMargin);
+            int blockY = 100 + blockMargin + currentRow * (blockHeight + blockMargin);
+            
+            // 绘制块背景
+            cv::rectangle(regionImage, 
+                        cv::Rect(blockX, blockY, blockWidth, blockHeight), 
+                        cv::Scalar(255, 255, 255), -1);
+            cv::rectangle(regionImage, 
+                        cv::Rect(blockX, blockY, blockWidth, blockHeight), 
+                        cv::Scalar(200, 200, 200), 2);
+            
+            // 绘制区域高斯颜色块
+            int gaussianX = blockX + blockMargin;
+            int gaussianY = blockY + blockMargin;
+            
+            cv::Scalar gaussianBGR(regionInfo.regionGaussianColor[2], 
+                                 regionInfo.regionGaussianColor[1], 
+                                 regionInfo.regionGaussianColor[0]);
+            cv::rectangle(regionImage, 
+                        cv::Rect(gaussianX, gaussianY, colorBlockSize, colorBlockSize), 
+                        gaussianBGR, -1);
+            cv::rectangle(regionImage, 
+                        cv::Rect(gaussianX, gaussianY, colorBlockSize, colorBlockSize), 
+                        cv::Scalar(0, 0, 0), 2);
+            
+            // 添加高斯标签
+            cv::putText(regionImage, "REGION GAUSS", 
+                       cv::Point(gaussianX + 5, gaussianY - 5), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+            
+            // 绘制区域图像块
+            int regionX = blockX + blockMargin + colorBlockSize + blockMargin;
+            int regionY = blockY + blockMargin;
+            
+            auto visIt = regionInfo.viewVisualizations.find(viewName);
+            if (visIt != regionInfo.viewVisualizations.end() && !visIt->second.empty()) {
+                cv::Mat resizedRegion;
+                cv::resize(visIt->second, resizedRegion, cv::Size(regionSize, regionSize));
+                
+                // 将区域图像绘制到指定位置
+                resizedRegion.copyTo(regionImage(cv::Rect(regionX, regionY, regionSize, regionSize)));
+                
+                cv::rectangle(regionImage, 
+                            cv::Rect(regionX, regionY, regionSize, regionSize), 
+                            cv::Scalar(0, 0, 0), 2);
+                
+                // 添加视图标签
+                cv::putText(regionImage, "VIEW REGION", 
+                           cv::Point(regionX + 5, regionY - 5), 
+                           cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+            }
+            
+            // 绘制信息区域
+            int infoY = blockY + blockMargin + regionSize;
+            cv::rectangle(regionImage, 
+                        cv::Rect(blockX, infoY, blockWidth, infoHeight), 
+                        cv::Scalar(240, 240, 240), -1);
+            cv::rectangle(regionImage, 
+                        cv::Rect(blockX, infoY, blockWidth, infoHeight), 
+                        cv::Scalar(200, 200, 200), 1);
+            
+            // 添加视图信息
+            std::string displayName = viewName;
+            if (displayName.length() > 20) {
+                displayName = displayName.substr(0, 18) + "...";
+            }
+            
+            cv::putText(regionImage, cv::format("View: %s", displayName.c_str()), 
+                       cv::Point(blockX + 10, infoY + 20), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+            
+            cv::putText(regionImage, cv::format("Region: %d", regionId), 
+                       cv::Point(blockX + 10, infoY + 40), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+            
+            // 添加颜色值
+            cv::putText(regionImage, 
+                       cv::format("Region Gauss: (%d,%d,%d)", 
+                                 regionInfo.regionGaussianColor[0], 
+                                 regionInfo.regionGaussianColor[1], 
+                                 regionInfo.regionGaussianColor[2]),
+                       cv::Point(blockX + 10, infoY + 60), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+            
+            cv::putText(regionImage, 
+                       cv::format("View Color: (%d,%d,%d)", 
+                                 viewColor[0], viewColor[1], viewColor[2]),
+                       cv::Point(blockX + 10, infoY + 80), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+            
+            // 添加距离和阈值
+            cv::putText(regionImage, 
+                       cv::format("Distance: %.4f", colorDistance),
+                       cv::Point(blockX + 10, infoY + 100), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+            
+            // 添加判断结果
+            int resultX = blockX + blockWidth - 50;
+            int resultY = infoY + 30;
+            
+            std::string resultText = (colorDistance > 0.31f) ? "FIX" : "OK";
+            cv::Scalar resultColor = (colorDistance > 0.31f) ? cv::Scalar(0, 0, 255) : cv::Scalar(0, 180, 0);
+            
+            cv::putText(regionImage, resultText, 
+                       cv::Point(resultX, resultY), 
+                       cv::FONT_HERSHEY_SIMPLEX, 0.6, resultColor, 1);
+            
+            // 更新行和列索引
+            blockIndex++;
+            currentCol++;
+            if (currentCol >= numCols) {
+                currentCol = 0;
+                currentRow++;
+            }
+        }
+        
+        // 在底部添加统计信息
+        float avgDistance = sumDistances / regionInfo.viewColors.size();
+        std::string stats = cv::format("Avg Distance: %.4f, Max Distance: %.4f (in %s)", 
+                                      avgDistance, maxDistance, worstView.c_str());
+        cv::putText(regionImage, stats, 
+                   cv::Point(20, totalHeight - 20), 
+                   cv::FONT_HERSHEY_SIMPLEX, 0.6, cv::Scalar(0, 0, 0), 1);
+        
+        // 保存图片
+        std::string outputPath = outputDir + cv::format("continuous_region_%d_comparison.png", regionId);
+        
+        if (!cv::imwrite(outputPath, regionImage)) {
+            printf("❌❌ 无法保存连续区域 %d 的对比图: %s\n", regionId, outputPath.c_str());
+        } else {
+            printf("✅ 连续区域 %d 对比图已保存: %s\n", regionId, outputPath.c_str());
+        }
+        
+        regionCount++;
+    }
+    
+    // 保存连续区域信息到CSV文件
+    std::string regionSummaryPath = outputDir + "continuous_regions_summary.csv";
+    FILE* regionFp = fopen(regionSummaryPath.c_str(), "w");
+    
+    if (regionFp) {
+        fprintf(regionFp, "RegionID,FaceCount,Views,AvgDistance,MaxDistance,WorstView,NeedsFixCount,NeedsFix%%\n");
+        
+        for (const auto& regionEntry : continuousRegions) {
+            int regionId = regionEntry.first;
+            const ContinuousRegionInfo& regionInfo = regionEntry.second;
+            
+            float sumDist = 0.0f;
+            float maxDist = 0.0f;
+            int needsFixCount = 0;
+            
+            for (const auto& distEntry : regionInfo.viewDistances) {
+                float dist = distEntry.second;
+                sumDist += dist;
+                if (dist > maxDist) maxDist = dist;
+                if (dist > 0.31f) needsFixCount++;
+            }
+            
+            float avgDist = (regionInfo.viewDistances.size() > 0) ? 
+                           (sumDist / regionInfo.viewDistances.size()) : 0.0f;
+            float fixPercentage = (regionInfo.viewDistances.size() > 0) ? 
+                                 (needsFixCount * 100.0f / regionInfo.viewDistances.size()) : 0.0f;
+            
+            fprintf(regionFp, "%d,%zu,%zu,%.4f,%.4f,", 
+                    regionId, regionInfo.faceIds.size(), regionInfo.viewDistances.size(),
+                    avgDist, maxDist);
+            
+            // 找到最差的视图
+            std::string worstView = "";
+            for (const auto& distEntry : regionInfo.viewDistances) {
+                if (distEntry.second == maxDist) {
+                    worstView = distEntry.first;
+                    break;
+                }
+            }
+            
+            fprintf(regionFp, "%s,%d,%.2f%%\n",
+                    worstView.c_str(), needsFixCount, fixPercentage);
+        }
+        
+        fclose(regionFp);
+        printf("✅ 连续区域汇总统计信息已保存到: %s\n", regionSummaryPath.c_str());
+    }
+}

libs/MVS/ColorComparisonFace.h

@@ -0,0 +1,112 @@
+#ifndef COLORCOMPARISONBFACE_H
+#define COLORCOMPARISONBFACE_H
+
+#include <string>
+#include <vector>
+#include <map>
+#include <set>
+#include <opencv2/opencv.hpp>
+
+// 不使用前向声明，直接定义简单的颜色结构
+struct MeshColor {
+    unsigned char r, g, b;
+    
+    MeshColor() : r(0), g(0), b(0) {}
+    MeshColor(unsigned char r, unsigned char g, unsigned char b) 
+        : r(r), g(g), b(b) {}
+    
+    unsigned char operator[](size_t idx) const {
+        if (idx == 0) return r;
+        if (idx == 1) return g;
+        if (idx == 2) return b;
+        return 0;
+    }
+};
+
+class ColorComparisonFace {
+private:
+    // 单面信息结构
+    struct FaceColorInfo {
+        int faceId;                       // 面的ID
+        MeshColor gaussianColor;          // 高斯颜色
+        MeshColor originalColor;          // 原始颜色
+        cv::Mat triangleRegion;           // 带透明通道的三角形区域
+        cv::Mat visualization;            // 三角形可视化图像
+        float colorDistance;              // 颜色距离
+        float threshold;                  // 阈值
+        std::string filename;             // 文件名
+    };
+    
+    // 连续区域信息结构
+    struct ContinuousRegionInfo {
+        int regionId;                     // 区域ID
+        std::set<unsigned int> faceIds;   // 修改为 unsigned int
+        MeshColor regionGaussianColor;    // 区域的整体高斯颜色
+        std::map<std::string, MeshColor> viewColors;  // 每个视图的颜色
+        std::map<std::string, cv::Mat> viewRegions;   // 每个视图的区域图像
+        std::map<std::string, cv::Mat> viewVisualizations;  // 每个视图的可视化
+        std::map<std::string, float> viewDistances;   // 每个视图的距离
+        int totalPixels;                  // 区域总像素数
+    };
+
+    // 使用嵌套map: faceid -> filename -> FaceColorInfo列表
+    std::map<int, std::map<std::string, std::vector<FaceColorInfo>>> faceViewColorMap;
+    
+    // 连续区域映射: regionId -> ContinuousRegionInfo
+    std::map<int, ContinuousRegionInfo> continuousRegions;
+    
+    std::string outputDir;
+    
+public:
+    // 构造函数
+    ColorComparisonFace(const std::string& dir);
+    
+    // 析构函数
+    virtual ~ColorComparisonFace() {}
+    
+    // 添加精确三角形信息（替代原来的addColorInfo）
+    void addExactTriangleInfo(int faceId, 
+                            MeshColor gaussianColor, 
+                            MeshColor originalColor,
+                            const cv::Mat& triangleRegionWithAlpha,  // 带透明通道
+                            const cv::Mat& visualization,  // 可视化图像
+                            float colorDistance,
+                            float threshold,
+                            const std::string& filename);
+    
+    // 添加连续区域信息
+    void addContinuousRegionInfo(int regionId,
+                            const std::set<unsigned int>& faceIds,  // 修改为 unsigned int
+                            MeshColor regionGaussianColor);
+    
+    // 添加连续区域在特定视图中的信息
+    void addRegionViewInfo(int regionId,
+                          const std::string& filename,
+                          MeshColor viewColor,
+                          const cv::Mat& regionImage,
+                          const cv::Mat& visualization,
+                          float colorDistance);
+    
+    // 创建三角形区域对比图
+    void createBatchComparison(int maxBlocksPerRow = 6, int maxFacesPerImage = 20);
+    
+    // 创建连续区域跨视图比较图
+    void createContinuousRegionComparison(int maxBlocksPerRow = 6, int maxRegionsPerImage = 20);
+    
+    // 保存颜色信息到CSV文件
+    void saveColorInfoToFile();
+    
+    // 获取总face数
+    int getTotalFaces() const;
+    
+    // 获取总记录数
+    int getTotalRecords() const;
+    
+    // 获取faceid列表
+    std::vector<int> getFaceIds() const;
+    
+    // 获取连续区域数
+    int getTotalRegions() const;
+};
+
+#endif // COLORCOMPARISONBFACE_H

libs/MVS/ColorComparisonPixel.cpp

@@ -0,0 +1,505 @@
+#include "ColorComparisonPixel.h"
+#include "Mesh.h"  // 在cpp中包含完整定义
+#include <opencv2/opencv.hpp>
+
+#include <cstdlib>
+#include <cstdio>
+#include <algorithm>
+#include <sys/stat.h>
+#include <iomanip>
+#include <sstream>
+
+using namespace MVS;
+
+// 辅助函数：检查目录是否存在
+static bool directoryExists(const std::string& path) {
+    struct stat info;
+    if (stat(path.c_str(), &info) != 0) {
+        return false;
+    }
+    return (info.st_mode & S_IFDIR) != 0;
+}
+
+// 辅助函数：创建目录
+static bool createDirectory(const std::string& path) {
+    #ifdef _WIN32
+        return _mkdir(path.c_str()) == 0;
+    #else
+        return mkdir(path.c_str(), 0755) == 0;
+    #endif
+}
+
+// 辅助函数：递归创建目录
+static bool createDirectories(const std::string& path) {
+    size_t pos = 0;
+    std::string dir;
+    
+    while ((pos = path.find_first_of("/\\", pos + 1)) != std::string::npos) {
+        dir = path.substr(0, pos);
+        if (!directoryExists(dir)) {
+            if (!createDirectory(dir)) {
+                return false;
+            }
+        }
+    }
+    
+    // 创建最终目录
+    if (!directoryExists(path)) {
+        return createDirectory(path);
+    }
+    
+    return true;
+}
+
+// 构造函数
+ColorComparisonPixel::ColorComparisonPixel(const std::string& dir) : outputDir(dir) {
+    // 确保输出目录以斜杠结尾
+    if (!outputDir.empty() && outputDir.back() != '/' && outputDir.back() != '\\') {
+        outputDir += '/';
+    }
+    
+    // 创建输出目录
+    if (!createDirectories(outputDir)) {
+        printf("⚠️ 无法创建目录: %s\n", outputDir.c_str());
+    } else {
+        printf("✅ 输出目录: %s\n", outputDir.c_str());
+    }
+}
+
+// 添加颜色信息
+void ColorComparisonPixel::addColorInfo(int faceId, 
+                     const MeshColor& gaussianColor, 
+                     const MeshColor& originalColor,
+                     float distance, float threshold,
+                     const std::string& filename) {
+    ColorInfo info = {faceId, gaussianColor, originalColor, distance, threshold, filename};
+    faceViewColorMap[faceId][filename].push_back(info);
+}
+
+// 获取总face数
+int ColorComparisonPixel::getTotalFaces() const {
+    return faceViewColorMap.size();
+}
+
+// 获取总记录数
+int ColorComparisonPixel::getTotalRecords() const {
+    int total = 0;
+    for (const auto& faceEntry : faceViewColorMap) {
+        for (const auto& viewEntry : faceEntry.second) {
+            total += viewEntry.second.size();
+        }
+    }
+    return total;
+}
+
+// 获取faceid列表
+std::vector<int> ColorComparisonPixel::getFaceIds() const {
+    std::vector<int> faceIds;
+    for (const auto& faceEntry : faceViewColorMap) {
+        faceIds.push_back(faceEntry.first);
+    }
+    return faceIds;
+}
+
+// 创建按faceid分组的对比图
+void ColorComparisonPixel::createBatchComparison(int maxCellsPerRow, int maxFacesPerImage) {
+    if (faceViewColorMap.empty()) {
+        printf("⚠️ 没有颜色信息可生成\n");
+        return;
+    }
+    
+    printf("正在创建按faceid分组的对比图...\n");
+    printf("总face数: %zu\n", faceViewColorMap.size());
+    printf("总记录数: %d\n", getTotalRecords());
+    
+    // 单元格参数
+    int cellWidth = 220;    // 每个单元格宽度
+    int cellHeight = 150;   // 每个单元格高度
+    int cellMargin = 5;     // 单元格边距
+    
+    // 左侧视图名称区域宽度
+    int viewNameWidth = 200;
+    
+    // 限制处理的face数
+    int facesToProcess = std::min((int)faceViewColorMap.size(), maxFacesPerImage);
+    
+    // 处理前N个face
+    int faceCount = 0;
+    for (const auto& faceEntry : faceViewColorMap) {
+        if (faceCount >= facesToProcess) break;
+        
+        int faceId = faceEntry.first;
+        const auto& viewMap = faceEntry.second;
+        
+        printf("处理 face %d (%zu 个视图)...\n", faceId, viewMap.size());
+        
+        // 计算这个face需要的总行数
+        int totalRows = 0;
+        std::vector<std::pair<std::string, int>> viewRowsInfo; // 存储每个视图需要的行数
+        
+        for (const auto& viewEntry : viewMap) {
+            const std::string& viewName = viewEntry.first;
+            const std::vector<ColorInfo>& infos = viewEntry.second;
+            
+            // 计算这个视图需要的行数
+            int rowsForThisView = (infos.size() + maxCellsPerRow - 1) / maxCellsPerRow;
+            viewRowsInfo.emplace_back(viewName, rowsForThisView);
+            totalRows += rowsForThisView;
+        }
+        
+        if (totalRows == 0) continue;
+        
+        // 图片总尺寸
+        int totalWidth = viewNameWidth + (maxCellsPerRow * cellWidth);
+        int totalHeight = 60 + (totalRows * cellHeight);  // 60像素用于标题
+        
+        // 创建大图
+        cv::Mat faceImage(totalHeight, totalWidth, CV_8UC3, cv::Scalar(245, 245, 245));
+        
+        // 添加标题
+        std::string title = cv::format("Face %d - Color Comparison", faceId);
+        cv::putText(faceImage, title, 
+                    cv::Point(20, 30), 
+                    cv::FONT_HERSHEY_SIMPLEX, 0.8, cv::Scalar(0, 0, 0), 2);
+        
+        // 添加统计信息
+        int totalRecords = 0;
+        int needFixCount = 0;
+        for (const auto& viewEntry : viewMap) {
+            totalRecords += viewEntry.second.size();
+            for (const auto& info : viewEntry.second) {
+                if (info.distance > info.threshold) needFixCount++;
+            }
+        }
+        
+        std::string stats = cv::format("Views: %zu, Records: %d, Need Fix: %d", 
+                                       viewMap.size(), totalRecords, needFixCount);
+        cv::putText(faceImage, stats, 
+                    cv::Point(20, 55), 
+                    cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0), 1);
+        
+        int currentGlobalRow = 0;  // 全局行索引
+        
+        // 遍历这个face的所有视图
+        for (const auto& viewRowPair : viewRowsInfo) {
+            const std::string& viewName = viewRowPair.first;
+            int rowsForThisView = viewRowPair.second;
+            const std::vector<ColorInfo>& infos = viewMap.at(viewName);
+            
+            // 为这个视图的每一行绘制
+            for (int viewRow = 0; viewRow < rowsForThisView; viewRow++) {
+                int globalRowY = 60 + (currentGlobalRow * cellHeight);
+                
+                // 绘制视图名称区域（只在第一行显示）
+                cv::rectangle(faceImage, 
+                            cv::Rect(0, globalRowY, viewNameWidth, cellHeight), 
+                            cv::Scalar(255, 255, 255), -1);
+                cv::rectangle(faceImage, 
+                            cv::Rect(0, globalRowY, viewNameWidth, cellHeight), 
+                            cv::Scalar(200, 200, 200), 1);
+                
+                if (viewRow == 0) {
+                    // 第一行：显示完整视图信息
+                    cv::putText(faceImage, viewName, 
+                               cv::Point(10, globalRowY + 25), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0), 1);
+                    
+                    std::string countText = cv::format("Records: %zu", infos.size());
+                    cv::putText(faceImage, countText, 
+                               cv::Point(10, globalRowY + 50), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(100, 100, 100), 1);
+                    
+                    // 计算这个视图中需要修复的记录数
+                    int viewNeedFixCount = 0;
+                    for (const auto& info : infos) {
+                        if (info.distance > info.threshold) viewNeedFixCount++;
+                    }
+                    
+                    if (viewNeedFixCount > 0) {
+                        std::string fixText = cv::format("Fix: %d", viewNeedFixCount);
+                        cv::Scalar fixColor = cv::Scalar(0, 0, 255);
+                        cv::putText(faceImage, fixText, 
+                                   cv::Point(10, globalRowY + 70), 
+                                   cv::FONT_HERSHEY_SIMPLEX, 0.4, fixColor, 1);
+                    }
+                } else {
+                    // 后续行：显示视图名称缩写和行号
+                    std::string continuationText = cv::format("%s (cont.)", viewName.substr(0, 8).c_str());
+                    cv::putText(faceImage, continuationText, 
+                               cv::Point(10, globalRowY + 25), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(100, 100, 100), 1);
+                    
+                    std::string rowText = cv::format("Row %d/%d", viewRow + 1, rowsForThisView);
+                    cv::putText(faceImage, rowText, 
+                               cv::Point(10, globalRowY + 50), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(100, 100, 100), 1);
+                }
+                
+                // 计算这一行要显示的记录
+                int startIndex = viewRow * maxCellsPerRow;
+                int endIndex = std::min(startIndex + maxCellsPerRow, (int)infos.size());
+                
+                // 绘制这一行的单元格
+                for (int col = 0; col < (endIndex - startIndex); col++) {
+                    int infoIndex = startIndex + col;
+                    const ColorInfo& info = infos[infoIndex];
+                    
+                    // 计算单元格位置
+                    int cellX = viewNameWidth + (col * cellWidth);
+                    int cellY = globalRowY;
+                    
+                    // 绘制单个单元格
+                    int innerX = cellX + cellMargin;
+                    int innerY = cellY + cellMargin;
+                    int innerWidth = cellWidth - 2 * cellMargin;
+                    int innerHeight = cellHeight - 2 * cellMargin;
+                    
+                    // 创建单元格背景
+                    cv::rectangle(faceImage, 
+                                 cv::Rect(cellX, cellY, cellWidth, cellHeight), 
+                                 cv::Scalar(255, 255, 255), -1);
+                    cv::rectangle(faceImage, 
+                                 cv::Rect(cellX, cellY, cellWidth, cellHeight), 
+                                 cv::Scalar(200, 200, 200), 1);
+                    
+                    // 颜色块参数
+                    int colorBlockSize = 35;
+                    int colorBlockY = innerY + 10;
+                    
+                    // 绘制高斯颜色块
+                    cv::Scalar gaussianBGR(info.gaussianColor[2], info.gaussianColor[1], info.gaussianColor[0]);
+                    cv::rectangle(faceImage, 
+                                 cv::Point(innerX + 5, colorBlockY), 
+                                 cv::Point(innerX + 5 + colorBlockSize, colorBlockY + colorBlockSize), 
+                                 gaussianBGR, -1);
+                    
+                    // 绘制原始颜色块
+                    cv::Scalar originalBGR(info.originalColor[2], info.originalColor[1], info.originalColor[0]);
+                    cv::rectangle(faceImage, 
+                                 cv::Point(innerX + 5 + colorBlockSize + 35, colorBlockY), 
+                                 cv::Point(innerX + 5 + colorBlockSize + 35 + colorBlockSize, colorBlockY + colorBlockSize), 
+                                 originalBGR, -1);
+                    
+                    // 添加边框
+                    cv::rectangle(faceImage, 
+                                 cv::Point(innerX + 5, colorBlockY), 
+                                 cv::Point(innerX + 5 + colorBlockSize, colorBlockY + colorBlockSize), 
+                                 cv::Scalar(0, 0, 0), 1);
+                    
+                    cv::rectangle(faceImage, 
+                                 cv::Point(innerX + 5 + colorBlockSize + 35, colorBlockY), 
+                                 cv::Point(innerX + 5 + colorBlockSize + 35 + colorBlockSize, colorBlockY + colorBlockSize), 
+                                 cv::Scalar(0, 0, 0), 1);
+                    
+                    // 添加标签
+                    int labelY = colorBlockY - 5;
+                    cv::putText(faceImage, "G", 
+                               cv::Point(innerX + 5 + 10, labelY), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+                    
+                    cv::putText(faceImage, "O", 
+                               cv::Point(innerX + 5 + colorBlockSize + 35 + 10, labelY), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.4, cv::Scalar(0, 0, 0), 1);
+                    
+                    // 添加颜色值（简化显示）
+                    std::string gValue = cv::format("%d,%d,%d", 
+                                                    info.gaussianColor[0], info.gaussianColor[1], info.gaussianColor[2]);
+                    cv::putText(faceImage, gValue, 
+                               cv::Point(innerX + 5, innerY + 60), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.3, cv::Scalar(0, 0, 0), 1);
+                    
+                    std::string oValue = cv::format("%d,%d,%d", 
+                                                    info.originalColor[0], info.originalColor[1], info.originalColor[2]);
+                    cv::putText(faceImage, oValue, 
+                               cv::Point(innerX + 5 + colorBlockSize + 35, innerY + 60), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.3, cv::Scalar(0, 0, 0), 1);
+                    
+                    // 添加距离
+                    std::string distText = cv::format("D:%.3f", info.distance);
+                    cv::putText(faceImage, distText, 
+                               cv::Point(innerX + 5, innerY + 75), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+                    
+                    // 添加阈值
+                    std::string threshText = cv::format("T:%.3f", info.threshold);
+                    cv::putText(faceImage, threshText, 
+                               cv::Point(innerX + 5 + colorBlockSize + 35, innerY + 75), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.35, cv::Scalar(0, 0, 0), 1);
+                    
+                    // 添加判断结果
+                    std::string resultText = (info.distance > info.threshold) ? "FIX" : "OK";
+                    cv::Scalar resultColor = (info.distance > info.threshold) ? cv::Scalar(0, 0, 255) : cv::Scalar(0, 180, 0);
+                    
+                    cv::putText(faceImage, resultText, 
+                               cv::Point(innerX + 5, innerY + 90), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.4, resultColor, 1);
+                    
+                    // 添加记录序号
+                    std::string seqText = cv::format("#%d", infoIndex + 1);
+                    cv::putText(faceImage, seqText, 
+                               cv::Point(innerX + 5, innerY + 110), 
+                               cv::FONT_HERSHEY_SIMPLEX, 0.3, cv::Scalar(100, 100, 100), 1);
+                    
+                    // 添加判断标记
+                    if (info.distance > info.threshold) {
+                        cv::circle(faceImage, 
+                                  cv::Point(innerX + innerWidth - 10, innerY + 10), 
+                                  5, cv::Scalar(0, 0, 255), -1);
+                    } else {
+                        cv::circle(faceImage, 
+                                  cv::Point(innerX + innerWidth - 10, innerY + 10), 
+                                  5, cv::Scalar(0, 180, 0), -1);
+                    }
+                }
+                
+                // 如果这一行没有填满，留空
+                for (int col = (endIndex - startIndex); col < maxCellsPerRow; col++) {
+                    int cellX = viewNameWidth + (col * cellWidth);
+                    int cellY = globalRowY;
+                    
+                    cv::rectangle(faceImage, 
+                                 cv::Rect(cellX, cellY, cellWidth, cellHeight), 
+                                 cv::Scalar(245, 245, 245), -1);
+                    cv::rectangle(faceImage, 
+                                 cv::Rect(cellX, cellY, cellWidth, cellHeight), 
+                                 cv::Scalar(220, 220, 220), 1);
+                }
+                
+                currentGlobalRow++;
+            }
+            
+            // 在每个视图之后添加一个浅色分隔线
+            if (currentGlobalRow < totalRows) {
+                int separatorY = 60 + (currentGlobalRow * cellHeight);
+                cv::line(faceImage, 
+                        cv::Point(0, separatorY - 1), 
+                        cv::Point(totalWidth, separatorY - 1), 
+                        cv::Scalar(220, 220, 220), 1);
+            }
+        }
+        
+        // 添加网格线
+        for (int row = 0; row <= totalRows; row++) {
+            int y = 60 + (row * cellHeight);
+            cv::line(faceImage, 
+                    cv::Point(0, y), 
+                    cv::Point(totalWidth, y), 
+                    cv::Scalar(200, 200, 200), 1);
+        }
+        
+        // 添加视图名称区域分隔线
+        cv::line(faceImage, 
+                cv::Point(viewNameWidth, 60), 
+                cv::Point(viewNameWidth, totalHeight), 
+                cv::Scalar(150, 150, 150), 2);
+        
+        // 保存图片
+        std::string outputPath = outputDir + cv::format("face_%d_comparison.png", faceId);
+        
+        if (!cv::imwrite(outputPath, faceImage)) {
+            printf("❌ 无法保存face %d的对比图: %s\n", faceId, outputPath.c_str());
+        } else {
+            printf("✅ face %d对比图已保存: %s\n", faceId, outputPath.c_str());
+            printf("   尺寸: %d x %d 像素, 视图数: %zu, 记录数: %d\n", 
+                   totalWidth, totalHeight, viewMap.size(), totalRecords);
+        }
+        
+        faceCount++;
+    }
+    
+    // 保存颜色信息到CSV文件
+    saveColorInfoToFile();
+}
+
+// 保存颜色信息到CSV文件
+void ColorComparisonPixel::saveColorInfoToFile() {
+    // 为每个face保存单独的CSV
+    for (const auto& faceEntry : faceViewColorMap) {
+        int faceId = faceEntry.first;
+        const auto& viewMap = faceEntry.second;
+        
+        if (viewMap.empty()) {
+            continue;
+        }
+        
+        std::string filePath = outputDir + cv::format("face_%d_colors.csv", faceId);
+        FILE* fp = fopen(filePath.c_str(), "w");
+        
+        if (!fp) {
+            printf("❌ 无法创建文件: %s\n", filePath.c_str());
+            continue;
+        }
+        
+        // 写入CSV标题
+        fprintf(fp, "FaceID,View,RecordNo,Gaussian_R,Gaussian_G,Gaussian_B,Original_R,Original_G,Original_B,Distance,Threshold,NeedsFix\n");
+        
+        int recordNo = 1;
+        for (const auto& viewEntry : viewMap) {
+            const std::string& viewName = viewEntry.first;
+            const std::vector<ColorInfo>& infos = viewEntry.second;
+            
+            for (int i = 0; i < (int)infos.size(); i++) {
+                const ColorInfo& info = infos[i];
+                bool needsFix = (info.distance > info.threshold);
+                fprintf(fp, "%d,%s,%d,%d,%d,%d,%d,%d,%d,%.4f,%.4f,%s\n",
+                        faceId,
+                        viewName.c_str(),
+                        i + 1,
+                        info.gaussianColor[0], info.gaussianColor[1], info.gaussianColor[2],
+                        info.originalColor[0], info.originalColor[1], info.originalColor[2],
+                        info.distance, info.threshold,
+                        needsFix ? "YES" : "NO");
+            }
+        }
+        
+        fclose(fp);
+        printf("✅ face %d颜色信息已保存到: %s\n", faceId, filePath.c_str());
+    }
+    
+    // 保存汇总统计信息
+    std::string summaryPath = outputDir + "face_comparison_summary.csv";
+    FILE* summaryFp = fopen(summaryPath.c_str(), "w");
+    
+    if (summaryFp) {
+        fprintf(summaryFp, "FaceID,Views,TotalRecords,NeedFixRecords,NeedFix%%,MinDistance,MaxDistance,AvgDistance\n");
+        
+        for (const auto& faceEntry : faceViewColorMap) {
+            int faceId = faceEntry.first;
+            const auto& viewMap = faceEntry.second;
+            
+            int totalRecords = 0;
+            int needFixCount = 0;
+            float minDist = std::numeric_limits<float>::max();
+            float maxDist = 0.0f;
+            float sumDist = 0.0f;
+            
+            for (const auto& viewEntry : viewMap) {
+                const std::vector<ColorInfo>& infos = viewEntry.second;
+                totalRecords += infos.size();
+                
+                for (const auto& info : infos) {
+                    if (info.distance > info.threshold) needFixCount++;
+                    minDist = std::min(minDist, info.distance);
+                    maxDist = std::max(maxDist, info.distance);
+                    sumDist += info.distance;
+                }
+            }
+            
+            float avgDist = (totalRecords > 0) ? (sumDist / totalRecords) : 0.0f;
+            float fixPercentage = (totalRecords > 0) ? (needFixCount * 100.0f / totalRecords) : 0.0f;
+            
+            fprintf(summaryFp, "%d,%zu,%d,%d,%.2f%%,%.4f,%.4f,%.4f\n",
+                    faceId,
+                    viewMap.size(),
+                    totalRecords,
+                    needFixCount,
+                    fixPercentage,
+                    minDist,
+                    maxDist,
+                    avgDist);
+        }
+        
+        fclose(summaryFp);
+        printf("✅ 汇总统计信息已保存到: %s\n", summaryPath.c_str());
+    }
+}

libs/MVS/ColorComparisonPixel.h

@@ -0,0 +1,74 @@
+#ifndef COLORCOMPARISONPIXEL_H
+#define COLORCOMPARISONPIXEL_H
+
+#include <string>
+#include <vector>
+#include <map>
+#include <unordered_map>
+
+#include "ColorComparisonFace.h"
+
+/*
+// 不使用前向声明，直接定义简单的颜色结构
+struct MeshColor {
+    unsigned char r, g, b;
+    
+    MeshColor() : r(0), g(0), b(0) {}
+    MeshColor(unsigned char r, unsigned char g, unsigned char b) 
+        : r(r), g(g), b(b) {}
+    
+    unsigned char operator[](size_t idx) const {
+        if (idx == 0) return r;
+        if (idx == 1) return g;
+        if (idx == 2) return b;
+        return 0;
+    }
+};
+*/
+
+class ColorComparisonPixel {
+private:
+    struct ColorInfo {
+        int faceId;
+        MeshColor gaussianColor;
+        MeshColor originalColor;
+        float distance;
+        float threshold;
+        std::string filename;
+    };
+    
+    // 使用嵌套map: faceid -> filename -> ColorInfo列表
+    std::map<int, std::map<std::string, std::vector<ColorInfo>>> faceViewColorMap;
+    std::string outputDir;
+    
+public:
+    // 构造函数
+    ColorComparisonPixel(const std::string& dir);
+    
+    // 析构函数
+    virtual ~ColorComparisonPixel() {}
+    
+    // 添加颜色信息
+    void addColorInfo(int faceId, 
+                     const MeshColor& gaussianColor, 
+                     const MeshColor& originalColor,
+                     float distance, float threshold,
+                     const std::string& filename);
+    
+    // 创建按faceid分组的对比图
+    void createBatchComparison(int maxCellsPerRow = 10, int maxFacesPerImage = 50);
+    
+    // 保存颜色信息到CSV文件
+    void saveColorInfoToFile();
+    
+    // 获取总face数
+    int getTotalFaces() const;
+    
+    // 获取总记录数
+    int getTotalRecords() const;
+    
+    // 获取faceid列表
+    std::vector<int> getFaceIds() const;
+};
+
+#endif // COLORCOMPARISONPIXEL_H

libs/MVS/Mesh.cpp

@@ -350,6 +350,16 @@ void Mesh::ComputeNormalFaces()
 	#endif
 }
 
+// compute color for all faces
+void Mesh::ComputeColorFaces()
+{
+	faceColors.resize(faces.size());
+
+	FOREACH(idxFace, faces)
+		faceColors[idxFace] = FaceColor(faces[idxFace]);
+
+}
+
 // compute normal for all vertices
 #if 1
 // computes the vertex normal as the area weighted face normals average
@@ -1096,18 +1106,20 @@ namespace BasicPLY {
 	struct Vertex {
 		Mesh::Vertex v;
 		Mesh::Normal n;
+		Mesh::Color color;
 		static void InitLoadProps(PLY& ply, int elem_count,
-			Mesh::VertexArr& vertices, Mesh::NormalArr& vertexNormals)
+			Mesh::VertexArr& vertices, Mesh::ColorArr& vertexColors)
 		{
 			PLY::PlyElement* elm = ply.find_element(elem_names[0]);
 			const size_t nMaxProps(SizeOfArray(props));
 			for (size_t p=0; p<nMaxProps; ++p) {
+				// DEBUG_EXTRA("InitLoadProps name=%s\n", props[p].name.c_str());
 				if (ply.find_property(elm, props[p].name.c_str()) < 0)
 					continue;
 				ply.setup_property(props[p]);
 				switch (p) {
 				case 0: vertices.resize((IDX)elem_count); break;
-				case 3: vertexNormals.resize((IDX)elem_count); break;
+				case 3: vertexColors.resize((IDX)elem_count); break;
 				}
 			}
 		}
@@ -1125,6 +1137,15 @@ namespace BasicPLY {
 		}
 		static const PLY::PlyProperty props[9];
 	};
+	const PLY::PlyProperty Vertex::props[] = {
+		{"x",             PLY::Float32, PLY::Float32, offsetof(Vertex,v.x), 0, 0, 0, 0},
+		{"y",             PLY::Float32, PLY::Float32, offsetof(Vertex,v.y), 0, 0, 0, 0},
+		{"z",             PLY::Float32, PLY::Float32, offsetof(Vertex,v.z), 0, 0, 0, 0},
+		{"red",           PLY::Int8, PLY::Int8, offsetof(Vertex,color.r), 0, 0, 0, 0},
+		{"green",         PLY::Int8, PLY::Int8, offsetof(Vertex,color.g), 0, 0, 0, 0},
+		{"blue",          PLY::Int8, PLY::Int8, offsetof(Vertex,color.b), 0, 0, 0, 0}
+	};
+	/*
 	const PLY::PlyProperty Vertex::props[] = {
 		{"x",             PLY::Float32, PLY::Float32, offsetof(Vertex,v.x), 0, 0, 0, 0},
 		{"y",             PLY::Float32, PLY::Float32, offsetof(Vertex,v.y), 0, 0, 0, 0},
@@ -1133,6 +1154,7 @@ namespace BasicPLY {
 		{"ny",            PLY::Float32, PLY::Float32, offsetof(Vertex,n.y), 0, 0, 0, 0},
 		{"nz",            PLY::Float32, PLY::Float32, offsetof(Vertex,n.z), 0, 0, 0, 0}
 	};
+	*/
 	// list of property information for a face
 	struct Face {
 		struct FaceIndices {
@@ -1191,7 +1213,7 @@ namespace BasicPLY {
 } // namespace MeshInternal
 
 // import the mesh from the given file
-bool Mesh::Load(const String& fileName)
+bool Mesh::Load(const String& fileName, bool *pBExistVertexColor)
 {
 	TD_TIMER_STARTD();
 	const String ext(Util::getFileExt(fileName).ToLower());
@@ -1202,14 +1224,14 @@ bool Mesh::Load(const String& fileName)
 	if (ext == _T(".gltf") || ext == _T(".glb"))
 		ret = LoadGLTF(fileName, ext == _T(".glb"));
 	else
-		ret = LoadPLY(fileName);
+		ret = LoadPLY(fileName, pBExistVertexColor);
 	if (!ret)
 		return false;
 	DEBUG_EXTRA("Mesh loaded: %u vertices, %u faces (%s)", vertices.size(), faces.size(), TD_TIMER_GET_FMT().c_str());
 	return true;
 }
 // import the mesh as a PLY file
-bool Mesh::LoadPLY(const String& fileName)
+bool Mesh::LoadPLY(const String& fileName, bool *pBExistVertexColor)
 {
 	ASSERT(!fileName.empty());
 	Release();
@@ -1244,16 +1266,23 @@ bool Mesh::LoadPLY(const String& fileName)
 		LPCSTR elem_name = ply.setup_element_read(i, &elem_count);
 		if (PLY::equal_strings(BasicPLY::elem_names[0], elem_name)) {
 			ASSERT(vertices.size() == (VIndex)elem_count);
-			BasicPLY::Vertex::InitLoadProps(ply, elem_count, vertices, vertexNormals);
-			if (vertexNormals.empty()) {
+			// BasicPLY::Vertex::InitLoadProps(ply, elem_count, vertices, vertexNormals);
+			BasicPLY::Vertex::InitLoadProps(ply, elem_count, vertices, vertexColors);
+			if (vertexColors.empty()) {
+				// printf("vertexColors.empty, elem_count=%u\n", elem_count);
+				*pBExistVertexColor = false;
 				for (Vertex& vert: vertices)
 					ply.get_element(&vert);
 			} else {
+				// printf("Not vertexColors.empty, elem_count=%u\n", elem_count);
+				*pBExistVertexColor = true;
 				BasicPLY::Vertex vertex;
 				for (int v=0; v<elem_count; ++v) {
 					ply.get_element(&vertex);
 					vertices[v] = vertex.v;
-					vertexNormals[v] = vertex.n;
+					vertexColors[v] = vertex.color;
+					// if (v<10)
+					//	printf("vertexColors v=%u, rgb=(%u, %u, %u)\n", v, vertex.color.r, vertex.color.g, vertex.color.b);
 				}
 			}
 		} else

libs/MVS/Mesh.h

@@ -60,6 +60,9 @@ public:
 
 	typedef SEACAVE::cList<Vertex,const Vertex&,0,8192,VIndex> VertexArr;
 	typedef SEACAVE::cList<Face,const Face&,0,8192,FIndex> FaceArr;
+	
+	typedef Color8U Color;
+	typedef SEACAVE::cList<Color,const Color&,0,8192,VIndex> ColorArr;
 
 	typedef SEACAVE::cList<VIndex,VIndex,0,8,VIndex> VertexIdxArr;
 	typedef SEACAVE::cList<FIndex,FIndex,0,8,FIndex> FaceIdxArr;
@@ -154,6 +157,9 @@ public:
 	VertexFacesArr vertexFaces; // for each vertex, the ordered list of faces containing it (optional)
 	BoolArr vertexBoundary; // for each vertex, stores if it is at the boundary or not (optional)
 
+	ColorArr vertexColors; // for each vertex, the normal to the surface in that point (optional)
+	ColorArr faceColors; // for each face, the color to it
+
 	NormalArr faceNormals; // for each face, the normal to it (optional)
 	FaceFacesArr faceFaces; // for each face, the list of adjacent faces, NO_ID for border edges (optional)
 	TexCoordArr faceTexcoords; // for each face, the texture-coordinates corresponding to its vertices, 3x num faces OR for each vertex (optional)
@@ -194,6 +200,8 @@ public:
 	void ComputeNormalFaces();
 	void ComputeNormalVertices();
 
+	void ComputeColorFaces();
+
 	void SmoothNormalFaces(float fMaxGradient=25.f, float fOriginalWeight=0.5f, unsigned nIterations=3);
 
 	void GetEdgeFaces(VIndex, VIndex, FaceIdxArr&) const;
@@ -238,6 +246,10 @@ public:
 		return n;
 	}
 
+	inline Color FaceColor(const Face& f) const {
+		return ComputeTriangleColor(vertexColors[f[0]], vertexColors[f[1]], vertexColors[f[2]]);
+	}
+
 	Planef EstimateGroundPlane(const ImageArr& images, float sampleMesh=0, float planeThreshold=0, const String& fileExportPlane="") const;
 
 	Vertex ComputeCentroid(FIndex) const;
@@ -262,7 +274,7 @@ public:
 	bool TransferTexture(Mesh& mesh, const FaceIdxArr& faceSubsetIndices={}, unsigned borderSize=3, unsigned textureSize=4096);
 
 	// file IO
-	bool Load(const String& fileName);
+	bool Load(const String& fileName, bool *pBExistVertexColor=nullptr);
 	bool Save(const String& fileName, const cList<String>& comments=cList<String>(), bool bBinary=true) const;
 	bool Save(const FacesChunkArr&, const String& fileName, const cList<String>& comments=cList<String>(), bool bBinary=true) const;
 	static bool Save(const VertexArr& vertices, const String& fileName, bool bBinary=true);
@@ -272,7 +284,7 @@ public:
 	static inline VIndex& GetVertex(Face& f, VIndex v) { const uint32_t idx(FindVertex(f, v)); ASSERT(idx != NO_ID); return f[idx]; }
 
 protected:
-	bool LoadPLY(const String& fileName);
+	bool LoadPLY(const String& fileName, bool *pBExistVertexColor);
 	bool LoadOBJ(const String& fileName);
 	bool LoadGLTF(const String& fileName, bool bBinary=true);
 

libs/MVS/Scene.h

@@ -66,6 +66,9 @@ public:
 	std::map<std::string, std::unordered_set<int>> edge_faces_map;
 	std::map<std::string, std::unordered_set<int>> delete_edge_faces_map;
 	std::unordered_set<int> face_visible_relative;
+	std::unordered_set<int> face_test;
+
+	std::string base_path;
 
 public:
 	inline Scene(unsigned _nMaxThreads=0)
@@ -164,12 +167,13 @@ public:
 						 std::map<std::string, std::unordered_set<int>>& edge_faces_map,
 						 std::map<std::string, std::unordered_set<int>>& delete_edge_faces_map,
                          std::string& basePath);
+	bool LoadTestFacesData(std::unordered_set<int>& face_test, std::string& basePath);
 
 	// Mesh texturing
 	bool TextureMesh(unsigned nResolutionLevel, unsigned nMinResolution, unsigned minCommonCameras=0, float fOutlierThreshold=0.f, float fRatioDataSmoothness=0.3f,
 		bool bGlobalSeamLeveling=true, bool bLocalSeamLeveling=true, unsigned nTextureSizeMultiple=0, unsigned nRectPackingHeuristic=3, Pixel8U colEmpty=Pixel8U(255,127,39),
 		float fSharpnessWeight=0.5f, int ignoreMaskLabel=-1, int maxTextureSize=0, const IIndexArr& views=IIndexArr(), const SEACAVE::String& basename = "", bool bOriginFaceview = false,
-		const std::string& inputFileName = "", const std::string& meshFileName = "");
+		const std::string& inputFileName = "", const std::string& meshFileName = "", bool bExistVertexColor = false);
 
 	std::string runPython(const std::string& command);
 	bool is_face_visible(const std::string& image_name, int face_index);

utilities/select_face.py

@@ -0,0 +1,33 @@
+import bpy
+import os
+
+mesh = bpy.context.active_object.data
+
+selected_faces = [polygon.index for polygon in mesh.polygons if polygon.select]
+
+output_lines = ["详细信息:"]
+    
+for face_idx in selected_faces[:10]:  # 只显示前10个
+    face = mesh.polygons[face_idx]
+    output_lines.append(f"  面 {face_idx}: 顶点数={len(face.vertices)}, ={face.area:.4f}")    
+
+text_name = f"selected_faces_report"
+
+# 删除已存在的同名文本数据块
+if text_name in bpy.data.texts:
+    bpy.data.texts.remove(bpy.data.texts[text_name])
+
+text_block = bpy.data.texts.new(text_name)
+for line in output_lines:
+    text_block.write(line + "\n")
+    
+save_dir = "/home/algo/Documents/openMVS/data/446442/out.446442"
+os.makedirs(save_dir, exist_ok=True)
+
+file_path = os.path.join(save_dir, "_test_faces.txt")
+
+with open(file_path, 'w') as f:
+    for face_index in selected_faces:
+        f.write(f"{face_index}\n")
+        
+print(f"面片索引已保存到: {file_path}")