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添加多个面处理

ColorComparison
hesuicong 2 days ago
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ad159acc6a
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9b8cfbdb1e
3 changed files with 484 additions and 5 deletions
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  1. 321
      libs/MVS/ColorComparisonFace.cpp
  2. 37
      libs/MVS/ColorComparisonFace.h
  3. 131
      libs/MVS/SceneTexture.cpp

321
libs/MVS/ColorComparisonFace.cpp
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@ -444,3 +444,324 @@ void ColorComparisonFace::saveColorInfoToFile() {
printf("✅ 三角形汇总统计信息已保存到: %s\n", summaryPath.c_str()); 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());
}
}

37
libs/MVS/ColorComparisonFace.h
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@ -4,6 +4,7 @@
#include <string> #include <string>
#include <vector> #include <vector>
#include <map> #include <map>
#include <set>
#include <opencv2/opencv.hpp> #include <opencv2/opencv.hpp>
// 不使用前向声明，直接定义简单的颜色结构 // 不使用前向声明，直接定义简单的颜色结构
@ -24,6 +25,7 @@ struct MeshColor {
class ColorComparisonFace { class ColorComparisonFace {
private: private:
// 单面信息结构
struct FaceColorInfo { struct FaceColorInfo {
int faceId; // 面的ID int faceId; // 面的ID
MeshColor gaussianColor; // 高斯颜色 MeshColor gaussianColor; // 高斯颜色
@ -35,8 +37,24 @@ private:
std::string filename; // 文件名 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 // 使用嵌套map: faceid -> filename -> FaceColorInfo列表
std::map<int, std::map<std::string, std::vector<FaceColorInfo>>> faceViewColorMap; 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; std::string outputDir;
public: public:
@ -56,9 +74,25 @@ public:
float threshold, float threshold,
const std::string& filename); 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 // 创建三角形区域对比图
void createBatchComparison(int maxBlocksPerRow = 6, int maxFacesPerImage = 20); 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 // 保存颜色信息到CSV文件
void saveColorInfoToFile(); void saveColorInfoToFile();
@ -70,6 +104,9 @@ public:
// 获取faceid列表 // 获取faceid列表
std::vector<int> getFaceIds() const; std::vector<int> getFaceIds() const;
// 获取连续区域数
int getTotalRegions() const;
}; };
#endif // COLORCOMPARISONBFACE_H #endif // COLORCOMPARISONBFACE_H

131
libs/MVS/SceneTexture.cpp
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@ -78,7 +78,7 @@ using namespace MVS;
#define TEXOPT_INFERENCE_TRWS 2 #define TEXOPT_INFERENCE_TRWS 2
#define TEXOPT_INFERENCE TEXOPT_INFERENCE_LBP #define TEXOPT_INFERENCE TEXOPT_INFERENCE_LBP
#define MASK_FACE_OCCLUSION #define MASK_FACE_OCCLUSION
// #define TEST #define TEST
// #define USE_CUDA // #define USE_CUDA
@ -985,6 +985,77 @@ public:
image = visualization; image = visualization;
} }
// 判断两个面是否相邻（共享一条边）
static bool areFacesAdjacent(const Mesh::Face& face1, const Mesh::Face& face2) {
int sharedVertices = 0;
// 检查共享的顶点数量
for (int i = 0; i < 3; i++) {
for (int j = 0; j < 3; j++) {
if (face1[i] == face2[j]) {
sharedVertices++;
}
}
}
// 如果共享2个顶点，说明共享一条边
return sharedVertices == 2;
}
// 修改 mergeContinuousFaces 函数的类型
static std::map<int, std::set<unsigned int>> mergeContinuousFaces( // 返回类型改为 unsigned int
const std::set<unsigned int>& testFaces, // 参数类型改为 unsigned int
const Mesh& mesh) {
std::map<int, std::set<unsigned int>> regions; // 返回类型改为 unsigned int
std::set<unsigned int> processed; // 类型改为 unsigned int
int regionId = 0;
// 遍历所有测试面
for (unsigned int face : testFaces) { // 类型改为 unsigned int
if (processed.find(face) != processed.end()) {
continue;
}
// 开始新区域
std::set<unsigned int> currentRegion; // 类型改为 unsigned int
std::queue<unsigned int> faceQueue; // 类型改为 unsigned int
faceQueue.push(face);
while (!faceQueue.empty()) {
unsigned int currentFace = faceQueue.front(); // 类型改为 unsigned int
faceQueue.pop();
if (processed.find(currentFace) != processed.end()) {
continue;
}
// 添加到当前区域
currentRegion.insert(currentFace);
processed.insert(currentFace);
// 查找相邻的测试面
for (unsigned int otherFace : testFaces) { // 类型改为 unsigned int
if (processed.find(otherFace) != processed.end()) {
continue;
}
// 检查是否相邻
if (areFacesAdjacent(mesh.faces[currentFace], mesh.faces[otherFace])) {
faceQueue.push(otherFace);
}
}
}
if (!currentRegion.empty()) {
regions[regionId] = currentRegion;
regionId++;
}
}
return regions;
}
//*/ //*/
/* /*
// 采用ITU-R BT.601标准系数，增加数值稳定性处理 // 采用ITU-R BT.601标准系数，增加数值稳定性处理
@ -1200,13 +1271,63 @@ static ColorComparisonPixel* g_colorComparisonPixel = nullptr;
bool MeshTexture::ListCameraFaces(FaceDataViewArr& facesDatas, float fOutlierThreshold, int nIgnoreMaskLabel, const IIndexArr& _views, bool bUseVirtualFaces) bool MeshTexture::ListCameraFaces(FaceDataViewArr& facesDatas, float fOutlierThreshold, int nIgnoreMaskLabel, const IIndexArr& _views, bool bUseVirtualFaces)
{ {
#ifdef TEST #ifdef TEST
std::string outputDir = scene.base_path + std::string("/color_comparison/"); std::string outputDir = scene.base_path + std::string("/color_comparison/");
printf("ListCameraFaces outputDir=%s\n", outputDir.c_str()); printf("ListCameraFaces outputDir=%s\n", outputDir.c_str());
g_colorComparisonFace = new ColorComparisonFace(outputDir); g_colorComparisonFace = new ColorComparisonFace(outputDir);
std::map<IIndex, std::map<FIndex, std::vector<cv::Point>>> testFacePixelsByView; std::map<IIndex, std::map<FIndex, std::vector<cv::Point>>> testFacePixelsByView;
g_colorComparisonPixel = new ColorComparisonPixel(outputDir);
// 1. 收集所有测试面
std::set<unsigned int> allTestFaces; // 修改为 unsigned int
for (FIndex idxFace = 0; idxFace < faces.size(); ++idxFace) {
if (isTestFace(scene.face_test, idxFace)) {
allTestFaces.insert(idxFace);
}
}
printf("找到 %zu 个测试面\n", allTestFaces.size());
g_colorComparisonPixel = new ColorComparisonPixel(outputDir); // 2. 合并连续的三角形为区域
std::map<int, std::set<unsigned int>> continuousRegions = mergeContinuousFaces(allTestFaces, scene.mesh);
printf("将测试面合并为 %zu 个连续区域\n", continuousRegions.size());
// 3. 为每个区域计算平均高斯颜色
std::map<int, MeshColor> regionGaussianColors;
for (const auto& regionEntry : continuousRegions) {
int regionId = regionEntry.first;
const std::set<unsigned int>& regionFaces = regionEntry.second; // 修改为 unsigned int
float sumR = 0, sumG = 0, sumB = 0;
int faceCount = 0;
for (unsigned int faceId : regionFaces) { // 修改为 unsigned int
if (faceId < faceColorsGaussian.size()) {
Mesh::Color gaussianColor = faceColorsGaussian[faceId];
sumR += gaussianColor.r;
sumG += gaussianColor.g;
sumB += gaussianColor.b;
faceCount++;
}
}
if (faceCount > 0) {
MeshColor avgColor(
static_cast<unsigned char>(sumR / faceCount),
static_cast<unsigned char>(sumG / faceCount),
static_cast<unsigned char>(sumB / faceCount)
);
regionGaussianColors[regionId] = avgColor;
printf("区域 %d: 包含 %zu 个面，高斯颜色(R=%d,G=%d,B=%d)\n",
regionId, regionFaces.size(),
avgColor.r, avgColor.g, avgColor.b);
// 添加到批处理器
g_colorComparisonFace->addContinuousRegionInfo(regionId, regionFaces, avgColor);
}
}
#endif #endif
// create faces octree // create faces octree

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