diff --git a/libs/MVS/SceneTexture.cpp b/libs/MVS/SceneTexture.cpp index 1c2c952..3188b4b 100644 --- a/libs/MVS/SceneTexture.cpp +++ b/libs/MVS/SceneTexture.cpp @@ -4301,9 +4301,10 @@ bool MeshTexture::CreateVirtualFaces62(FaceDataViewArr& facesDatas, FaceDataView } else { IIndexArr selectedCams = SelectBestViews(centerFaceDatas, virtualFaceCenterFaceID, minCommonCameras, ratioAngleToQuality); - //* // 获取中心面片的法线 (注意变量名是 normalCenter, 不是 centerNormal) const Normal& normalCenter = scene.mesh.faceNormals[virtualFaceCenterFaceID]; + + //* // 过滤selectedCams：只保留夹角小于30度的视图 IIndexArr filteredCams; // 用于存储过滤后的视图索引 for (IIndex idxView : selectedCams) { @@ -4359,53 +4360,220 @@ bool MeshTexture::CreateVirtualFaces62(FaceDataViewArr& facesDatas, FaceDataView if (angleDeg <= 45.0f) { - // filteredCams.push_back(idxView); - - //* - float brightnessScore = CalculateBrightnessScore(imageData); // 亮度评分函数 - float angleScore = 1.0f - (angleDeg / 45.0f); - float qualityScore = 0.0f; - const FaceDataArr& centerFaceDatas = facesDatas[virtualFaceCenterFaceID]; - for (const FaceData& fd : centerFaceDatas) { - if (fd.idxView == idxView) { - qualityScore = fd.quality; - break; - } - } - qualityScore = std::max(0.0f, std::min(1.0f, qualityScore)); - float overallScore = 0.5f * angleScore + 0.3f * brightnessScore + 0.2f * qualityScore; - if (overallScore > 0.35f) { - filteredCams.push_back(idxView); - } - //*/ - } + filteredCams.push_back(idxView); + // float brightnessScore = CalculateBrightnessScore(imageData); // 亮度评分函数 + // float angleScore = 1.0f - (angleDeg / 45.0f); + // float qualityScore = 0.0f; + // const FaceDataArr& centerFaceDatas = facesDatas[virtualFaceCenterFaceID]; + // for (const FaceData& fd : centerFaceDatas) { + // if (fd.idxView == idxView) { + // qualityScore = fd.quality; + // break; + // } + // } + // qualityScore = std::max(0.0f, std::min(1.0f, qualityScore)); + // float overallScore = 0.5f * angleScore + 0.3f * brightnessScore + 0.2f * qualityScore; + // if (overallScore > 0.35f) { + // filteredCams.push_back(idxView); + // } + } } else { - // filteredCams.push_back(idxView); + filteredCams.push_back(idxView); - //* - float brightnessScore = CalculateBrightnessScore(imageData); // 亮度评分函数 - float angleScore = 1.0f - (angleDeg / 45.0f); - float qualityScore = 0.0f; - const FaceDataArr& centerFaceDatas = facesDatas[virtualFaceCenterFaceID]; - for (const FaceData& fd : centerFaceDatas) { - if (fd.idxView == idxView) { - qualityScore = fd.quality; - break; - } - } - qualityScore = std::max(0.0f, std::min(1.0f, qualityScore)); - float overallScore = 0.5f * angleScore + 0.3f * brightnessScore + 0.2f * qualityScore; - if (overallScore > 0.35f) { + // float brightnessScore = CalculateBrightnessScore(imageData); // 亮度评分函数 + // float angleScore = 1.0f - (angleDeg / 45.0f); + // float qualityScore = 0.0f; + // const FaceDataArr& centerFaceDatas = facesDatas[virtualFaceCenterFaceID]; + // for (const FaceData& fd : centerFaceDatas) { + // if (fd.idxView == idxView) { + // qualityScore = fd.quality; + // break; + // } + // } + // qualityScore = std::max(0.0f, std::min(1.0f, qualityScore)); + // float overallScore = 0.5f * angleScore + 0.3f * brightnessScore + 0.2f * qualityScore; + // if (overallScore > 0.35f) { + // filteredCams.push_back(idxView); + // } + } + } + } + //*/ + + /* + + struct CameraInfo { + float brightness; + float angleDeg; + float qualityScore; + bool isEdge; + }; + // 修改后的代码，使用亮度统计分布过滤异常值 + IIndexArr filteredCams; // 用于存储过滤后的视图索引 + + // 步骤1: 收集所有候选相机的亮度值 + std::vector allBrightnessScores; + std::vector> cameraInfos; // 存储相机ID和相关信息 + + for (IIndex idxView : selectedCams) { + const Image& imageData = images[idxView]; + + // 计算相机朝向向量 + const RMatrix& R = imageData.camera.R; + Point3f localForward(0.0f, 0.0f, -1.0f); + Point3f cameraForward; + cameraForward.x = R(0,0) * localForward.x + R(0,1) * localForward.y + R(0,2) * localForward.z; + cameraForward.y = R(1,0) * localForward.x + R(1,1) * localForward.y + R(1,2) * localForward.z; + cameraForward.z = R(2,0) * localForward.x + R(2,1) * localForward.y + R(2,2) * localForward.z; + + // 归一化 + float norm = std::sqrt(cameraForward.x * cameraForward.x + + cameraForward.y * cameraForward.y + + cameraForward.z * cameraForward.z); + if (norm > 0.0f) { + cameraForward.x /= norm; + cameraForward.y /= norm; + cameraForward.z /= norm; + } else { + cameraForward = Point3f(0, 0, -1); + } + + // 计算夹角 + Point3f normalPoint(normalCenter.x, normalCenter.y, normalCenter.z); + float cosAngle = cameraForward.dot(normalPoint); + float angleDeg = std::acos(cosAngle) * 180.0f / M_PI; + + // 计算亮度分数 + float brightnessScore = CalculateBrightnessScore(imageData); + allBrightnessScores.push_back(brightnessScore); + + // 获取质量分数 + float qualityScore = 0.0f; + const FaceDataArr& centerFaceDatas = facesDatas[virtualFaceCenterFaceID]; + for (const FaceData& fd : centerFaceDatas) { + if (fd.idxView == idxView) { + qualityScore = fd.quality; + break; + } + } + qualityScore = std::max(0.0f, std::min(1.0f, qualityScore)); + + // 检查是否为边缘 + std::string strPath = imageData.name; + size_t lastSlash = strPath.find_last_of("/\\"); + if (lastSlash == std::string::npos) lastSlash = 0; + else lastSlash++; + + size_t lastDot = strPath.find_last_of('.'); + if (lastDot == std::string::npos) lastDot = strPath.size(); + + std::string strName = strPath.substr(lastSlash, lastDot - lastSlash); + + bool isEdge = false; + if (!scene.is_face_delete_edge(strName, virtualFaceCenterFaceID)) { + isEdge = scene.is_face_edge(strName, virtualFaceCenterFaceID); + } + + // 存储相机信息 + cameraInfos.emplace_back(idxView, CameraInfo{ + .brightness = brightnessScore, + .angleDeg = angleDeg, + .qualityScore = qualityScore, + .isEdge = isEdge + }); + } + + float medianBrightness = 0.0f; + // 步骤2: 计算亮度分布的统计特征 + if (!allBrightnessScores.empty()) { + // 方法1: 使用中位数和MAD（绝对中位差） - 对异常值更鲁棒 + std::vector sortedBrightness = allBrightnessScores; + std::sort(sortedBrightness.begin(), sortedBrightness.end()); + + medianBrightness = sortedBrightness[sortedBrightness.size() / 2]; + + // 计算MAD + std::vector deviations; + for (float brightness : allBrightnessScores) { + deviations.push_back(std::abs(brightness - medianBrightness)); + } + std::sort(deviations.begin(), deviations.end()); + float mad = deviations[deviations.size() / 2]; + + // 使用3倍MAD作为阈值（通常2-3倍MAD是常用阈值） + float lowerThreshold = medianBrightness - 2.5f * mad; + float upperThreshold = medianBrightness + 2.5f * mad; + + // 方法2: 使用四分位距(IQR) - 备选方法 + if (sortedBrightness.size() >= 4) { + int q1_index = sortedBrightness.size() / 4; + int q3_index = 3 * sortedBrightness.size() / 4; + float q1 = sortedBrightness[q1_index]; + float q3 = sortedBrightness[q3_index]; + float iqr = q3 - q1; + + // 使用1.5倍IQR规则 + float iqrLower = q1 - 1.5f * iqr; + float iqrUpper = q3 + 1.5f * iqr; + + // 也可以结合两种方法 + lowerThreshold = std::max(lowerThreshold, iqrLower); + upperThreshold = std::min(upperThreshold, iqrUpper); + } + + // 步骤3: 根据统计特征过滤相机 + for (const auto& [idxView, info] : cameraInfos) { + // 检查亮度是否在正常范围内 + if (info.brightness < lowerThreshold || info.brightness > upperThreshold) { + // printf("过滤相机 %d: 亮度 %.3f 超出范围 [%.3f, %.3f]\n", + // idxView, info.brightness, lowerThreshold, upperThreshold); + continue; + } + + // 根据是否为边缘面使用不同的参数 + float angleLimit = info.isEdge ? 45.0f : 60.0f; + float scoreThreshold = info.isEdge ? 0.4f : 0.3f; + + if (info.angleDeg <= angleLimit) { + float angleScore = 1.0f - (info.angleDeg / angleLimit); + float overallScore = 0.5f * angleScore + 0.3f * info.brightness + 0.2f * info.qualityScore; + + if (overallScore > scoreThreshold) { filteredCams.push_back(idxView); } - //*/ } } } + // 如果没有足够的相机满足统计条件，可以放宽阈值或使用原始方法 + if (filteredCams.size() < 3 && !cameraInfos.empty()) { + // 回退到简单方法：选择亮度最接近中位数的前N个相机 + std::vector> brightnessDifferences; + + for (const auto& cameraInfoPair : cameraInfos) { + IIndex idxView = cameraInfoPair.first; + CameraInfo info = cameraInfoPair.second; + if (info.isEdge ? (info.angleDeg <= 45.0f) : (info.angleDeg <= 60.0f)) { + // 计算亮度与中位数的差异 + float brightnessDiff = std::abs(info.brightness - medianBrightness); + brightnessDifferences.emplace_back(idxView, brightnessDiff); + } + } + + // 按亮度差异排序，选择差异最小的 + std::sort(brightnessDifferences.begin(), brightnessDifferences.end(), + [](const auto& a, const auto& b) { return a.second < b.second; }); + + int neededCount = std::min(5, (int)brightnessDifferences.size()); + for (int i = 0; i < neededCount; i++) { + filteredCams.push_back(brightnessDifferences[i].first); + } + } + //*/ + // 确保 selectedCams 是非 const 的，才能对其进行赋值 // 例如，其声明应为：IIndexArr selectedCams = ...; (不能是 const IIndexArr) if (filteredCams.empty()) { @@ -4420,7 +4588,6 @@ bool MeshTexture::CreateVirtualFaces62(FaceDataViewArr& facesDatas, FaceDataView selectedCams = filteredCams; isVirtualFace[virtualFaceCenterFaceID] = true; } - //*/ currentVirtualFaceQueue.AddTail(virtualFaceCenterFaceID); queuedFaces.clear();