中间版本保存

libs/MVS/SceneTexture.cpp

@@ -6935,6 +6935,7 @@ bool MeshTexture::FaceViewSelection3( unsigned minCommonCameras, float fOutlierT
 		// printf("FaceViewSelection3 2 scene.mesh.vertices.size=%d\n", scene.mesh.vertices.size());
 
 		bool bUseVirtualFaces(minCommonCameras > 0);
+		bUseVirtualFaces = false;
 
 		// list all views for each face
 		FaceDataViewArr facesDatas;
@@ -7673,263 +7674,49 @@ bool MeshTexture::FaceViewSelection3( unsigned minCommonCameras, float fOutlierT
 
 		if (!bUseVirtualFaces)
 		{
-			// assign the best view to each face
+			// 分配最佳视图给每个面片
 			labels.resize(faces.size());
-			{
+			labelsInvalid.resize(faces.size());
-				// normalize quality values
-				float maxQuality(0);
-				for (const FaceDataArr& faceDatas: facesDatas) {
-					for (const FaceData& faceData: faceDatas)
-						if (maxQuality < faceData.quality)
-							maxQuality = faceData.quality;
-				}
-				Histogram32F hist(std::make_pair(0.f, maxQuality), 1000);
-				for (const FaceDataArr& faceDatas: facesDatas) {
-					for (const FaceData& faceData: faceDatas)
-						hist.Add(faceData.quality);
-				}
-				const float normQuality(hist.GetApproximatePermille(0.95f));
-
-				#if TEXOPT_INFERENCE == TEXOPT_INFERENCE_LBP
-				// initialize inference structures
-				const LBPInference::EnergyType MaxEnergy(fRatioDataSmoothness*(LBPInference::EnergyType)LBPInference::MaxEnergy);
-				LBPInference inference; {
-					inference.SetNumNodes(faces.size());
-					inference.SetSmoothCost(SmoothnessPotts);
-					// inference.SetSmoothCost(SmoothnessLinear);
-					// inference.SetSmoothCost(NewSmoothness);
-
-					EdgeOutIter ei, eie;
-					FOREACH(f, faces) {
-						for (boost::tie(ei, eie) = boost::out_edges(f, graph); ei != eie; ++ei) {
-							ASSERT(f == (FIndex)ei->m_source);
-							const FIndex fAdj((FIndex)ei->m_target);
-							if (f < fAdj) // add edges only once
-								inference.SetNeighbors(f, fAdj);
-						}
-						// set costs for label 0 (undefined)
-						inference.SetDataCost((Label)0, f, MaxEnergy);
-					}
-				}
 			
-				//*
+			FOREACH(l, labelsInvalid) {
-				for (const FaceDataArr& faceDatas : facesDatas) {
+				labelsInvalid[l] = NO_ID;
-					for (const FaceData& faceData : faceDatas) {
-						if (faceData.quality > maxQuality) 
-							maxQuality = faceData.quality;
-					}
-				}
-				for (const FaceDataArr& faceDatas : facesDatas) {
-					for (const FaceData& faceData : faceDatas)
-						hist.Add(faceData.quality);
 			}
 
-				FOREACH(f, facesDatas) {
+			// 直接为每个面片选择最佳视图（跳过推理）
-					// if (scene.mesh.invalidFacesRelative.data.contains(f))
+			FOREACH(f, faces) {
-					//	continue;
-
 				const FaceDataArr& faceDatas = facesDatas[f];
-					const size_t numViews = faceDatas.size();
+				if (faceDatas.empty()) {
-					const unsigned minSingleView = 6; // 与虚拟面模式相同的阈值
+					labels[f] = NO_ID;
-					
-					bool bInvalidFacesRelative = false;
-					IIndex invalidView;
-					float invalidQuality;
-
-					// if (numViews <= minSingleView) {
-					if (true) {
-
-					    std::vector<std::pair<float, IIndex>> sortedViews;
-						sortedViews.reserve(faceDatas.size());
-						for (const FaceData& fd : faceDatas) {
-
-							if (fd.bInvalidFacesRelative)
-							{
-								bInvalidFacesRelative = true;
-								// sortedViews.emplace_back(fd.quality, fd.idxView);
-								invalidView = fd.idxView;
-								invalidQuality = fd.quality;
-							}
-							else
-							{
-								// if (fd.quality<=999.0)
-								{
-									sortedViews.emplace_back(fd.quality, fd.idxView);
-									// printf("1fd.quality=%f\n", fd.quality);
-								}
-								// else
-								//	printf("2fd.quality=%f\n", fd.quality);
-							}
-						}
-
-						std::sort(sortedViews.begin(), sortedViews.end(), 
-							[](const auto& a, const auto& b) { return a.first > b.first; });
-						// 设置数据成本：最佳视角成本最低，其他按质量排序递增
-						const float baseCostScale = 0.1f; // 基础成本缩放系数
-						const float costStep = 0.3f;      // 相邻视角成本增量
-
-						for (const auto& image : images)
-						{
-							// printf("image name=%s\n", image.name.c_str());
-						}
- 
-						if (bInvalidFacesRelative && sortedViews.size() == 0)
-						{
-							// const Label label = (Label)sortedViews[0].second + 1;
-							const Label label = (Label)invalidView + 1;
-							float cost = (1.f - invalidQuality / normQuality) * MaxEnergy;
-							// float cost = 0;
-							inference.SetDataCost(label, f, cost);
 					continue;
 				}
 
-						// printf("sortedViews size=%d\n", sortedViews.size());
+				float bestQuality = -1.0f;
-						for (size_t i = 0; i < sortedViews.size(); ++i) {
+				IIndex bestView = NO_ID;
-							const Label label = (Label)sortedViews[i].second + 1;
+				bool bBestIsInvalid = false;
-							float cost;
-							
-							std::string strPath = images[label-1].name;
-							size_t lastSlash = strPath.find_last_of("/\\");
-							if (lastSlash == std::string::npos) lastSlash = 0;  // 若无分隔符，从头开始
-							else lastSlash++;  // 跳过分隔符
-
-							// 查找扩展名分隔符 '.' 的位置
-							size_t lastDot = strPath.find_last_of('.');
-							if (lastDot == std::string::npos) lastDot = strPath.size();  // 若无扩展名，截到末尾
-
-							// 截取文件名（不含路径和扩展名）
-							std::string strName = strPath.substr(lastSlash, lastDot - lastSlash);
-
-							if (i == 0) {
-							// if (true) {
-								// 最佳视角
-								// cost = (1.f - sortedViews[i].first / normQuality) * MaxEnergy * baseCostScale;
-								cost = (1.f - sortedViews[i].first / normQuality) * MaxEnergy;
-								// cost = 0;
-								inference.SetDataCost(label, f, cost);
-							} else {
-								// 其他视角：成本随排名线性增加
-								int stepIndex = i;
-								// if (i > 3)
-								//	stepIndex = i - 3;
-								cost = MaxEnergy * (baseCostScale + costStep * stepIndex);
-								// 确保成本不超过MaxEnergy
-								cost = std::min(cost, MaxEnergy);
-								// cost = MaxEnergy;
-								inference.SetDataCost(label, f, cost);
-							}
-						}
 				
-					} else {
 				for (const FaceData& fd : faceDatas) {
-							const Label label = (Label)fd.idxView + 1;
+					// 跳过无效视图（根据你的需求决定是否跳过）
-							const float normalizedQuality = fd.quality / normQuality;
+					if (fd.bInvalidFacesRelative) {
-							const float cost = (1.f - normalizedQuality) * MaxEnergy;
+						// 如果没有有效视图，才考虑无效视图
-							inference.SetDataCost(label, f, cost);
+						if (bestView == NO_ID) {
-						}
+							bestView = fd.idxView;
-					}
+							bestQuality = fd.quality;
-				}
+							bBestIsInvalid = true;
-				//*/
- 
-				// assign the optimal view (label) to each face
-				// (label 0 is reserved as undefined)
-				inference.Optimize();
-
-				// extract resulting labeling
-				labels.Memset(0xFF);
-				FOREACH(l, labels) {
-					const Label label(inference.GetLabel(l));
-					ASSERT(label < images.size()+1);
-					if (label > 0)
-						labels[l] = label-1;
 						}
-				#endif
-
-				#if TEXOPT_INFERENCE == TEXOPT_INFERENCE_TRWS
-				// find connected components
-				ASSERT((FIndex)boost::num_vertices(graph) == faces.size());
-				components.resize(faces.size());
-				const FIndex nComponents(boost::connected_components(graph, components.data()));
-
-				// map face ID from global to component space
-				typedef cList<NodeID, NodeID, 0, 128, NodeID> NodeIDs;
-				NodeIDs nodeIDs(faces.size());
-				NodeIDs sizes(nComponents);
-				sizes.Memset(0);
-				FOREACH(c, components)
-					nodeIDs[c] = sizes[components[c]]++;
-
-				// initialize inference structures
-				const LabelID numLabels(images.size()+1);
-				CLISTDEFIDX(TRWSInference, FIndex) inferences(nComponents);
-				FOREACH(s, sizes) {
-					const NodeID numNodes(sizes[s]);
-					ASSERT(numNodes > 0);
-					if (numNodes <= 1)
 						continue;
-					TRWSInference& inference = inferences[s];
-					inference.Init(numNodes, numLabels);
 					}
 					
-				// set data costs
+					if (fd.quality > bestQuality) {
-				{
+						bestQuality = fd.quality;
-					// add nodes
+						bestView = fd.idxView;
-					CLISTDEF0(EnergyType) D(numLabels);
+						bBestIsInvalid = false;
-					FOREACH(f, facesDatas) {
-						TRWSInference& inference = inferences[components[f]];
-						if (inference.IsEmpty())
-							continue;
-						D.MemsetValue(MaxEnergy);
-						const FaceDataArr& faceDatas = facesDatas[f];
-						for (const FaceData& faceData: faceDatas) {
-							const Label label((Label)faceData.idxView);
-							const float normalizedQuality(faceData.quality>=normQuality ? 1.f : faceData.quality/normQuality);
-							const EnergyType dataCost(MaxEnergy*(1.f-normalizedQuality));
-							D[label] = dataCost;
-						}
-						const NodeID nodeID(nodeIDs[f]);
-						inference.AddNode(nodeID, D.Begin());
-					}
-					// add edges
-					EdgeOutIter ei, eie;
-					FOREACH(f, faces) {
-						TRWSInference& inference = inferences[components[f]];
-						if (inference.IsEmpty())
-							continue;
-						for (boost::tie(ei, eie) = boost::out_edges(f, graph); ei != eie; ++ei) {
-							ASSERT(f == (FIndex)ei->m_source);
-							const FIndex fAdj((FIndex)ei->m_target);
-							ASSERT(components[f] == components[fAdj]);
-							if (f < fAdj) // add edges only once
-								inference.AddEdge(nodeIDs[f], nodeIDs[fAdj]);
-						}
 					}
 				}
 				
-				// assign the optimal view (label) to each face
+				labels[f] = bestView;
-				#ifdef TEXOPT_USE_OPENMP
+				if (bBestIsInvalid) {
-				#pragma omp parallel for schedule(dynamic)
+					labelsInvalid[f] = bestView;
-				for (int i=0; i<(int)inferences.size(); ++i) {
-				#else
-				FOREACH(i, inferences) {
-				#endif
-					TRWSInference& inference = inferences[i];
-					if (inference.IsEmpty())
-						continue;
-					inference.Optimize();
-				}
-				// extract resulting labeling
-				labels.Memset(0xFF);
-				FOREACH(l, labels) {
-					TRWSInference& inference = inferences[components[l]];
-					if (inference.IsEmpty())
-						continue;
-					const Label label(inference.GetLabel(nodeIDs[l]));
-					ASSERT(label >= 0 && label < numLabels);
-					if (label < images.size())
-						labels[l] = label;
 				}
-				#endif
 			}
 		}