FIX:fix bugs of algo and read quad in obj file

Jira: STUDIO-6805
Change-Id: I6c33e8197225f27dccdfa0681e64d76d1df14f61

src/libslic3r/Format/OBJ.cpp

@@ -165,12 +165,7 @@ bool load_obj(const char *path, TriangleMesh *meshptr, ObjInfo& obj_info, std::s
                     } else {
                         for (size_t k = 0; k < data.usemtls.size(); k++) {
                             auto mtl = data.usemtls[k];
-                            if (mtl.vertexIdxEnd == -1 && face_index >= (mtl.vertexIdxFirst / ONE_FACE_SIZE)) {
+                            if (face_index >= mtl.face_start && face_index <= mtl.face_end) {
-                                set_face_color(face_index, data.usemtls[k].name);
-                                break;
-                            } else if (mtl.vertexIdxEnd != -1 &&
-                                face_index >= (mtl.vertexIdxFirst / ONE_FACE_SIZE)
-                                && face_index < (mtl.vertexIdxEnd / ONE_FACE_SIZE)) {
                                 set_face_color(face_index, data.usemtls[k].name);
                                 break;
                             }

src/libslic3r/Format/objparser.cpp

@@ -251,6 +251,24 @@ static bool obj_parseline(const char *line, ObjData &data)
 			data.vertices.push_back(vertex);
 			EATWS();
 		}
+        if (data.usemtls.size() > 0) {
+			data.usemtls.back().vertexIdxEnd = (int) data.vertices.size();
+		}
+        if (data.usemtls.size() > 0) {
+            int face_index_count = 0;
+            for (int i = data.vertices.size() - 1; i >= 0; i--) {
+                if (data.vertices[i].coordIdx == -1) {
+					break;
+				}
+                face_index_count++;
+            }
+            if (face_index_count == 3) {//tri
+                data.usemtls.back().face_end++;
+			} else if (face_index_count == 4) {//quad
+                data.usemtls.back().face_end++;
+                data.usemtls.back().face_end++;
+			}
+        }
 		vertex.coordIdx			= -1;
 		vertex.normalIdx		= -1;
 		vertex.textureCoordIdx	= -1;
@@ -289,6 +307,16 @@ static bool obj_parseline(const char *line, ObjData &data)
         usemtl.vertexIdxFirst = (int)data.vertices.size();
         usemtl.name = line;
 		data.usemtls.push_back(usemtl);
+        if (data.usemtls.size() == 1) {
+            data.usemtls.back().face_start = 0;
+		}
+		else {//>=2
+            auto count       = data.usemtls.size();
+            auto& last_usemtl = data.usemtls[count-1];
+            auto& last_last_usemtl  = data.usemtls[count - 2];
+            last_usemtl.face_start = last_last_usemtl.face_end + 1;
+		}
+        data.usemtls.back().face_end = data.usemtls.back().face_start - 1;
 		break;
 	}
 	case 'o':

src/libslic3r/Format/objparser.hpp

@@ -27,6 +27,8 @@ struct ObjUseMtl
 {
 	int			vertexIdxFirst;
     int         vertexIdxEnd{-1};
+    int         face_start;
+    int         face_end{-1};
 	std::string name;
 };
 

src/libslic3r/ObjColorUtils.hpp

@@ -57,16 +57,19 @@ public:
         convert_color_space(flatten_image8UC3, image8UC3, color_space);
 
         cv::Mat image32FC3(image8UC3.rows, 1, CV_32FC3);
-        for (int i = 0; i < image8UC3.rows; i++) image32FC3.at<cv::Vec3f>(i, 0) = image8UC3.at<cv::Vec3b>(i, 0);
+        for (int i = 0; i < image8UC3.rows; i++)
+            image32FC3.at<cv::Vec3f>(i, 0) = image8UC3.at<cv::Vec3b>(i, 0);
 
-        int best_cluster = 1, cur_score = 0, best_score = 100;
+        int best_cluster = 1;
+        double cur_score, best_score = 100;
         int max_cluster = ori_colors.size();
         num_cluster     = fmin(num_cluster, max_cluster);
         if (num_cluster < 1) {
             cur_score  = kmeans(image32FC3, 1, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3, cv::KMEANS_PP_CENTERS);
             best_score = cur_score;
             for (int cur_cluster = 2; cur_cluster < 16; cur_cluster++) {
-                if (cur_cluster > max_cluster) break;
+                if (cur_cluster > max_cluster)
+                    break;
                 cur_score    = kmeans(image32FC3, cur_cluster, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3,
                                    cv::KMEANS_PP_CENTERS);
                 best_cluster = cur_score < best_score ? cur_cluster : best_cluster;
@@ -79,7 +82,8 @@ public:
         kmeans(image32FC3, best_cluster, this->m_flatten_labels, cv::TermCriteria(cv::TermCriteria::EPS + cv::TermCriteria::COUNT, 300, 0.5), 3, cv::KMEANS_PP_CENTERS,
                centers32FC3);
         this->m_centers8UC3 = cv::Mat(best_cluster, 1, CV_8UC3);
-        for (int i = 0; i < best_cluster; i++) this->m_centers8UC3.at<cv::Vec3b>(i) = centers32FC3.at<cv::Vec3f>(i);
+        for (int i = 0; i < best_cluster; i++)
+            this->m_centers8UC3.at<cv::Vec3b>(i) = centers32FC3.at<cv::Vec3f>(i);
 
         convert_color_space(this->m_centers8UC3, this->m_centers8UC3, color_space, true);