From 6a2be3ab5010e95fc0d8548ea32485b3bdf039a9 Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Thu, 26 Nov 2020 23:19:50 +0800
Subject: [PATCH 1/7] =?UTF-8?q?=E7=9B=B4=E7=BA=BF=E6=A3=80=E6=B5=8B?=
 =?UTF-8?q?=E5=8F=98=E6=88=90=EF=BC=9A=E5=85=88=E6=A3=80=E6=B5=8B=E5=AE=9E?=
 =?UTF-8?q?=E7=BA=BF=E3=80=81=E5=86=8D=E6=A3=80=E6=B5=8B=E5=85=B3=E7=B3=BB?=
 =?UTF-8?q?=E7=B1=BB=E5=9E=8B=E3=80=81=E5=86=8D=E6=A3=80=E6=B5=8B=E8=99=9A?=
 =?UTF-8?q?=E7=BA=BF?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../uct/umlrecog/UMLDiagramRecognizer.java    |  2 +-
 .../umlrecog/cddetector/ClassDetector.java    | 14 +++--
 .../cddetector/ClassRelationDetector.java     | 53 ++++++++++---------
 3 files changed, 38 insertions(+), 31 deletions(-)

diff --git a/src/main/java/com/hy/java/uct/umlrecog/UMLDiagramRecognizer.java b/src/main/java/com/hy/java/uct/umlrecog/UMLDiagramRecognizer.java
index 48d9e14..dfdbf4b 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/UMLDiagramRecognizer.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/UMLDiagramRecognizer.java
@@ -33,7 +33,7 @@ public class UMLDiagramRecognizer {
 	 * 测试一下识别特定的类图和顺序图
 	 */
 	public static void main(String[] args) {
-		UMLDiagramRecognizer.recogCD(cd_dir, "Team-MWSU/GroupProject");
+		UMLDiagramRecognizer.recogCD(cd_dir, "Salaboy/smart-tasks");
 		UMLDiagramRecognizer.recogSD(sd_dir, "albanoj2/grp");
 	}
 }
diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java
index 551c2fe..56bf8e7 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java
@@ -98,7 +98,7 @@ public class ClassDetector {
 			}
 		}
 		// 对所有矩形边框进行涂白，防止其干扰关系符号和关系线识别
-		Imgproc.drawContours(cls_diagram, rect_contours, -1, new Scalar(255, 255, 255), 4);
+		Imgproc.drawContours(cls_diagram, rect_contours, -1, new Scalar(255, 255, 255), 5);
 		// 此时的cls_diagram中矩形已涂白
 		return Pair.createPair(cls_diagram, all_rect_areas);
 	}
@@ -203,10 +203,14 @@ public class ClassDetector {
 				// 将uc中的每个区域写入临时文件，然后识别临时文件中的文字
 				Imgcodecs.imwrite(temp_res_path, uc.top.getMat());
 				uc.setTitle(instance.doOCR(new File(temp_res_path)));
-				Imgcodecs.imwrite(temp_res_path, uc.mid.getMat());
-				uc.setAttrisStr(instance.doOCR(new File(temp_res_path)));
-				Imgcodecs.imwrite(temp_res_path, uc.bottom.getMat());
-				uc.setMethodsStr(instance.doOCR(new File(temp_res_path)));
+				if (uc.mid != null) {
+					Imgcodecs.imwrite(temp_res_path, uc.mid.getMat());
+					uc.setAttrisStr(instance.doOCR(new File(temp_res_path)));
+				}
+				if (uc.bottom != null) {
+					Imgcodecs.imwrite(temp_res_path, uc.bottom.getMat());
+					uc.setMethodsStr(instance.doOCR(new File(temp_res_path)));
+				}
 			} catch (TesseractException e) {
 				// TODO Auto-generated catch block
 				e.printStackTrace();
diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
index e73382a..7ae1fd9 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
@@ -27,10 +27,33 @@ public class ClassRelationDetector {
 	}
 
 	public void recog() {
-		// 先检测关系类型检测
-		Mat temp = detectRelationType(classes_in_cd, 0.000555);
-		// 再检测关系线
-		// detectLines(temp);
+		// 先检测实线
+		detectLines(classes_in_cd.getLeft());
+		// 再检测关系类型检测
+		// Mat temp = detectRelationType(classes_in_cd, 0.00002);
+		// 最后再检测虚线
+		// detectLines(classes_in_cd.getLeft());
+	}
+
+	private void detectLines(Mat src) {
+		// TODO Auto-generated method stub
+		System.out.println("识别关系");
+		// 先检测边缘。然后从边缘集中检测直线
+		Mat canny = new Mat();
+		Imgproc.Canny(src, canny, 50, 150, 3, true);
+		// 从边缘集中检测直线
+		Mat lines = new Mat();
+		// 这些步长可有的调了。得按像素来
+		Imgproc.HoughLinesP(canny, lines, 1, Math.PI / 180, 12, 17, 5);
+		// 将检测到的直线绘制到图中
+		for (int i = 0; i < lines.rows(); i++) {
+			Point pt1 = new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]);
+			Point pt2 = new Point(lines.get(i, 0)[2], lines.get(i, 0)[3]);
+			Imgproc.line(src, pt1, pt2, new Scalar(187, 255, 255), 1);
+		}
+		// Writing the image
+		Imgcodecs.imwrite(temp_res_path, src);
+		System.out.println("识别关系完毕，共" + lines.rows() + "条");
 	}
 
 	/**
@@ -74,33 +97,13 @@ public class ClassRelationDetector {
 			Imgproc.fillConvexPoly(classes_in_cd.getLeft(), contour, new Scalar(15, 225, 25));
 		}
 		// 对所有边框进行涂白
-		Imgproc.drawContours(classes_in_cd.getLeft(), rela_shapes, -1, new Scalar(255, 255, 255), 8);
+		Imgproc.drawContours(classes_in_cd.getLeft(), rela_shapes, -1, new Scalar(15, 225, 25), 1);
 		// 将图片写入result文件
 		Imgcodecs.imwrite(temp_res_path, classes_in_cd.getLeft());
 		System.out.println("识别关系符号完毕，共" + rela_shapes.size() + "个");
 		return classes_in_cd.getLeft();
 	}
 
-	private void detectLines(Mat src) {
-		// TODO Auto-generated method stub
-		System.out.println("识别关系");
-		// 先检测边缘。然后从边缘集中检测直线
-		Mat canny = new Mat();
-		Imgproc.Canny(src, canny, 50, 150, 3, true);
-		// 从边缘集中检测直线
-		Mat lines = new Mat();
-		Imgproc.HoughLinesP(canny, lines, 1, Math.PI / 4, 12, 17, 20);
-		// 将检测到的直线绘制到图中
-		for (int i = 0; i < lines.rows(); i++) {
-			Point pt1 = new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]);
-			Point pt2 = new Point(lines.get(i, 0)[2], lines.get(i, 0)[3]);
-			Imgproc.line(src, pt1, pt2, new Scalar(187, 255, 255), 2);
-		}
-		// Writing the image
-		Imgcodecs.imwrite("D:\\eclipse-committers\\uml-code-trace\\src\\test\\resources\\result.png", src);
-		System.out.println("识别关系完毕，共" + lines.rows() + "条");
-	}
-
 	public Object getResult() {
 		return result;
 	}
-- 
Gitee


From 3925515072a7474f03da976ea9236e5a6529fb1a Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Fri, 27 Nov 2020 21:02:28 +0800
Subject: [PATCH 2/7] =?UTF-8?q?=E5=AE=9E=E7=BA=BF=E6=A3=80=E6=B5=8B?=
 =?UTF-8?q?=E5=B0=8F=E4=BF=AE?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../cddetector/ClassRelationDetector.java     |  22 ++++++++----------
 src/main/resources/cd/temp result.png         | Bin 5383 -> 8779 bytes
 2 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
index 7ae1fd9..d4be5a9 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
@@ -28,32 +28,30 @@ public class ClassRelationDetector {
 
 	public void recog() {
 		// 先检测实线
-		detectLines(classes_in_cd.getLeft());
+		detectSolidLines(classes_in_cd.getLeft());
 		// 再检测关系类型检测
 		// Mat temp = detectRelationType(classes_in_cd, 0.00002);
 		// 最后再检测虚线
 		// detectLines(classes_in_cd.getLeft());
 	}
 
-	private void detectLines(Mat src) {
-		// TODO Auto-generated method stub
-		System.out.println("识别关系");
+	private void detectSolidLines(Mat cls_diagram) {
+		System.out.println("识别实线");
 		// 先检测边缘。然后从边缘集中检测直线
-		Mat canny = new Mat();
-		Imgproc.Canny(src, canny, 50, 150, 3, true);
-		// 从边缘集中检测直线
+		Mat edges = new Mat();
+		Imgproc.Canny(cls_diagram, edges, 50, 150, 3, true);
+		// 从边缘集中检测直线。实线检测时，“最大像素间隔”越小越准确
 		Mat lines = new Mat();
-		// 这些步长可有的调了。得按像素来
-		Imgproc.HoughLinesP(canny, lines, 1, Math.PI / 180, 12, 17, 5);
+		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, 17, 5);
 		// 将检测到的直线绘制到图中
 		for (int i = 0; i < lines.rows(); i++) {
 			Point pt1 = new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]);
 			Point pt2 = new Point(lines.get(i, 0)[2], lines.get(i, 0)[3]);
-			Imgproc.line(src, pt1, pt2, new Scalar(187, 255, 255), 1);
+			Imgproc.line(cls_diagram, pt1, pt2, new Scalar(55, 55, 55), 1);
 		}
 		// Writing the image
-		Imgcodecs.imwrite(temp_res_path, src);
-		System.out.println("识别关系完毕，共" + lines.rows() + "条");
+		Imgcodecs.imwrite(temp_res_path, cls_diagram);
+		System.out.println("识别实线完毕，共" + lines.rows() + "条");
 	}
 
 	/**
diff --git a/src/main/resources/cd/temp result.png b/src/main/resources/cd/temp result.png
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-- 
Gitee


From b2a3161593b03b22fb2a8b4b1a537ed74aa42d3b Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Fri, 27 Nov 2020 21:16:31 +0800
Subject: [PATCH 3/7] =?UTF-8?q?=E5=83=8F=E7=B4=A0=E9=97=B4=E9=9A=94?=
 =?UTF-8?q?=E5=8F=82=E6=95=B0=E8=B0=83=E6=95=B4?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../umlrecog/cddetector/ClassRelationDetector.java | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
index d4be5a9..840502f 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
@@ -28,26 +28,30 @@ public class ClassRelationDetector {
 
 	public void recog() {
 		// 先检测实线
-		detectSolidLines(classes_in_cd.getLeft());
+		detectSolidLines(classes_in_cd.getLeft(), 0.00003025);
 		// 再检测关系类型检测
 		// Mat temp = detectRelationType(classes_in_cd, 0.00002);
 		// 最后再检测虚线
 		// detectLines(classes_in_cd.getLeft());
 	}
 
-	private void detectSolidLines(Mat cls_diagram) {
+	private void detectSolidLines(Mat cls_diagram, double ratio) {
 		System.out.println("识别实线");
 		// 先检测边缘。然后从边缘集中检测直线
 		Mat edges = new Mat();
 		Imgproc.Canny(cls_diagram, edges, 50, 150, 3, true);
-		// 从边缘集中检测直线。实线检测时，“最大像素间隔”越小越准确
+		// 从边缘集中检测直线。实线检测时，“最大像素间隔”越小，要求像素连接越密集
 		Mat lines = new Mat();
-		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, 17, 5);
+		int cd_width = cls_diagram.width();
+		int cd_height = cls_diagram.height();
+		long cd_area = cd_width * cd_height;
+		double min_line_length = cd_area * ratio;
+		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, min_line_length, 3);
 		// 将检测到的直线绘制到图中
 		for (int i = 0; i < lines.rows(); i++) {
 			Point pt1 = new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]);
 			Point pt2 = new Point(lines.get(i, 0)[2], lines.get(i, 0)[3]);
-			Imgproc.line(cls_diagram, pt1, pt2, new Scalar(55, 55, 55), 1);
+			Imgproc.line(cls_diagram, pt1, pt2, new Scalar(55, 55, 55), 5);
 		}
 		// Writing the image
 		Imgcodecs.imwrite(temp_res_path, cls_diagram);
-- 
Gitee


From 9a6db276771fe34963d509d3f79dcdc76a76ad20 Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Fri, 27 Nov 2020 21:24:31 +0800
Subject: [PATCH 4/7] =?UTF-8?q?=E8=B0=83=E5=8F=82?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../umlrecog/cddetector/ClassDetector.java    |   4 +---
 .../cddetector/ClassRelationDetector.java     |  10 ++++------
 src/main/resources/cd/temp result.png         | Bin 8779 -> 7724 bytes
 3 files changed, 5 insertions(+), 9 deletions(-)

diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java
index 56bf8e7..498a20b 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassDetector.java
@@ -73,9 +73,7 @@ public class ClassDetector {
 		// 这个rect_contours里只存那些检测结果为矩形的contour，用于后面边框涂白，防止矩形干扰关系符号和关系线识别
 		List<MatOfPoint> rect_contours = new ArrayList<>();
 		// 根据图片像素计算轮廓面积阈值。如果轮廓面积太小或太大，则直接忽略
-		int cd_width = cls_diagram.width();
-		int cd_height = cls_diagram.height();
-		long cd_area = cd_width * cd_height;
+		long cd_area = cls_diagram.width() * cls_diagram.height();
 		double min_cls_area = cd_area * ratio;
 		double max_cls_area = cd_area * 0.5;
 		for (MatOfPoint contour : contours) {
diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
index 840502f..b275e74 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
@@ -28,7 +28,7 @@ public class ClassRelationDetector {
 
 	public void recog() {
 		// 先检测实线
-		detectSolidLines(classes_in_cd.getLeft(), 0.00003025);
+		detectSolidLines(classes_in_cd.getLeft(), 0.0505);
 		// 再检测关系类型检测
 		// Mat temp = detectRelationType(classes_in_cd, 0.00002);
 		// 最后再检测虚线
@@ -42,11 +42,9 @@ public class ClassRelationDetector {
 		Imgproc.Canny(cls_diagram, edges, 50, 150, 3, true);
 		// 从边缘集中检测直线。实线检测时，“最大像素间隔”越小，要求像素连接越密集
 		Mat lines = new Mat();
-		int cd_width = cls_diagram.width();
-		int cd_height = cls_diagram.height();
-		long cd_area = cd_width * cd_height;
-		double min_line_length = cd_area * ratio;
-		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, min_line_length, 3);
+		double min_line_length_width = cls_diagram.width() * ratio;
+		double min_line_length_height = cls_diagram.height() * ratio;
+		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, Math.min(min_line_length_width, min_line_length_height), 3);
 		// 将检测到的直线绘制到图中
 		for (int i = 0; i < lines.rows(); i++) {
 			Point pt1 = new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]);
diff --git a/src/main/resources/cd/temp result.png b/src/main/resources/cd/temp result.png
index 4e04dc1d1e0963823d878a297d4975d30e596878..172a35d8bc910b4842721dbf4c96c79e14160b35 100644
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hwe|nPze~(T-#<8H=!rRm{%wRN-nn~6&-QHPe*rV*fj$5L

-- 
Gitee


From 9ee25253b9d51a1a8c3a042609605a80542712ab Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Mon, 30 Nov 2020 22:28:04 +0800
Subject: [PATCH 5/7] =?UTF-8?q?=E7=9B=B4=E7=BA=BF=E6=A3=80=E6=B5=8B?=
 =?UTF-8?q?=E4=BF=9D=E5=AD=98=E6=89=80=E6=9C=89=E5=88=9A=E6=A3=80=E6=B5=8B?=
 =?UTF-8?q?=E5=87=BA=E6=9D=A5=E7=9A=84=E2=80=9C=E5=8E=9F=E5=A7=8B=E7=9B=B4?=
 =?UTF-8?q?=E7=BA=BF=E2=80=9D=EF=BC=8C=E5=B9=B6=E5=BC=80=E5=A7=8B=E5=AF=B9?=
 =?UTF-8?q?=E2=80=9C=E5=8E=9F=E5=A7=8B=E7=9B=B4=E7=BA=BF=E2=80=9D=E5=81=9A?=
 =?UTF-8?q?=E5=A4=84=E7=90=86?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../cddetector/ClassRelationDetector.java     | 36 ++++++++++++-------
 1 file changed, 24 insertions(+), 12 deletions(-)

diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
index b275e74..ccf2ebf 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
@@ -11,6 +11,7 @@ import org.opencv.core.Scalar;
 import org.opencv.imgcodecs.Imgcodecs;
 import org.opencv.imgproc.Imgproc;
 
+import com.hy.java.uct.umlrecog.util.Line;
 import com.hy.java.uct.umlrecog.util.UMLClass;
 import com.hy.java.utility.common.Pair;
 
@@ -35,25 +36,36 @@ public class ClassRelationDetector {
 		// detectLines(classes_in_cd.getLeft());
 	}
 
-	private void detectSolidLines(Mat cls_diagram, double ratio) {
-		System.out.println("识别实线");
+	private List<Line> detectSolidLines(Mat cls_diagram, double ratio) {
+		System.out.println("识别" + cd_path + "中的实线");
+		List<Line> result = new ArrayList<>();
+		/*
+		 * 先检测边缘，然后从边缘集中初步检测“原始直线”
+		 */
 		// 先检测边缘。然后从边缘集中检测直线
 		Mat edges = new Mat();
-		Imgproc.Canny(cls_diagram, edges, 50, 150, 3, true);
-		// 从边缘集中检测直线。实线检测时，“最大像素间隔”越小，要求像素连接越密集
+		Imgproc.Canny(cls_diagram, edges, 50, 50 * 3, 3, true);
+		// 从边缘集中检测直线。实线检测时，“最大像素间隔”（与图像像素做比）越小，要求像素连接越密集
 		Mat lines = new Mat();
-		double min_line_length_width = cls_diagram.width() * ratio;
-		double min_line_length_height = cls_diagram.height() * ratio;
-		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, Math.min(min_line_length_width, min_line_length_height), 3);
-		// 将检测到的直线绘制到图中
+		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, Math.min(cls_diagram.width() * ratio, cls_diagram.height() * ratio), 3);
+		// 保存所有刚检测出来的“原始直线”
 		for (int i = 0; i < lines.rows(); i++) {
-			Point pt1 = new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]);
-			Point pt2 = new Point(lines.get(i, 0)[2], lines.get(i, 0)[3]);
-			Imgproc.line(cls_diagram, pt1, pt2, new Scalar(55, 55, 55), 5);
+			result.add(new Line(new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]), new Point(lines.get(i, 0)[2], lines.get(i, 0)[3])));
+		}
+		/*
+		 * 对“原始直线”进行处理，校正关系线对象Line的信息
+		 */
+		// “原始直线”中存在“两端都接近”的情况，将其算为一条线
+		for (Line l : result) {
+			if (l.isNear(null)) {
+				result.remove(l);
+			}
+			Imgproc.line(cls_diagram, l.pt1, l.pt2, new Scalar(55, 55, 55), 1);
 		}
 		// Writing the image
 		Imgcodecs.imwrite(temp_res_path, cls_diagram);
-		System.out.println("识别实线完毕，共" + lines.rows() + "条");
+		System.out.println("识别实线完毕，共" + result.size() + "条");
+		return result;
 	}
 
 	/**
-- 
Gitee


From b07ddcee1b6485110aca55c9c899cbe22a09bb55 Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Mon, 30 Nov 2020 22:28:28 +0800
Subject: [PATCH 6/7] =?UTF-8?q?=E8=A1=A5=E5=85=85=E4=B8=8E=E7=9B=B4?=
 =?UTF-8?q?=E7=BA=BF=E6=9C=89=E5=85=B3=E7=9A=84=E7=B1=BBLine?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../com/hy/java/uct/umlrecog/util/Line.java   |  19 ++++++++++++++++++
 src/main/resources/cd/temp result.png         | Bin 7724 -> 7897 bytes
 2 files changed, 19 insertions(+)
 create mode 100644 src/main/java/com/hy/java/uct/umlrecog/util/Line.java

diff --git a/src/main/java/com/hy/java/uct/umlrecog/util/Line.java b/src/main/java/com/hy/java/uct/umlrecog/util/Line.java
new file mode 100644
index 0000000..da92e1c
--- /dev/null
+++ b/src/main/java/com/hy/java/uct/umlrecog/util/Line.java
@@ -0,0 +1,19 @@
+package com.hy.java.uct.umlrecog.util;
+
+import org.opencv.core.Point;
+
+public class Line {
+	public Point pt1;
+	public Point pt2;
+
+	public Line(Point pt1, Point pt2) {
+		this.pt1 = pt1;
+		this.pt2 = pt2;
+	}
+
+	public boolean isNear(Line line) {
+		boolean result = false;
+		
+		return result;
+	}
+}
diff --git a/src/main/resources/cd/temp result.png b/src/main/resources/cd/temp result.png
index 172a35d8bc910b4842721dbf4c96c79e14160b35..7da472524d9f0ce08b3fdf18669215046df8940c 100644
GIT binary patch
literal 7897
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-- 
Gitee


From aabc962462963c4047fb7d490266f6bea9a8990c Mon Sep 17 00:00:00 2001
From: chief <chief@CFW-P65>
Date: Wed, 2 Dec 2020 23:40:38 +0800
Subject: [PATCH 7/7] =?UTF-8?q?=E5=AE=9E=E7=BA=BF=E6=A3=80=E6=B5=8B?=
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---
 .../cddetector/ClassRelationDetector.java     |  43 ++++++++++---
 .../com/hy/java/uct/umlrecog/util/Line.java   |  57 +++++++++++++++++-
 src/main/resources/cd/temp result.png         | Bin 7897 -> 7310 bytes
 3 files changed, 91 insertions(+), 9 deletions(-)

diff --git a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
index ccf2ebf..3afcfc4 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/cddetector/ClassRelationDetector.java
@@ -29,7 +29,7 @@ public class ClassRelationDetector {
 
 	public void recog() {
 		// 先检测实线
-		detectSolidLines(classes_in_cd.getLeft(), 0.0505);
+		List<Line> solid_lines = detectSolidLines(classes_in_cd.getLeft(), 0.0505);
 		// 再检测关系类型检测
 		// Mat temp = detectRelationType(classes_in_cd, 0.00002);
 		// 最后再检测虚线
@@ -45,7 +45,7 @@ public class ClassRelationDetector {
 		// 先检测边缘。然后从边缘集中检测直线
 		Mat edges = new Mat();
 		Imgproc.Canny(cls_diagram, edges, 50, 50 * 3, 3, true);
-		// 从边缘集中检测直线。实线检测时，“最大像素间隔”（与图像像素做比）越小，要求像素连接越密集
+		// 从边缘集中检测直线。实线检测时，“最小直线长度”与图像像素有关；“最大像素间隔”越小越接近实线
 		Mat lines = new Mat();
 		Imgproc.HoughLinesP(edges, lines, 1, Math.PI / 180, 12, Math.min(cls_diagram.width() * ratio, cls_diagram.height() * ratio), 3);
 		// 保存所有刚检测出来的“原始直线”
@@ -53,13 +53,37 @@ public class ClassRelationDetector {
 			result.add(new Line(new Point(lines.get(i, 0)[0], lines.get(i, 0)[1]), new Point(lines.get(i, 0)[2], lines.get(i, 0)[3])));
 		}
 		/*
-		 * 对“原始直线”进行处理，校正关系线对象Line的信息
+		 * 检查“原始直线”集中是否有重合直线，去除冗余或合并
 		 */
-		// “原始直线”中存在“两端都接近”的情况，将其算为一条线
-		for (Line l : result) {
-			if (l.isNear(null)) {
-				result.remove(l);
+		int current_size = result.size();
+		for (int i = 0; i < current_size; i++) {
+			Line line = result.get(i);
+			// 将line与other_line做比较
+			for (int j = i + 1; j < current_size; j++) {
+				Line other_line = result.get(j);
+				// “原始直线”中存在“两端都接近”的情况，将其算为一条线；或其中一端接近、且两直线斜率接近，则合并两直线
+				if (line.near(other_line)) {
+					other_line.should_be_del = true;
+				}
+			}
+			// 去除冗余；合并同斜率
+			for (int j = i + 1; j < current_size;) {
+				Line other_line = result.get(j);
+				if (other_line.should_be_del) {
+					if (other_line.merge_with != null) {
+						// 合并同斜率
+						mergeKNearLines(line, other_line);
+					}
+					// 去除冗余
+					result.remove(other_line);
+					current_size = result.size();
+				} else {
+					j++;
+				}
 			}
+		}
+		for (Line l : result) {
+			System.out.println("(" + l.pt1.x + ", " + l.pt1.y + ")" + "(" + l.pt2.x + ", " + l.pt2.y + ")");
 			Imgproc.line(cls_diagram, l.pt1, l.pt2, new Scalar(55, 55, 55), 1);
 		}
 		// Writing the image
@@ -68,6 +92,11 @@ public class ClassRelationDetector {
 		return result;
 	}
 
+	// 将斜率接近的两条直线合并成“最长”的一条线，并存在line中
+	private void mergeKNearLines(Line line, Line other_line) {
+		// 这TM怎么合并啊？！！
+	}
+
 	/**
 	 * 识别关系符号
 	 * 
diff --git a/src/main/java/com/hy/java/uct/umlrecog/util/Line.java b/src/main/java/com/hy/java/uct/umlrecog/util/Line.java
index da92e1c..4224daa 100644
--- a/src/main/java/com/hy/java/uct/umlrecog/util/Line.java
+++ b/src/main/java/com/hy/java/uct/umlrecog/util/Line.java
@@ -5,15 +5,68 @@ import org.opencv.core.Point;
 public class Line {
 	public Point pt1;
 	public Point pt2;
+	public boolean should_be_del = false;
+	public Line merge_with = null;
 
 	public Line(Point pt1, Point pt2) {
 		this.pt1 = pt1;
 		this.pt2 = pt2;
 	}
 
-	public boolean isNear(Line line) {
+	/**
+	 * 判断一条直线是否与另一条直线重合
+	 */
+	public boolean near(Line line) {
 		boolean result = false;
-		
+		// 如果该直线的每个端点都与另一条直线重合，则该直线与另一条直线重合
+		if (ptNearLine(pt1, line) && ptNearLine(pt2, line)) {
+			result = true;
+		}
+		// 或者该直线某一个端点与另一条直线重合，且两条直线斜率接近，则也认为两条直线重合
+		else {
+			// 先判断该直线是否存在某一个端点与另一条直线重合
+			if (ptNearLine(pt1, line) || ptNearLine(pt2, line)) {
+				// 再判断是否斜率接近
+				if (Line.getK(this) == "无穷大" || Line.getK(line) == "无穷大") {
+					if (Line.getK(this) == Line.getK(line)) {
+						line.merge_with = this;
+						result = true;
+					}
+				} else if (Math.abs(Double.parseDouble(getK(this)) - Double.parseDouble(getK(line))) <= 0.5) {
+					line.merge_with = this;
+					result = true;
+				}
+			}
+		}
 		return result;
 	}
+
+	private static String getK(Line line) {
+		if (line.pt1.x == line.pt2.x) {
+			return "无穷大";
+		} else {
+			return String.valueOf((line.pt2.y - line.pt1.y) / (line.pt2.x - line.pt1.x));
+		}
+	}
+
+	private boolean ptNearLine(Point pt, Line line) {
+		boolean result = false;
+		// 如果该端点与另一条直线的某一个端点接近，则认为该端点与另一条直线重合
+		if (ptNearPt(pt, line.pt1) || ptNearPt(pt, line.pt2)) {
+			result = true;
+		}
+		return result;
+	}
+
+	private boolean ptNearPt(Point p1, Point p2) {
+		boolean x_near = false;
+		boolean y_near = false;
+		if (Math.abs(p1.x - p2.x) <= 3) {
+			x_near = true;
+		}
+		if (Math.abs(p1.y - p2.y) <= 3) {
+			y_near = true;
+		}
+		return x_near && y_near;
+	}
 }
diff --git a/src/main/resources/cd/temp result.png b/src/main/resources/cd/temp result.png
index 7da472524d9f0ce08b3fdf18669215046df8940c..16a319315b960adda0f266dd6af8642488dab69d 100644
GIT binary patch
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