├── README.md
├── img
    ├── prediction.jpg
    └── test.webp
├── pom.xml
├── requirements.txt
├── src
    └── main
    │   ├── java
    │       ├── sy
    │       │   ├── Detection.java
    │       │   ├── ImageUtil.java
    │       │   ├── MainTest.java
    │       │   └── ModelDet.java
    │       └── utils
    │       │   ├── CollectionUtil.java
    │       │   └── PropertiesReader.java
    │   └── resources
    │       ├── model
    │           ├── label.names
    │           └── model.onnx
    │       └── properties.properties
└── target
    └── classes
        ├── META-INF
            └── layout_analysis4j.kotlin_module
        ├── model
            ├── label.names
            └── model.onnx
        ├── properties.properties
        ├── sy
            ├── Detection.class
            ├── ImageUtil.class
            ├── MainTest.class
            └── ModelDet.class
        └── utils
            ├── CollectionUtil.class
            └── PropertiesReader.class


/README.md:
--------------------------------------------------------------------------------
 1 | ### 利用java-yolov8实现版面检测
 2 | 利用java加载yolov8模型，进行推理，以及前后处理均以java实现。
 3 | 
 4 | java-yolov8 is used to detect the layout of Chinese document images
 5 | 
 6 | #### 模型下载、推理
 7 | 本项目根据开源中文版面数据[CDLA](https://github.com/buptlihang/CDLA)  ，利用yolov8进行训练
 8 | 
 9 | CDLA是一个中文文档版面分析数据集，面向中文文献类（论文）场景。包含以下10个label：
10 | 
11 | |正文|标题|图片|图片标题|表格|表格标题|页眉|页脚|注释|公式|
12 | |---|---|---|---|---|---|---|---|---|---|
13 | |Text|Title|Figure|Figure caption|Table|Table caption|Header|Footer|Reference|Equation|
14 | 
15 | 模型下载：
16 | 
17 | 链接：https://pan.baidu.com/s/1cqMLPKcIOatXmCxmR3QnVQ 
18 | 
19 | 提取码：g39u
20 | 
21 | 推理：src/main/java/sy
22 | ```
23 | public static void main(String...args) {
24 |         String modelPath = MainTest.class.getClassLoader().getResource(PropertiesReader.get("model_path")).getPath().replaceFirst("/", "");
25 |         String labelPath = MainTest.class.getClassLoader().getResource(PropertiesReader.get("table_det_labels_path")).getPath().replaceFirst("/", "");
26 |         String imgPath = "D:\\project\\idea_workspace\\layout_analysis4j\\img\\test.webp";
27 | 
28 |         try {
29 |             ModelDet modelDet = new ModelDet(modelPath, labelPath);
30 |             Mat img = Imgcodecs.imread(imgPath);
31 |             if (img.dataAddr() == 0) {
32 |                 System.out.println("Could not open image: " + imgPath);
33 |                 System.exit(1);
34 |             }
35 |             // run detection
36 |             try {
37 |                 List<Detection> detectionList = modelDet.detectObjects(img);
38 | 
39 |                 ImageUtil.drawPredictions(img, detectionList);
40 |                 System.out.println(JSON.toJSONString(detectionList));
41 |                 Imgcodecs.imwrite("D:\\project\\idea_workspace\\layout_analysis4j\\img\\prediction.jpg", img);
42 |             } catch (OrtException ortException) {
43 |                 ortException.printStackTrace();
44 |             }
45 | 
46 |         } catch (OrtException e) {
47 |             e.printStackTrace();
48 |         }
49 |     }
50 | ```
51 | 
52 | <br/>
53 | <p align="center">
54 |   <a>
55 |     <img src="img/prediction.jpg">
56 |   </a>
57 | </p>
58 | <br/>
59 | 
60 | 
61 | #### contact
62 | 
63 | 1、github：https://github.com/jiangnanboy
64 | 
65 | 2、博客：https://www.cnblogs.com/little-horse/
66 | 
67 | 3、邮件:2229029156@qq.com
68 | 
69 | #### reference
70 | https://github.com/jiangnanboy/layout_analysis
71 | 
72 | https://github.com/ultralytics/ultralytics
73 | 
74 | https://github.com/buptlihang/CDLA
75 | 
76 | 


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/img/prediction.jpg:
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https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/img/prediction.jpg


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/img/test.webp:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/img/test.webp


--------------------------------------------------------------------------------
/pom.xml:
--------------------------------------------------------------------------------
 1 | <?xml version="1.0" encoding="UTF-8"?>
 2 | <project xmlns="http://maven.apache.org/POM/4.0.0"
 3 |          xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
 4 |          xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
 5 |     <modelVersion>4.0.0</modelVersion>
 6 | 
 7 |     <groupId>org.example</groupId>
 8 |     <artifactId>layout_analysis4j</artifactId>
 9 |     <version>1.0-SNAPSHOT</version>
10 | 
11 | <dependencies>
12 |     <dependency>
13 |         <groupId>com.microsoft.onnxruntime</groupId>
14 |         <artifactId>onnxruntime</artifactId>
15 |         <version>1.11.0</version>
16 |     </dependency>
17 | 
18 |     <dependency>
19 |         <groupId>com.alibaba.fastjson2</groupId>
20 |         <artifactId>fastjson2</artifactId>
21 |         <version>2.0.20</version>
22 |     </dependency>
23 | 
24 |     <dependency>
25 |         <groupId>org.bytedeco</groupId>
26 |         <artifactId>javacv-platform</artifactId>
27 |         <version>1.5.7</version>
28 |     </dependency>
29 | 
30 |     <dependency>
31 |         <groupId>org.bytedeco</groupId>
32 |         <artifactId>javacpp</artifactId>
33 |         <version>1.5.7</version>
34 |     </dependency>
35 | 
36 |     <dependency>
37 |         <groupId>org.bytedeco</groupId>
38 |         <artifactId>openblas</artifactId>
39 |         <version>0.3.19-1.5.7</version>
40 |     </dependency>
41 | 
42 |     <dependency>
43 |         <groupId>org.slf4j</groupId>
44 |         <artifactId>slf4j-api</artifactId>
45 |         <version>1.7.25</version>
46 |     </dependency>
47 | 
48 |     <dependency>
49 |         <groupId>org.slf4j</groupId>
50 |         <artifactId>slf4j-simple</artifactId>
51 |         <version>1.7.25</version>
52 |     </dependency>
53 | 
54 |     <dependency>
55 |         <groupId>org.apache.commons</groupId>
56 |         <artifactId>commons-lang3</artifactId>
57 |         <version>3.7</version>
58 |     </dependency>
59 | 
60 |     <dependency>
61 |         <groupId>ai.djl.opencv</groupId>
62 |         <artifactId>opencv</artifactId>
63 |         <version>0.17.0</version>
64 | 
65 |     </dependency>
66 | 
67 | </dependencies>
68 | 
69 | </project>


--------------------------------------------------------------------------------
/requirements.txt:
--------------------------------------------------------------------------------
1 | java=11
2 | onnxruntime=1.11.0
3 | javacv-platform=1.5.7
4 | ...
5 | 
6 | 


--------------------------------------------------------------------------------
/src/main/java/sy/Detection.java:
--------------------------------------------------------------------------------
 1 | package sy;
 2 | 
 3 | /**
 4 |  * @author sy
 5 |  * @date 2023/5/2 14:44
 6 |  */
 7 | public class Detection {
 8 |     private String label;
 9 |     private int labelIndex;
10 |     private float[] bbox;
11 |     private float confidence;
12 | 
13 |     public String getLabel() {
14 |         return label;
15 |     }
16 | 
17 |     public int getLabelIndex() {
18 |         return labelIndex;
19 |     }
20 |     public float[] getBbox() {
21 |         return bbox;
22 |     }
23 | 
24 |     public float getConfidence() {
25 |         return confidence;
26 |     }
27 | 
28 |     public Detection(String label, int labelIndex, float[] bbox, float confidence) {
29 |         this.label = label;
30 |         this.labelIndex = labelIndex;
31 |         this.bbox = bbox;
32 |         this.confidence = confidence;
33 |     }
34 | 
35 | }
36 | 


--------------------------------------------------------------------------------
/src/main/java/sy/ImageUtil.java:
--------------------------------------------------------------------------------
  1 | package sy;
  2 | 
  3 | import org.opencv.core.*;
  4 | import org.opencv.imgproc.Imgproc;
  5 | import utils.CollectionUtil;
  6 | 
  7 | import java.util.Comparator;
  8 | import java.util.List;
  9 | import java.util.Map;
 10 | import java.util.stream.Collectors;
 11 | 
 12 | /**
 13 |  * @author sy
 14 |  * @date 2023/5/2 13:48
 15 |  */
 16 | public class ImageUtil {
 17 | 
 18 |     public static float[] whc2cwh(float[] src) {
 19 |         float[] chw = new float[src.length];
 20 |         int j = 0;
 21 |         for (int ch = 0; ch < 3; ++ch) {
 22 |             for (int i = ch; i < src.length; i += 3) {
 23 |                 chw[j] = src[i];
 24 |                 j++;
 25 |             }
 26 |         }
 27 |         return chw;
 28 |     }
 29 | 
 30 |     private static final Map<Integer, Scalar> COLOR_MAP = Map.of(
 31 |             0, new Scalar(220, 50, 0),
 32 |             1, new Scalar(0, 200, 0),
 33 |             2, new Scalar(0, 0, 200),
 34 |             3, new Scalar(200, 200, 0),
 35 |             4, new Scalar(200, 0, 200),
 36 |             5, new Scalar(0, 200, 200),
 37 |             6, new Scalar(200, 100, 60),
 38 |             7, new Scalar(60, 50, 249),
 39 |             8, new Scalar(10, 60, 249),
 40 |             9, new Scalar(60, 100, 10)
 41 |     );
 42 | 
 43 |     public static void drawPredictions(Mat img, List<Detection> detectionList) {
 44 |         // debugging image
 45 |         for (Detection detection : detectionList) {
 46 |             float[] bbox = detection.getBbox();
 47 |             Scalar color = COLOR_MAP.get(detection.getLabelIndex());
 48 |             Imgproc.rectangle(img,                    //Matrix obj of the image
 49 |                     new Point(bbox[0], bbox[1]),        //p1
 50 |                     new Point(bbox[2], bbox[3]),       //p2
 51 |                     color,     //Scalar object for color
 52 |                     2                        //Thickness of the line
 53 |             );
 54 |             Imgproc.putText(
 55 |                     img,
 56 |                     detection.getLabel(),
 57 |                     new Point(bbox[0] - 1, bbox[1] - 5),
 58 |                     Imgproc.FONT_HERSHEY_SIMPLEX,
 59 |                     .5, color,
 60 |                     1);
 61 |         }
 62 |     }
 63 |     public static void xywh2xyxy(float[] bbox) {
 64 |         float x = bbox[0];
 65 |         float y = bbox[1];
 66 |         float w = bbox[2];
 67 |         float h = bbox[3];
 68 |         bbox[0] = x - w * 0.5f;
 69 |         bbox[1] = y - h * 0.5f;
 70 |         bbox[2] = x + w * 0.5f;
 71 |         bbox[3] = y + h * 0.5f;
 72 |     }
 73 | 
 74 |     public static List<float[]> nonMaxSuppression(List<float[]> bboxes, float iouThreshold) {
 75 |         // output boxes
 76 |         List<float[]> bestBboxes = CollectionUtil.newArrayList();
 77 |         // confidence
 78 |         bboxes.sort(Comparator.comparing(a -> a[4]));
 79 |         // standard nms
 80 |         while (!bboxes.isEmpty()) {
 81 |             float[] bestBbox = bboxes.remove(bboxes.size() - 1);
 82 |             bestBboxes.add(bestBbox);
 83 |             bboxes = bboxes.stream().filter(a -> computeIOU(a, bestBbox) < iouThreshold).collect(Collectors.toList());
 84 |         }
 85 |         return bestBboxes;
 86 |     }
 87 | 
 88 |     public static float computeIOU(float[] box1, float[] box2) {
 89 |         float area1 = (box1[2] - box1[0]) * (box1[3] - box1[1]);
 90 |         float area2 = (box2[2] - box2[0]) * (box2[3] - box2[1]);
 91 | 
 92 |         float left = Math.max(box1[0], box2[0]);
 93 |         float top = Math.max(box1[1], box2[1]);
 94 |         float right = Math.min(box1[2], box2[2]);
 95 |         float bottom = Math.min(box1[3], box2[3]);
 96 | 
 97 |         float interArea = Math.max(right - left, 0) * Math.max(bottom - top, 0);
 98 |         float unionArea = area1 + area2 - interArea;
 99 |         return Math.max(interArea / unionArea, 1e-8f);
100 |     }
101 | 
102 | }
103 | 


--------------------------------------------------------------------------------
/src/main/java/sy/MainTest.java:
--------------------------------------------------------------------------------
 1 | package sy;
 2 | 
 3 | import ai.onnxruntime.OrtException;
 4 | import com.alibaba.fastjson2.JSON;
 5 | import org.opencv.core.Mat;
 6 | import org.opencv.imgcodecs.Imgcodecs;
 7 | import utils.PropertiesReader;
 8 | 
 9 | import java.util.List;
10 | 
11 | /**
12 |  * @author sy
13 |  * @date 2023/5/2 15:49
14 |  */
15 | public class MainTest {
16 |         public static void main(String...args) {
17 |         String modelPath = MainTest.class.getClassLoader().getResource(PropertiesReader.get("model_path")).getPath().replaceFirst("/", "");
18 |         String labelPath = MainTest.class.getClassLoader().getResource(PropertiesReader.get("table_det_labels_path")).getPath().replaceFirst("/", "");
19 |         String imgPath = "D:\\project\\idea_workspace\\layout_analysis4j\\img\\test.webp";
20 | 
21 |         try {
22 |             ModelDet modelDet = new ModelDet(modelPath, labelPath);
23 |             Mat img = Imgcodecs.imread(imgPath);
24 |             if (img.dataAddr() == 0) {
25 |                 System.out.println("Could not open image: " + imgPath);
26 |                 System.exit(1);
27 |             }
28 |             // run detection
29 |             try {
30 |                 List<Detection> detectionList = modelDet.detectObjects(img);
31 | 
32 |                 ImageUtil.drawPredictions(img, detectionList);
33 |                 System.out.println(JSON.toJSONString(detectionList));
34 |                 Imgcodecs.imwrite("D:\\project\\idea_workspace\\layout_analysis4j\\img\\prediction.jpg", img);
35 |             } catch (OrtException ortException) {
36 |                 ortException.printStackTrace();
37 |             }
38 | 
39 |         } catch (OrtException e) {
40 |             e.printStackTrace();
41 |         }
42 |     }
43 | 
44 | }
45 | 


--------------------------------------------------------------------------------
/src/main/java/sy/ModelDet.java:
--------------------------------------------------------------------------------
  1 | package sy;
  2 | 
  3 | import ai.onnxruntime.*;
  4 | import org.opencv.core.CvType;
  5 | import org.opencv.core.Mat;
  6 | import org.opencv.core.Size;
  7 | import org.opencv.imgproc.Imgproc;
  8 | import utils.CollectionUtil;
  9 | 
 10 | import java.io.IOException;
 11 | import java.nio.FloatBuffer;
 12 | import java.nio.file.Files;
 13 | import java.nio.file.Paths;
 14 | import java.util.*;
 15 | import java.util.stream.Collectors;
 16 | import java.util.stream.Stream;
 17 | 
 18 | /**
 19 |  * @author sy
 20 |  * @date 2023/5/2 13:48
 21 |  */
 22 | public class ModelDet {
 23 |     float confThreshold;
 24 |     float iouThreshold;
 25 |     long inputHeight;
 26 |     long inputWidth;
 27 |     long[] inputShape;
 28 |     int numInputElements;
 29 |     OnnxJavaType inputType;
 30 |     OrtEnvironment env;
 31 |     OrtSession session;
 32 |     String inputName;
 33 |     String outputName;
 34 | 
 35 |     long rawImgHeight;
 36 |     long rawImgWidth;
 37 | 
 38 |     public List<String> labelNames;
 39 | 
 40 |     public ModelDet(String path, String labelPath) throws OrtException {
 41 |         this(path, labelPath, 0.3f, 0.5f);
 42 |     }
 43 | 
 44 |     public ModelDet(String path, String labelPath, float confThres, float iouThres) throws OrtException {
 45 |         this.confThreshold = confThres;
 46 |         this.iouThreshold = iouThres;
 47 |         initializeModel(path);
 48 |         initializeLabel(labelPath);
 49 |     }
 50 | 
 51 |     private void initializeModel(String path) throws OrtException {
 52 |         nu.pattern.OpenCV.loadLocally();
 53 |         this.initializeModel(path, -1);
 54 |     }
 55 | 
 56 |     private void initializeModel(String path, int gpuDeviceId) throws OrtException {
 57 |         this.env = OrtEnvironment.getEnvironment();
 58 |         var sessionOptions = new OrtSession.SessionOptions();
 59 |         sessionOptions.setOptimizationLevel(OrtSession.SessionOptions.OptLevel.ALL_OPT);
 60 |         if(gpuDeviceId >= 0) {
 61 |             sessionOptions.addCPU(false);
 62 |             sessionOptions.addCUDA(gpuDeviceId);
 63 |         } else {
 64 |             sessionOptions.addCPU(true);
 65 |         }
 66 |         this.session = this.env.createSession(path, sessionOptions);
 67 | 
 68 |         Map<String, NodeInfo> inputMetaMap = this.session.getInputInfo();
 69 |         this.inputName = this.session.getInputNames().iterator().next();
 70 |         NodeInfo inputMeta = inputMetaMap.get(this.inputName);
 71 |         this.inputType = ((TensorInfo)inputMeta.getInfo()).type;
 72 |         this.inputShape = ((TensorInfo) inputMeta.getInfo()).getShape();
 73 |         this.numInputElements = (int) (this.inputShape[1] * this.inputShape[2] * this.inputShape[3]);
 74 |         this.inputHeight = this.inputShape[2];
 75 |         this.inputWidth = this.inputShape[3];
 76 |         this.outputName = this.session.getOutputNames().iterator().next();
 77 |     }
 78 | 
 79 |     private void initializeLabel(String labelPath) {
 80 |         try(Stream<String> lines = Files.lines(Paths.get(labelPath))) {
 81 |             labelNames = lines.map(line -> line.strip()).collect(Collectors.toList());
 82 |         } catch (IOException e) {
 83 |             e.printStackTrace();
 84 |         }
 85 |     }
 86 | 
 87 |     public List<Detection> detectObjects(Mat img) throws OrtException {
 88 |         Map<String, OnnxTensor> inputMap = this.prepareInput(img);
 89 |         float[][] predictions = inference(inputMap);
 90 |         List<Detection> detectionList = this.processOutput(predictions);
 91 |         return detectionList;
 92 |     }
 93 | 
 94 |     private float[][] inference(Map<String, OnnxTensor> inputMap) throws OrtException { ;
 95 |         OrtSession.Result result = this.session.run(inputMap);
 96 |         float[][] predicitons = ((float[][][])result.get(0).getValue())[0];
 97 |         return predicitons;
 98 |     }
 99 | 
100 |     private Map<String, OnnxTensor> prepareInput(Mat img) throws OrtException {
101 |         this.rawImgHeight = img.height();
102 |         this.rawImgWidth = img.width();
103 |         Mat inputImg = new Mat();
104 |         Imgproc.cvtColor(img, inputImg, Imgproc.COLOR_BGR2RGB);
105 |         Imgproc.resize(inputImg, inputImg, new Size(this.inputWidth, this.inputHeight));
106 |         inputImg.convertTo(inputImg, CvType.CV_32FC3, 1./255);
107 | 
108 |         Map<String, OnnxTensor> inputMap = CollectionUtil.newHashMap();
109 |         float[] whc = new float[this.numInputElements];
110 |         inputImg.get(0, 0, whc);
111 |         float[] chw = ImageUtil.whc2cwh(whc);
112 |         FloatBuffer inputBuffer= FloatBuffer.wrap(chw);
113 |         OnnxTensor inputTensor = OnnxTensor.createTensor(this.env, inputBuffer, this.inputShape);
114 |         inputMap.put(this.inputName, inputTensor);
115 |         return inputMap;
116 |     }
117 | 
118 |     private List<Detection> processOutput(float[][] predictions) {
119 |         // prediction
120 |         predictions = transposeMatrix(predictions);
121 |         Map<Integer, List<float[]>> class2Bbox = CollectionUtil.newHashMap();
122 |         for(float[] bbox : predictions) {
123 |             float[] condProb = Arrays.copyOfRange(bbox, 4, bbox.length);
124 |             int label = predMax(condProb);
125 |             float conf = condProb[label];
126 |             if(conf < this.confThreshold) {
127 |                 continue;
128 |             }
129 |             bbox[4] = conf;
130 |             rescaleBoxes(bbox); // xmin, ymin, xmax, ymax -> (xmin_raw, ymin_raw, xmax_raw, ymax_raw)
131 |             ImageUtil.xywh2xyxy(bbox); // xywh -> (x1, y1, x2, y2)
132 |             //skip invalid prediction
133 |             if(bbox[0] >= bbox[2] || bbox[1] >= bbox[3]) {
134 |                 continue;
135 |             }
136 |             class2Bbox.putIfAbsent(label, CollectionUtil.newArrayList());
137 |             class2Bbox.get(label).add(bbox);
138 |         }
139 |         //apply non-max suppression for each class
140 |         List<Detection> detectionList = CollectionUtil.newArrayList();
141 |         for(Map.Entry<Integer, List<float[]>> entry : class2Bbox.entrySet()) {
142 |             int lable = entry.getKey();
143 |             List<float[]> bboxList = entry.getValue();
144 |             bboxList = ImageUtil.nonMaxSuppression(bboxList, this.iouThreshold);
145 |             for(float[] bbox : bboxList) {
146 |                 String labelString = labelNames.get(lable);
147 |                 detectionList.add(new Detection(labelString, lable, Arrays.copyOfRange(bbox, 0, 4), bbox[4]));
148 |             }
149 |         }
150 |         return detectionList;
151 |     }
152 | 
153 |     public float[][] transposeMatrix(float[][] matrix) {
154 |         float[][] transMatrix = new float[matrix[0].length][matrix.length];
155 |         for(int i=0; i<matrix.length; i++) {
156 |             for(int j=0; j<matrix[0].length; j++) {
157 |                 transMatrix[j][i] = matrix[i][j];
158 |             }
159 |         }
160 |         return transMatrix;
161 |     }
162 | 
163 |     /**
164 |      * @param probabilities
165 |      * @return
166 |      */
167 |     private int predMax(float[] probabilities) {
168 |         float maxVal = Float.NEGATIVE_INFINITY;
169 |         int idx = 0;
170 |         for (int i = 0; i < probabilities.length; i++) {
171 |             if (probabilities[i] > maxVal) {
172 |                 maxVal = probabilities[i];
173 |                 idx = i;
174 |             }
175 |         }
176 |         return idx;
177 |     }
178 | 
179 |     public void rescaleBoxes(float[] bbox) {
180 |         bbox[0] /= this.inputWidth;
181 |         bbox[0] *= this.rawImgWidth;
182 |         bbox[1] /= this.inputHeight;
183 |         bbox[1] *= this.rawImgHeight;
184 |         bbox[2] /= this.inputWidth;
185 |         bbox[2] *= this.rawImgWidth;
186 |         bbox[3] /= this.inputHeight;
187 |         bbox[3] *= this.rawImgHeight;
188 |     }
189 | 
190 | }
191 | 
192 | 


--------------------------------------------------------------------------------
/src/main/java/utils/CollectionUtil.java:
--------------------------------------------------------------------------------
 1 | package utils;
 2 | 
 3 | import java.util.*;
 4 | 
 5 | /**
 6 |  * @author sy
 7 |  * @date 2022/2/2 19:36
 8 |  */
 9 | public class CollectionUtil<E, T> {
10 | 
11 |     public static <E> List<E> newArrayList(List<E> list) {
12 |         return new ArrayList<>(list);
13 |     }
14 | 
15 |     public static <E> List<E> newArrayList() {
16 |         return new ArrayList<>();
17 |     }
18 | 
19 |     public static <E> LinkedList<E> newLinkedList() {
20 |         return new LinkedList<>();
21 |     }
22 | 
23 |     public static <E> List<E> newArrayList(int N) {
24 |         return new ArrayList<>(N);
25 |     }
26 | 
27 |     public static <E> List<E> newArrayList(Set<E> entry) {
28 |         return new ArrayList<>(entry);
29 |     }
30 | 
31 |     public static <E> Set<E> newHashset() {
32 |         return new HashSet<>();
33 |     }
34 | 
35 |     public static <E> Set<E> newHashset(List<E> entry) {
36 |         return new HashSet<>(entry);
37 |     }
38 | 
39 |     public static <E,T> Map<E, T> newHashMap() {
40 |         return new HashMap<>();
41 |     }
42 | 
43 |     public static <E,T> LinkedHashMap<E, T> newLinkedHashMap() {
44 |         return new LinkedHashMap<>();
45 |     }
46 | 
47 |     public static <E,T> Map<E, T> newTreeMap() {
48 |         return new TreeMap<>();
49 |     }
50 | 
51 | }
52 | 


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/src/main/java/utils/PropertiesReader.java:
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 1 | package utils;
 2 | 
 3 | import java.io.IOException;
 4 | import java.io.InputStreamReader;
 5 | import java.util.Properties;
 6 | 
 7 | /**
 8 |  * @author sy
 9 |  * @date 2022/2/2 19:07
10 |  */
11 | public class PropertiesReader {
12 |     private static Properties properties = new Properties();
13 | 
14 |     static {
15 |         try {
16 |             properties.load(new InputStreamReader(PropertiesReader.class.getClassLoader().getResourceAsStream("properties.properties"), "UTF-8"));
17 | 
18 |         } catch (IOException e) {
19 |             e.printStackTrace();
20 |         }
21 |     }
22 | 
23 |     public static String get(String keyName) {
24 |         return properties.getProperty(keyName);
25 |     }
26 | 
27 | }
28 | 


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/src/main/resources/model/label.names:
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 1 | Header
 2 | Text
 3 | Reference
 4 | Figure caption
 5 | Figure
 6 | Table caption
 7 | Table
 8 | Title
 9 | Footer
10 | Equation


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/src/main/resources/model/model.onnx:
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https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/src/main/resources/model/model.onnx


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/src/main/resources/properties.properties:
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1 | model_path = model/model.onnx
2 | table_det_labels_path = model/label.names


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/target/classes/META-INF/layout_analysis4j.kotlin_module:
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1 | 




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/target/classes/model/label.names:
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 1 | Header
 2 | Text
 3 | Reference
 4 | Figure caption
 5 | Figure
 6 | Table caption
 7 | Table
 8 | Title
 9 | Footer
10 | Equation


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/target/classes/model/model.onnx:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/model/model.onnx


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/target/classes/properties.properties:
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1 | model_path = model/model.onnx
2 | table_det_labels_path = model/label.names


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/target/classes/sy/Detection.class:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/sy/Detection.class


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/target/classes/sy/ImageUtil.class:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/sy/ImageUtil.class


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/target/classes/sy/MainTest.class:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/sy/MainTest.class


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/target/classes/sy/ModelDet.class:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/sy/ModelDet.class


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/target/classes/utils/CollectionUtil.class:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/utils/CollectionUtil.class


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/target/classes/utils/PropertiesReader.class:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/jiangnanboy/layout_analysis4j/710bf41c11bc0d26f991aee14e4ea995f246fd19/target/classes/utils/PropertiesReader.class


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