From 0e8d2c3c4fba01f5d5531547644e91a7c4ae156a Mon Sep 17 00:00:00 2001 From: wangchuang <994001556@qq.com> Date: Tue, 17 Jan 2023 13:04:26 +0800 Subject: [PATCH] =?UTF-8?q?ai=E5=9B=BE=E5=83=8F=E8=AF=86=E5=88=AB?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- SC-boot/build/output/ocr_result.png | Bin 0 -> 43291 bytes SC-boot/build/output/table.html | 1 + SC-boot/build/output/table.xls | Bin 0 -> 4096 bytes SC-boot/build/output/table_cells_content.png | Bin 0 -> 23249 bytes SC-boot/build/output/table_cells_detected.png | Bin 0 -> 28449 bytes SC-boot/build/output/table_texts_detected.png | Bin 0 -> 19331 bytes SC-boot/linkage-scm/pom.xml | 103 ++++ .../jnpf/ocr_sdk/OcrV3RecognitionExample.java | 83 +++ .../utils/cls/OcrDirectionDetection.java | 141 +++++ .../utils/cls/PpWordRotateTranslator.java | 69 +++ .../ocr_sdk/utils/common/DJLImageUtils.java | 99 +++ .../jnpf/ocr_sdk/utils/common/ImageInfo.java | 48 ++ .../jnpf/ocr_sdk/utils/common/ImageUtils.java | 262 ++++++++ .../jnpf/ocr_sdk/utils/common/RotatedBox.java | 29 + .../detection/OCRDetectionTranslator.java | 574 ++++++++++++++++++ .../utils/detection/OcrV3Detection.java | 34 ++ .../detection/PpWordDetectionTranslator.java | 120 ++++ .../ocr_sdk/utils/layout/LayoutDetection.java | 32 + .../layout/LayoutDetectionTranslator.java | 104 ++++ .../ocr_sdk/utils/opencv/NDArrayUtils.java | 64 ++ .../ocr_sdk/utils/opencv/OpenCVUtils.java | 72 +++ .../recognition/OcrV3AlignedRecognition.java | 129 ++++ .../OcrV3MultiThreadRecognition.java | 194 ++++++ .../utils/recognition/OcrV3Recognition.java | 140 +++++ .../PpWordRecognitionTranslator.java | 108 ++++ .../rotation/PpWordRotateTranslator.java | 69 +++ .../utils/table/ConvertHtml2Excel.java | 235 +++++++ .../utils/table/CrossRangeCellMeta.java | 42 ++ .../ocr_sdk/utils/table/TableDetection.java | 227 +++++++ .../jnpf/ocr_sdk/utils/table/TableResult.java | 31 + .../utils/table/TableStructTranslator.java | 246 ++++++++ 31 files changed, 3256 insertions(+) create mode 100644 SC-boot/build/output/ocr_result.png create mode 100644 SC-boot/build/output/table.html create mode 100644 SC-boot/build/output/table.xls create mode 100644 SC-boot/build/output/table_cells_content.png create mode 100644 SC-boot/build/output/table_cells_detected.png create mode 100644 SC-boot/build/output/table_texts_detected.png create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/OcrV3RecognitionExample.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/OcrDirectionDetection.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/PpWordRotateTranslator.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/DJLImageUtils.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageInfo.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageUtils.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/RotatedBox.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OCRDetectionTranslator.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OcrV3Detection.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/PpWordDetectionTranslator.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetection.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetectionTranslator.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/NDArrayUtils.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/OpenCVUtils.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3AlignedRecognition.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3MultiThreadRecognition.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3Recognition.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/PpWordRecognitionTranslator.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/rotation/PpWordRotateTranslator.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/ConvertHtml2Excel.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/CrossRangeCellMeta.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableDetection.java create mode 100644 SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableResult.java create mode 100644 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上海长江云息文档编号密级
CJYX202211240001<V1.0e 机密
」数字科技有限公司再生资源智慧管家平台之货客智慧管控平台一共51页
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zL`>C*RM-mpUF{yW4d~e)xFgjt{*ukC-4r_8+sIhpmqxxQEG(Q44z?$`%N9I0>7tq| zoj)(H6SNXta!o!~yL@e=i9v3=n;uy13) zo#`co+NCVta?JDy^uSQ%W5J^KF>8VerS(QBS34Kr*q+C5)y!tY|1{LdIS-(G$R7hs z7^sbTXAhyPKtci%0J1_l3+@SGrapcEHf#g%xQ2UkfRhQ(f^HHxz=Ye literal 0 HcmV?d00001 diff --git a/SC-boot/linkage-scm/pom.xml b/SC-boot/linkage-scm/pom.xml index 35197e4f..49097941 100644 --- a/SC-boot/linkage-scm/pom.xml +++ b/SC-boot/linkage-scm/pom.xml @@ -11,6 +11,13 @@ linkage-scm + + UTF-8 + 1.8 + 1.8 + 0.17.0 + + com.jnpf @@ -62,6 +69,102 @@ 3.4.1-RELEASE compile + + + + + + + commons-cli + commons-cli + 1.4 + + + org.apache.logging.log4j + log4j-slf4j-impl + 2.17.2 + + + com.google.code.gson + gson + 2.8.5 + + + + ai.djl + api + ${djl.version} + + + ai.djl + basicdataset + ${djl.version} + + + ai.djl + model-zoo + ${djl.version} + + + + ai.djl.mxnet + mxnet-model-zoo + ${djl.version} + + + ai.djl.mxnet + mxnet-engine + ${djl.version} + + + + ai.djl.paddlepaddle + paddlepaddle-engine + ${djl.version} + + + ai.djl.paddlepaddle + paddlepaddle-model-zoo + ${djl.version} + + + + org.bytedeco + javacv-platform + 1.5.7 + + + ai.djl.opencv + opencv + ${djl.version} + + + + org.apache.commons + commons-lang3 + 3.12.0 + + + commons-collections + commons-collections + 3.2.2 + + + org.projectlombok + lombok + 1.18.18 + provided + + + org.apache.poi + poi + 4.0.0 + + + dom4j + dom4j + 1.6.1 + diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/OcrV3RecognitionExample.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/OcrV3RecognitionExample.java new file mode 100644 index 00000000..df6b287f --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/OcrV3RecognitionExample.java @@ -0,0 +1,83 @@ +package jnpf.ocr_sdk; + +import ai.djl.ModelException; +import ai.djl.inference.Predictor; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.ndarray.NDList; +import ai.djl.opencv.OpenCVImageFactory; +import ai.djl.repository.zoo.ModelZoo; +import ai.djl.repository.zoo.ZooModel; +import ai.djl.translate.TranslateException; +import jnpf.ocr_sdk.utils.common.ImageUtils; +import jnpf.ocr_sdk.utils.common.RotatedBox; +import jnpf.ocr_sdk.utils.detection.OcrV3Detection; +import jnpf.ocr_sdk.utils.opencv.OpenCVUtils; +import jnpf.ocr_sdk.utils.recognition.OcrV3Recognition; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.awt.image.BufferedImage; +import java.io.IOException; +import java.nio.file.Path; +import java.nio.file.Paths; +import java.util.List; + +/** + * OCR V3模型 文字识别. 支持文本有旋转角度 + * + * @author Calvin + * @date 2022-10-07 + * @email 179209347@qq.com + */ +public final class OcrV3RecognitionExample { + + private static final Logger logger = LoggerFactory.getLogger(OcrV3RecognitionExample.class); + + private OcrV3RecognitionExample() { + } + + public static void main(String[] args) throws IOException, ModelException, TranslateException { +// Path imageFile = Paths.get("src/test/resources/7.jpg"); + String relativelyPath=System.getProperty("user.dir"); +// Path imageFile = Paths.get("C:\\Users\\admin\\Desktop\\图像\\AISDK\\AIAS\\1_image_sdks\\text_recognition\\ocr_sdk\\src\\test\\resources\\7.jpg"); +// Path imageFile = Paths.get("src/test/resources/7.jpg"); + StringBuffer ocrStr = new StringBuffer("本次识别的内容："); + Path imageFile = Paths.get("C:/Users/admin/Desktop/AAAA.png"); + Image image = OpenCVImageFactory.getInstance().fromFile(imageFile); + + + OcrV3Detection detection = new OcrV3Detection(); + OcrV3Recognition recognition = new OcrV3Recognition(); + try (ZooModel detectionModel = ModelZoo.loadModel(detection.detectCriteria()); + Predictor detector = detectionModel.newPredictor(); + ZooModel recognitionModel = ModelZoo.loadModel(recognition.recognizeCriteria()); + Predictor recognizer = recognitionModel.newPredictor()) { + + long timeInferStart = System.currentTimeMillis(); + List detections = recognition.predict(image, detector, recognizer); + +// for (int i = 0; i < 1000; i++) { +// detections = recognition.predict(image, detector, recognizer); +// System.out.println("time: " + i); +// } + + long timeInferEnd = System.currentTimeMillis(); + System.out.println("time: " + (timeInferEnd - timeInferStart)); + + for (RotatedBox result : detections) { + System.out.println(result.getText()); + ocrStr.append(result.getText()); + } + + BufferedImage bufferedImage = OpenCVUtils.mat2Image((org.opencv.core.Mat) image.getWrappedImage()); + for (RotatedBox result : detections) { + ImageUtils.drawImageRectWithText(bufferedImage, result.getBox(), result.getText()); + } + image = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(bufferedImage)); + ImageUtils.saveImage(image, "ocr_result.png", "build/output"); + logger.info("{}", detections); + logger.info(ocrStr.toString()); + } + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/OcrDirectionDetection.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/OcrDirectionDetection.java new file mode 100644 index 00000000..cb038469 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/OcrDirectionDetection.java @@ -0,0 +1,141 @@ +package jnpf.ocr_sdk.utils.cls; + +import ai.djl.inference.Predictor; +import ai.djl.modality.Classifications; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import ai.djl.repository.zoo.Criteria; +import ai.djl.training.util.ProgressBar; +import ai.djl.translate.TranslateException; +import jnpf.ocr_sdk.utils.detection.PpWordDetectionTranslator; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.ArrayList; +import java.util.List; +import java.util.concurrent.ConcurrentHashMap; + +public final class OcrDirectionDetection { + + private static final Logger logger = LoggerFactory.getLogger(OcrDirectionDetection.class); + + public OcrDirectionDetection() {} + + public DetectedObjects predict( + Image image, + Predictor detector, + Predictor rotateClassifier) + throws TranslateException { + DetectedObjects detections = detector.predict(image); + + List boxes = detections.items(); + + List names = new ArrayList<>(); + List prob = new ArrayList<>(); + List rect = new ArrayList<>(); + + for (int i = 0; i < boxes.size(); i++) { + Image subImg = getSubImage(image, boxes.get(i).getBoundingBox()); + Classifications.Classification result = null; + if (subImg.getHeight() * 1.0 / subImg.getWidth() > 1.5) { + subImg = rotateImg(subImg); + result = rotateClassifier.predict(subImg).best(); + prob.add(result.getProbability()); + if (result.getClassName().equalsIgnoreCase("Rotate")) { + names.add("90"); + } else { + names.add("270"); + } + } else { + result = rotateClassifier.predict(subImg).best(); + prob.add(result.getProbability()); + if (result.getClassName().equalsIgnoreCase("No Rotate")) { + names.add("0"); + } else { + names.add("180"); + } + } + rect.add(boxes.get(i).getBoundingBox()); + } + DetectedObjects detectedObjects = new DetectedObjects(names, prob, rect); + + return detectedObjects; + } + + public Criteria detectCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, DetectedObjects.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv2_det_infer.zip") + // .optModelUrls( + // "/Users/calvin/Documents/build/paddle_models/ppocr/ch_PP-OCRv2_det_infer") + // .optDevice(Device.cpu()) + .optTranslator(new PpWordDetectionTranslator(new ConcurrentHashMap())) + .optProgress(new ProgressBar()) + .build(); + + return criteria; + } + + public Criteria clsCriteria() { + + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, Classifications.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_ppocr_mobile_v2.0_cls_infer.zip") + // .optModelUrls( + // "/Users/calvin/Documents/build/paddle_models/ppocr/ch_ppocr_mobile_v2.0_cls_infer") + .optTranslator(new PpWordRotateTranslator()) + .optProgress(new ProgressBar()) + .build(); + return criteria; + } + + private Image getSubImage(Image img, BoundingBox box) { + Rectangle rect = box.getBounds(); + double[] extended = extendRect(rect.getX(), rect.getY(), rect.getWidth(), rect.getHeight()); + int width = img.getWidth(); + int height = img.getHeight(); + int[] recovered = { + (int) (extended[0] * width), + (int) (extended[1] * height), + (int) (extended[2] * width), + (int) (extended[3] * height) + }; + return img.getSubImage(recovered[0], recovered[1], recovered[2], recovered[3]); + } + + private double[] extendRect(double xmin, double ymin, double width, double height) { + double centerx = xmin + width / 2; + double centery = ymin + height / 2; + if (width > height) { + width += height * 2.0; + height *= 3.0; + } else { + height += width * 2.0; + width *= 3.0; + } + double newX = centerx - width / 2 < 0 ? 0 : centerx - width / 2; + double newY = centery - height / 2 < 0 ? 0 : centery - height / 2; + double newWidth = newX + width > 1 ? 1 - newX : width; + double newHeight = newY + height > 1 ? 1 - newY : height; + return new double[] {newX, newY, newWidth, newHeight}; + } + + private Image rotateImg(Image image) { + try (NDManager manager = NDManager.newBaseManager()) { + NDArray rotated = NDImageUtils.rotate90(image.toNDArray(manager), 1); + return ImageFactory.getInstance().fromNDArray(rotated); + } + } +} \ No newline at end of file diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/PpWordRotateTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/PpWordRotateTranslator.java new file mode 100644 index 00000000..27921a85 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/cls/PpWordRotateTranslator.java @@ -0,0 +1,69 @@ +package jnpf.ocr_sdk.utils.cls; + +import ai.djl.modality.Classifications; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.index.NDIndex; +import ai.djl.ndarray.types.Shape; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; + +import java.util.Arrays; +import java.util.List; + +public class PpWordRotateTranslator implements Translator { + List classes = Arrays.asList("No Rotate", "Rotate"); + + public PpWordRotateTranslator() {} + + public Classifications processOutput(TranslatorContext ctx, NDList list) { + NDArray prob = list.singletonOrThrow(); + return new Classifications(this.classes, prob); + } + + public NDList processInput(TranslatorContext ctx, Image input) throws Exception { + NDArray img = input.toNDArray(ctx.getNDManager()); + img = NDImageUtils.resize(img, 192, 48); + img = NDImageUtils.toTensor(img).sub(0.5F).div(0.5F); + img = img.expandDims(0); + return new NDList(new NDArray[]{img}); + } + + public NDList processInputBak(TranslatorContext ctx, Image input) throws Exception { + NDArray img = input.toNDArray(ctx.getNDManager()); + int imgC = 3; + int imgH = 48; + int imgW = 192; + + NDArray array = ctx.getNDManager().zeros(new Shape(imgC, imgH, imgW)); + + int h = input.getHeight(); + int w = input.getWidth(); + int resized_w = 0; + + float ratio = (float) w / (float) h; + if (Math.ceil(imgH * ratio) > imgW) { + resized_w = imgW; + } else { + resized_w = (int) (Math.ceil(imgH * ratio)); + } + + img = NDImageUtils.resize(img, resized_w, imgH); + + img = NDImageUtils.toTensor(img).sub(0.5F).div(0.5F); + // img = img.transpose(2, 0, 1); + + array.set(new NDIndex(":,:,0:" + resized_w), img); + + array = array.expandDims(0); + + return new NDList(new NDArray[] {array}); + } + + public Batchifier getBatchifier() { + return null; + } +} \ No newline at end of file diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/DJLImageUtils.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/DJLImageUtils.java new file mode 100644 index 00000000..00bc1d64 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/DJLImageUtils.java @@ -0,0 +1,99 @@ +package jnpf.ocr_sdk.utils.common; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.DetectedObjects; + +import java.awt.*; +import java.awt.image.BufferedImage; +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.nio.file.Paths; + +public class DJLImageUtils { + + public static Image bufferedImage2DJLImage(BufferedImage img) { + return ImageFactory.getInstance().fromImage(img); + } + + public static void saveImage(BufferedImage img, String name, String path) { + + Image djlImg = ImageFactory.getInstance().fromImage(img); // 支持多种图片格式，自动适配 + Path outputDir = Paths.get(path); + Path imagePath = outputDir.resolve(name); + // OpenJDK 不能保存 jpg 图片的 alpha channel + try { + djlImg.save(Files.newOutputStream(imagePath), "png"); + } catch (IOException e) { + e.printStackTrace(); + } + } + + public static void saveDJLImage(Image img, String name, String path) { + Path outputDir = Paths.get(path); + Path imagePath = outputDir.resolve(name); + // OpenJDK 不能保存 jpg 图片的 alpha channel + try { + img.save(Files.newOutputStream(imagePath), "png"); + } catch (IOException e) { + e.printStackTrace(); + } + } + + public static void saveBoundingBoxImage( + Image img, DetectedObjects detection, String name, String path) throws IOException { + // Make imageName copy with alpha channel because original imageName was jpg + img.drawBoundingBoxes(detection); + Path outputDir = Paths.get(path); + Files.createDirectories(outputDir); + Path imagePath = outputDir.resolve(name); + // OpenJDK can't save jpg with alpha channel + img.save(Files.newOutputStream(imagePath), "png"); + } + + public static void drawImageRect(BufferedImage image, int x, int y, int width, int height) { + // 将绘制图像转换为Graphics2D + Graphics2D g = (Graphics2D) image.getGraphics(); + try { + g.setColor(new Color(246, 96, 0)); + // 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角 + BasicStroke bStroke = new BasicStroke(4, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER); + g.setStroke(bStroke); + g.drawRect(x, y, width, height); + + } finally { + g.dispose(); + } + } + + public static void drawImageRect( + BufferedImage image, int x, int y, int width, int height, Color c) { + // 将绘制图像转换为Graphics2D + Graphics2D g = (Graphics2D) image.getGraphics(); + try { + g.setColor(c); + // 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角 + BasicStroke bStroke = new BasicStroke(4, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER); + g.setStroke(bStroke); + g.drawRect(x, y, width, height); + + } finally { + g.dispose(); + } + } + + public static void drawImageText(BufferedImage image, String text) { + Graphics graphics = image.getGraphics(); + int fontSize = 100; + Font font = new Font("楷体", Font.PLAIN, fontSize); + try { + graphics.setFont(font); + graphics.setColor(new Color(246, 96, 0)); + int strWidth = graphics.getFontMetrics().stringWidth(text); + graphics.drawString(text, fontSize - (strWidth / 2), fontSize + 30); + } finally { + graphics.dispose(); + } + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageInfo.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageInfo.java new file mode 100644 index 00000000..cc9d3da0 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageInfo.java @@ -0,0 +1,48 @@ +package jnpf.ocr_sdk.utils.common; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.output.BoundingBox; + +public class ImageInfo { + private String name; + private Double prob; + private Image image; + private BoundingBox box; + + public ImageInfo(Image image, BoundingBox box) { + this.image = image; + this.box = box; + } + + public String getName() { + return name; + } + + public void setName(String name) { + this.name = name; + } + + public Double getProb() { + return prob; + } + + public void setProb(Double prob) { + this.prob = prob; + } + + public Image getImage() { + return image; + } + + public void setImage(Image image) { + this.image = image; + } + + public BoundingBox getBox() { + return box; + } + + public void setBox(BoundingBox box) { + this.box = box; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageUtils.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageUtils.java new file mode 100644 index 00000000..23b82e7c --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/ImageUtils.java @@ -0,0 +1,262 @@ +package jnpf.ocr_sdk.utils.common; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.ndarray.NDArray; + +import java.awt.*; +import java.awt.image.BufferedImage; +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.nio.file.Paths; + +public class ImageUtils { + + /** + * BufferedImage图片格式转DJL图片格式 + * + * @author Calvin + */ + public static Image convert(BufferedImage img) { + return ImageFactory.getInstance().fromImage(img); + } + + /** + * 保存BufferedImage图片 + * + * @author Calvin + */ + public static void saveImage(BufferedImage img, String name, String path) { + Image djlImg = ImageFactory.getInstance().fromImage(img); // 支持多种图片格式，自动适配 + Path outputDir = Paths.get(path); + Path imagePath = outputDir.resolve(name); + // OpenJDK 不能保存 jpg 图片的 alpha channel + try { + djlImg.save(Files.newOutputStream(imagePath), "png"); + } catch (IOException e) { + e.printStackTrace(); + } + } + + /** + * 保存DJL图片 + * + * @author Calvin + */ + public static void saveImage(Image img, String name, String path) { + Path outputDir = Paths.get(path); + Path imagePath = outputDir.resolve(name); + // OpenJDK 不能保存 jpg 图片的 alpha channel + try { + img.save(Files.newOutputStream(imagePath), "png"); + } catch (IOException e) { + e.printStackTrace(); + } + } + + /** + * 保存图片,含检测框 + * + * @author Calvin + */ + public static void saveBoundingBoxImage( + Image img, DetectedObjects detection, String name, String path) throws IOException { + // Make image copy with alpha channel because original image was jpg + img.drawBoundingBoxes(detection); + Path outputDir = Paths.get(path); + Files.createDirectories(outputDir); + Path imagePath = outputDir.resolve(name); + // OpenJDK can't save jpg with alpha channel + img.save(Files.newOutputStream(imagePath), "png"); + } + + /** + * 绘制人脸关键点 + * + * @author Calvin + */ + public static void drawLandmark(Image img, BoundingBox box, float[] array) { + for (int i = 0; i < array.length / 2; i++) { + int x = getX(img, box, array[2 * i]); + int y = getY(img, box, array[2 * i + 1]); + Color c = new Color(0, 255, 0); + drawImageRect((BufferedImage) img.getWrappedImage(), x, y, 1, 1, c); + } + } + + /** + * 画检测框(有倾斜角) + * + * @author Calvin + */ + public static void drawImageRect(BufferedImage image, NDArray box) { + float[] points = box.toFloatArray(); + int[] xPoints = new int[5]; + int[] yPoints = new int[5]; + + for (int i = 0; i < 4; i++) { + xPoints[i] = (int) points[2 * i]; + yPoints[i] = (int) points[2 * i + 1]; + } + xPoints[4] = xPoints[0]; + yPoints[4] = yPoints[0]; + + // 将绘制图像转换为Graphics2D + Graphics2D g = (Graphics2D) image.getGraphics(); + try { + g.setColor(new Color(0, 255, 0)); + // 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角 + BasicStroke bStroke = new BasicStroke(4, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER); + g.setStroke(bStroke); + g.drawPolyline(xPoints, yPoints, 5); // xPoints, yPoints, nPoints + } finally { + g.dispose(); + } + } + + /** + * 画检测框(有倾斜角)和文本 + * + * @author Calvin + */ + public static void drawImageRectWithText(BufferedImage image, NDArray box, String text) { + float[] points = box.toFloatArray(); + int[] xPoints = new int[5]; + int[] yPoints = new int[5]; + + for (int i = 0; i < 4; i++) { + xPoints[i] = (int) points[2 * i]; + yPoints[i] = (int) points[2 * i + 1]; + } + xPoints[4] = xPoints[0]; + yPoints[4] = yPoints[0]; + + // 将绘制图像转换为Graphics2D + Graphics2D g = (Graphics2D) image.getGraphics(); + try { + int fontSize = 32; + Font font = new Font("楷体", Font.PLAIN, fontSize); + g.setFont(font); + g.setColor(new Color(0, 0, 255)); + // 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角 + BasicStroke bStroke = new BasicStroke(2, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER); + g.setStroke(bStroke); + g.drawPolyline(xPoints, yPoints, 5); // xPoints, yPoints, nPoints + g.drawString(text, xPoints[0], yPoints[0]); + } finally { + g.dispose(); + } + } + + /** + * 画检测框 + * + * @author Calvin + */ + public static void drawImageRect(BufferedImage image, int x, int y, int width, int height) { + // 将绘制图像转换为Graphics2D + Graphics2D g = (Graphics2D) image.getGraphics(); + try { + g.setColor(new Color(0, 255, 0)); + // 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角 + BasicStroke bStroke = new BasicStroke(2, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER); + g.setStroke(bStroke); + g.drawRect(x, y, width, height); + } finally { + g.dispose(); + } + } + + /** + * 画检测框 + * + * @author Calvin + */ + public static void drawImageRect( + BufferedImage image, int x, int y, int width, int height, Color c) { + // 将绘制图像转换为Graphics2D + Graphics2D g = (Graphics2D) image.getGraphics(); + try { + g.setColor(c); + // 声明画笔属性 ：粗 细（单位像素）末端无修饰 折线处呈尖角 + BasicStroke bStroke = new BasicStroke(1, BasicStroke.CAP_BUTT, BasicStroke.JOIN_MITER); + g.setStroke(bStroke); + g.drawRect(x, y, width, height); + + } finally { + g.dispose(); + } + } + + /** + * 显示文字 + * + * @author Calvin + */ + public static void drawImageText(BufferedImage image, String text, int x, int y) { + Graphics graphics = image.getGraphics(); + int fontSize = 32; + Font font = new Font("楷体", Font.PLAIN, fontSize); + try { + graphics.setFont(font); + graphics.setColor(new Color(0, 0, 255)); + int strWidth = graphics.getFontMetrics().stringWidth(text); + graphics.drawString(text, x, y); + } finally { + graphics.dispose(); + } + } + + /** + * 返回外扩人脸 factor = 1, 100%, factor = 0.2, 20% + * + * @author Calvin + */ + public static Image getSubImage(Image img, BoundingBox box, float factor) { + Rectangle rect = box.getBounds(); + // 左上角坐标 + int x1 = (int) (rect.getX() * img.getWidth()); + int y1 = (int) (rect.getY() * img.getHeight()); + // 宽度，高度 + int w = (int) (rect.getWidth() * img.getWidth()); + int h = (int) (rect.getHeight() * img.getHeight()); + // 左上角坐标 + int x2 = x1 + w; + int y2 = y1 + h; + + // 外扩大100%，防止对齐后人脸出现黑边 + int new_x1 = Math.max((int) (x1 + x1 * factor / 2 - x2 * factor / 2), 0); + int new_x2 = Math.min((int) (x2 + x2 * factor / 2 - x1 * factor / 2), img.getWidth() - 1); + int new_y1 = Math.max((int) (y1 + y1 * factor / 2 - y2 * factor / 2), 0); + int new_y2 = Math.min((int) (y2 + y2 * factor / 2 - y1 * factor / 2), img.getHeight() - 1); + int new_w = new_x2 - new_x1; + int new_h = new_y2 - new_y1; + + return img.getSubImage(new_x1, new_y1, new_w, new_h); + } + + private static int getX(Image img, BoundingBox box, float x) { + Rectangle rect = box.getBounds(); + // 左上角坐标 + int x1 = (int) (rect.getX() * img.getWidth()); + // 宽度 + int w = (int) (rect.getWidth() * img.getWidth()); + + return (int) (x * w + x1); + } + + private static int getY(Image img, BoundingBox box, float y) { + Rectangle rect = box.getBounds(); + // 左上角坐标 + int y1 = (int) (rect.getY() * img.getHeight()); + // 高度 + int h = (int) (rect.getHeight() * img.getHeight()); + + return (int) (y * h + y1); + } + +} \ No newline at end of file diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/RotatedBox.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/RotatedBox.java new file mode 100644 index 00000000..628b5133 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/common/RotatedBox.java @@ -0,0 +1,29 @@ +package jnpf.ocr_sdk.utils.common; + +import ai.djl.ndarray.NDArray; + +public class RotatedBox { + private NDArray box; + private String text; + + public RotatedBox(NDArray box, String text) { + this.box = box; + this.text = text; + } + + public NDArray getBox() { + return box; + } + + public void setBox(NDArray box) { + this.box = box; + } + + public String getText() { + return text; + } + + public void setText(String text) { + this.text = text; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OCRDetectionTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OCRDetectionTranslator.java new file mode 100644 index 00000000..731845b6 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OCRDetectionTranslator.java @@ -0,0 +1,574 @@ +package jnpf.ocr_sdk.utils.detection; + +import ai.djl.modality.cv.BufferedImageFactory; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDArrays; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.NDManager; +import ai.djl.ndarray.index.NDIndex; +import ai.djl.ndarray.types.DataType; +import ai.djl.ndarray.types.Shape; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; +import org.bytedeco.javacpp.indexer.FloatRawIndexer; +import org.bytedeco.javacpp.indexer.IntRawIndexer; +import org.bytedeco.javacpp.indexer.UByteRawIndexer; +import org.bytedeco.opencv.global.opencv_imgproc; +import org.bytedeco.opencv.opencv_core.*; +import org.opencv.core.CvType; + +import java.util.Map; + +import static org.bytedeco.opencv.global.opencv_imgproc.*; + +public class OCRDetectionTranslator implements Translator { + + private Image image; + private final int max_side_len; + private final int max_candidates; + private final int min_size; + private final float box_thresh; + private final float unclip_ratio; + private float ratio_h; + private float ratio_w; + private int img_height; + private int img_width; + + public OCRDetectionTranslator(Map arguments) { + max_side_len = + arguments.containsKey("max_side_len") + ? Integer.parseInt(arguments.get("max_side_len").toString()) + : 960; + max_candidates = + arguments.containsKey("max_candidates") + ? Integer.parseInt(arguments.get("max_candidates").toString()) + : 1000; + min_size = + arguments.containsKey("min_size") + ? Integer.parseInt(arguments.get("min_size").toString()) + : 3; + box_thresh = + arguments.containsKey("box_thresh") + ? Float.parseFloat(arguments.get("box_thresh").toString()) + : 0.5f; + unclip_ratio = + arguments.containsKey("unclip_ratio") + ? Float.parseFloat(arguments.get("unclip_ratio").toString()) + : 1.6f; + } + + @Override + public NDList processOutput(TranslatorContext ctx, NDList list) { + NDManager manager = ctx.getNDManager(); + NDArray pred = list.singletonOrThrow(); + pred = pred.squeeze(); + NDArray segmentation = pred.toType(DataType.UINT8, true).gt(0.3); // thresh=0.3 .mul(255f) + + segmentation = segmentation.toType(DataType.UINT8, true); + + //convert from NDArray to Mat + byte[] byteArray = segmentation.toByteArray(); + Shape shape = segmentation.getShape(); + int rows = (int) shape.get(0); + int cols = (int) shape.get(1); + + Mat srcMat = new Mat(rows, cols, CvType.CV_8U); + + UByteRawIndexer ldIdx = srcMat.createIndexer(); + for (int row = 0; row < rows; row++) { + for (int col = 0; col < cols; col++) { + ldIdx.put(row, col, byteArray[row * cols + col]); + } + } + ldIdx.release(); + + Mat mask = new Mat(); + // size 越小，腐蚀的单位越小，图片越接近原图 + Mat structImage = + opencv_imgproc.getStructuringElement(opencv_imgproc.MORPH_RECT, new Size(2, 2)); + + /** + * 膨胀 膨胀说明： 图像的一部分区域与指定的核进行卷积， 求核的最`大`值并赋值给指定区域。 膨胀可以理解为图像中`高亮区域`的'领域扩大'。 + * 意思是高亮部分会侵蚀不是高亮的部分，使高亮部分越来越多。 + */ + opencv_imgproc.dilate(srcMat, mask, structImage); + + ldIdx = mask.createIndexer(); + for (int row = 0; row < rows; row++) { + for (int col = 0; col < cols; col++) { + ldIdx.put(row, col, ldIdx.get(row, col) * 255); + } + } + ldIdx.release(); + + NDArray boxes = boxes_from_bitmap(manager, pred, mask, box_thresh); + + //boxes[:, :, 0] = boxes[:, :, 0] / ratio_w + NDArray boxes1 = boxes.get(":, :, 0").div(ratio_w); + boxes.set(new NDIndex(":, :, 0"), boxes1); + //boxes[:, :, 1] = boxes[:, :, 1] / ratio_h + NDArray boxes2 = boxes.get(":, :, 1").div(ratio_h); + boxes.set(new NDIndex(":, :, 1"), boxes2); + + NDList dt_boxes = this.filter_tag_det_res(boxes); + + dt_boxes.detach(); + + // release Mat + srcMat.release(); + mask.release(); + structImage.release(); + + return dt_boxes; + } + + + private NDList filter_tag_det_res(NDArray dt_boxes) { + NDList boxesList = new NDList(); + + int num = (int) dt_boxes.getShape().get(0); + for (int i = 0; i < num; i++) { + NDArray box = dt_boxes.get(i); + box = order_points_clockwise(box); + box = clip_det_res(box); + float[] box0 = box.get(0).toFloatArray(); + float[] box1 = box.get(1).toFloatArray(); + float[] box3 = box.get(3).toFloatArray(); + int rect_width = (int) Math.sqrt(Math.pow(box1[0] - box0[0], 2) + Math.pow(box1[1] - box0[1], 2)); + int rect_height = (int) Math.sqrt(Math.pow(box3[0] - box0[0], 2) + Math.pow(box3[1] - box0[1], 2)); + if (rect_width <= 3 || rect_height <= 3) + continue; + boxesList.add(box); + } + + return boxesList; + } + + private NDArray clip_det_res(NDArray points) { + for (int i = 0; i < points.getShape().get(0); i++) { + int value = Math.max((int) points.get(i, 0).toFloatArray()[0], 0); + value = Math.min(value, img_width - 1); + points.set(new NDIndex(i + ",0"), value); + value = Math.max((int) points.get(i, 1).toFloatArray()[0], 0); + value = Math.min(value, img_height - 1); + points.set(new NDIndex(i + ",1"), value); + } + + return points; + } + + /** + * sort the points based on their x-coordinates + * 顺时针 + * + * @param pts + * @return + */ + + private NDArray order_points_clockwise(NDArray pts) { + NDList list = new NDList(); + long[] indexes = pts.get(":, 0").argSort().toLongArray(); + + // grab the left-most and right-most points from the sorted + // x-roodinate points + Shape s1 = pts.getShape(); + NDArray leftMost1 = pts.get(indexes[0] + ",:"); + NDArray leftMost2 = pts.get(indexes[1] + ",:"); + NDArray leftMost = leftMost1.concat(leftMost2).reshape(2, 2); + NDArray rightMost1 = pts.get(indexes[2] + ",:"); + NDArray rightMost2 = pts.get(indexes[3] + ",:"); + NDArray rightMost = rightMost1.concat(rightMost2).reshape(2, 2); + + // now, sort the left-most coordinates according to their + // y-coordinates so we can grab the top-left and bottom-left + // points, respectively + indexes = leftMost.get(":, 1").argSort().toLongArray(); + NDArray lt = leftMost.get(indexes[0] + ",:"); + NDArray lb = leftMost.get(indexes[1] + ",:"); + indexes = rightMost.get(":, 1").argSort().toLongArray(); + NDArray rt = rightMost.get(indexes[0] + ",:"); + NDArray rb = rightMost.get(indexes[1] + ",:"); + + list.add(lt); + list.add(rt); + list.add(rb); + list.add(lb); + + NDArray rect = NDArrays.concat(list).reshape(4, 2); + return rect; + } + + /** + * Get boxes from the binarized image predicted by DB + * + * @param manager + * @param pred the binarized image predicted by DB. + * @param mask new 'pred' after threshold filtering. + */ + private NDArray boxes_from_bitmap(NDManager manager, NDArray pred, Mat mask, float box_thresh) { + int dest_height = (int) pred.getShape().get(0); + int dest_width = (int) pred.getShape().get(1); + int height = mask.rows(); + int width = mask.cols(); + + MatVector contours = new MatVector(); + Mat hierarchy = new Mat(); + // 寻找轮廓 + findContours( + mask, + contours, + hierarchy, + opencv_imgproc.RETR_LIST, + opencv_imgproc.CHAIN_APPROX_SIMPLE, + new Point(0, 0)); + + int num_contours = Math.min((int) contours.size(), max_candidates); + NDList boxList = new NDList(); +// NDArray boxes = manager.zeros(new Shape(num_contours, 4, 2), DataType.FLOAT32); + float[] scores = new float[num_contours]; + + int count = 0; + for (int index = 0; index < num_contours; index++) { + Mat contour = contours.get(index); + float[][] pointsArr = new float[4][2]; + int sside = get_mini_boxes(contour, pointsArr); + if (sside < this.min_size) + continue; + NDArray points = manager.create(pointsArr); + float score = box_score_fast(manager, pred, points); + if (score < this.box_thresh) + continue; + + NDArray box = unclip(manager, points); // TODO get_mini_boxes(box) + + + // box[:, 0] = np.clip(np.round(box[:, 0] / width * dest_width), 0, dest_width) + NDArray boxes1 = box.get(":,0").div(width).mul(dest_width).round().clip(0, dest_width); + box.set(new NDIndex(":, 0"), boxes1); + // box[:, 1] = np.clip(np.round(box[:, 1] / height * dest_height), 0, dest_height) + NDArray boxes2 = box.get(":,1").div(height).mul(dest_height).round().clip(0, dest_height); + box.set(new NDIndex(":, 1"), boxes2); + + if (score > box_thresh) { + boxList.add(box); +// boxes.set(new NDIndex(count + ",:,:"), box); + scores[index] = score; + count++; + } + + // release memory + contour.release(); + } +// if (count < num_contours) { +// NDArray newBoxes = manager.zeros(new Shape(count, 4, 2), DataType.FLOAT32); +// newBoxes.set(new NDIndex("0,0,0"), boxes.get(":" + count + ",:,:")); +// boxes = newBoxes; +// } + NDArray boxes = NDArrays.stack(boxList); + + // release + hierarchy.release(); + contours.releaseReference(); + + return boxes; + } + + /** + * Shrink or expand the boxaccording to 'unclip_ratio' + * + * @param points The predicted box. + * @return uncliped box + */ + private NDArray unclip(NDManager manager, NDArray points) { + points = order_points_clockwise(points); + float[] pointsArr = points.toFloatArray(); + float[] lt = java.util.Arrays.copyOfRange(pointsArr, 0, 2); + float[] lb = java.util.Arrays.copyOfRange(pointsArr, 6, 8); + + float[] rt = java.util.Arrays.copyOfRange(pointsArr, 2, 4); + float[] rb = java.util.Arrays.copyOfRange(pointsArr, 4, 6); + + float width = distance(lt, rt); + float height = distance(lt, lb); + + if (width > height) { + float k = (lt[1] - rt[1]) / (lt[0] - rt[0]); // y = k * x + b + + float delta_dis = height; + float delta_x = (float) Math.sqrt((delta_dis * delta_dis) / (k * k + 1)); + float delta_y = Math.abs(k * delta_x); + + if (k > 0) { + pointsArr[0] = lt[0] - delta_x + delta_y; + pointsArr[1] = lt[1] - delta_y - delta_x; + pointsArr[2] = rt[0] + delta_x + delta_y; + pointsArr[3] = rt[1] + delta_y - delta_x; + + pointsArr[4] = rb[0] + delta_x - delta_y; + pointsArr[5] = rb[1] + delta_y + delta_x; + pointsArr[6] = lb[0] - delta_x - delta_y; + pointsArr[7] = lb[1] - delta_y + delta_x; + } else { + pointsArr[0] = lt[0] - delta_x - delta_y; + pointsArr[1] = lt[1] + delta_y - delta_x; + pointsArr[2] = rt[0] + delta_x - delta_y; + pointsArr[3] = rt[1] - delta_y - delta_x; + + pointsArr[4] = rb[0] + delta_x + delta_y; + pointsArr[5] = rb[1] - delta_y + delta_x; + pointsArr[6] = lb[0] - delta_x + delta_y; + pointsArr[7] = lb[1] + delta_y + delta_x; + } + } else { + float k = (lt[1] - rt[1]) / (lt[0] - rt[0]); // y = k * x + b + + float delta_dis = width; + float delta_y = (float) Math.sqrt((delta_dis * delta_dis) / (k * k + 1)); + float delta_x = Math.abs(k * delta_y); + + if (k > 0) { + pointsArr[0] = lt[0] + delta_x - delta_y; + pointsArr[1] = lt[1] - delta_y - delta_x; + pointsArr[2] = rt[0] + delta_x + delta_y; + pointsArr[3] = rt[1] - delta_y + delta_x; + + pointsArr[4] = rb[0] - delta_x + delta_y; + pointsArr[5] = rb[1] + delta_y + delta_x; + pointsArr[6] = lb[0] - delta_x - delta_y; + pointsArr[7] = lb[1] + delta_y - delta_x; + } else { + pointsArr[0] = lt[0] - delta_x - delta_y; + pointsArr[1] = lt[1] - delta_y + delta_x; + pointsArr[2] = rt[0] - delta_x + delta_y; + pointsArr[3] = rt[1] - delta_y - delta_x; + + pointsArr[4] = rb[0] + delta_x + delta_y; + pointsArr[5] = rb[1] + delta_y - delta_x; + pointsArr[6] = lb[0] + delta_x - delta_y; + pointsArr[7] = lb[1] + delta_y + delta_x; + } + } + points = manager.create(pointsArr).reshape(4, 2); + + return points; + } + + private float distance(float[] point1, float[] point2) { + float disX = point1[0] - point2[0]; + float disY = point1[1] - point2[1]; + float dis = (float) Math.sqrt(disX * disX + disY * disY); + return dis; + } + + /** + * Get boxes from the contour or box. + * + * @param contour The predicted contour. + * @param pointsArr The predicted box. + * @return smaller side of box + */ + private int get_mini_boxes(Mat contour, float[][] pointsArr) { + // https://blog.csdn.net/qq_37385726/article/details/82313558 + // bounding_box[1] - rect 返回矩形的长和宽 + RotatedRect rect = minAreaRect(contour); + Mat points = new Mat(); + boxPoints(rect, points); + + FloatRawIndexer ldIdx = points.createIndexer(); + float[][] fourPoints = new float[4][2]; + for (int row = 0; row < 4; row++) { + fourPoints[row][0] = ldIdx.get(row, 0); + fourPoints[row][1] = ldIdx.get(row, 1); + } + ldIdx.release(); + + float[] tmpPoint = new float[2]; + for (int i = 0; i < 4; i++) { + for (int j = i + 1; j < 4; j++) { + if (fourPoints[j][0] < fourPoints[i][0]) { + tmpPoint[0] = fourPoints[i][0]; + tmpPoint[1] = fourPoints[i][1]; + fourPoints[i][0] = fourPoints[j][0]; + fourPoints[i][1] = fourPoints[j][1]; + fourPoints[j][0] = tmpPoint[0]; + fourPoints[j][1] = tmpPoint[1]; + } + } + } + + int index_1 = 0; + int index_2 = 1; + int index_3 = 2; + int index_4 = 3; + + if (fourPoints[1][1] > fourPoints[0][1]) { + index_1 = 0; + index_4 = 1; + } else { + index_1 = 1; + index_4 = 0; + } + + if (fourPoints[3][1] > fourPoints[2][1]) { + index_2 = 2; + index_3 = 3; + } else { + index_2 = 3; + index_3 = 2; + } + + pointsArr[0] = fourPoints[index_1]; + pointsArr[1] = fourPoints[index_2]; + pointsArr[2] = fourPoints[index_3]; + pointsArr[3] = fourPoints[index_4]; + + int height = rect.boundingRect().height(); + int width = rect.boundingRect().width(); + int sside = Math.min(height, width); + + + // release + points.release(); + rect.releaseReference(); + + return sside; + } + + /** + * Calculate the score of box. + * + * @param bitmap The binarized image predicted by DB. + * @param points The predicted box + * @return + */ + private float box_score_fast(NDManager manager, NDArray bitmap, NDArray points) { + NDArray box = points.get(":"); + long h = bitmap.getShape().get(0); + long w = bitmap.getShape().get(1); + // xmin = np.clip(np.floor(box[:, 0].min()).astype(np.int), 0, w - 1) + int xmin = box.get(":, 0").min().floor().clip(0, w - 1).toType(DataType.INT32, true).toIntArray()[0]; + int xmax = box.get(":, 0").max().ceil().clip(0, w - 1).toType(DataType.INT32, true).toIntArray()[0]; + int ymin = box.get(":, 1").min().floor().clip(0, h - 1).toType(DataType.INT32, true).toIntArray()[0]; + int ymax = box.get(":, 1").max().ceil().clip(0, h - 1).toType(DataType.INT32, true).toIntArray()[0]; + + NDArray mask = manager.zeros(new Shape(ymax - ymin + 1, xmax - xmin + 1), DataType.UINT8); + + box.set(new NDIndex(":, 0"), box.get(":, 0").sub(xmin)); + box.set(new NDIndex(":, 1"), box.get(":, 1").sub(ymin)); + + //mask - convert from NDArray to Mat + byte[] maskArray = mask.toByteArray(); + int rows = (int) mask.getShape().get(0); + int cols = (int) mask.getShape().get(1); + Mat maskMat = new Mat(rows, cols, CvType.CV_8U); + UByteRawIndexer ldIdx = maskMat.createIndexer(); + for (int row = 0; row < rows; row++) { + for (int col = 0; col < cols; col++) { + ldIdx.put(row, col, maskArray[row * cols + col]); + } + } + ldIdx.release(); + + //mask - convert from NDArray to Mat + float[] boxArray = box.toFloatArray(); + Mat boxMat = new Mat(4, 2, CvType.CV_32S); + IntRawIndexer intRawIndexer = boxMat.createIndexer(); + for (int row = 0; row < 4; row++) { + intRawIndexer.put(row, 0, (int) boxArray[row * 2]); + intRawIndexer.put(row, 1, (int) boxArray[row * 2 + 1]); + } + intRawIndexer.release(); + +// boxMat.reshape(1, new int[]{1, 4, 2}); + MatVector matVector = new MatVector(); + matVector.put(boxMat); + fillPoly(maskMat, matVector, new Scalar(1)); + + + NDArray subBitMap = bitmap.get(ymin + ":" + (ymax + 1) + "," + xmin + ":" + (xmax + 1)); + float[] subBitMapArr = subBitMap.toFloatArray(); + rows = (int) subBitMap.getShape().get(0); + cols = (int) subBitMap.getShape().get(1); + Mat bitMapMat = new Mat(rows, cols, CvType.CV_32F); + FloatRawIndexer floatRawIndexer = bitMapMat.createIndexer(); + for (int row = 0; row < rows; row++) { + for (int col = 0; col < cols; col++) { + floatRawIndexer.put(row, col, subBitMapArr[row * cols + col]); + } + } + floatRawIndexer.release(); + + Scalar score = org.bytedeco.opencv.global.opencv_core.mean(bitMapMat, maskMat); + float scoreValue = (float) score.get(); + // release + maskMat.release(); + boxMat.release(); + bitMapMat.release(); + matVector.releaseReference(); + score.releaseReference(); + + return scoreValue; + } + + @Override + public NDList processInput(TranslatorContext ctx, Image input) { + NDArray img = input.toNDArray(ctx.getNDManager()); + image = BufferedImageFactory.getInstance().fromNDArray(img); + int h = input.getHeight(); + int w = input.getWidth(); + img_height = h; + img_width = w; + int resize_w = w; + int resize_h = h; + + // limit the max side + float ratio = 1.0f; + if (Math.max(resize_h, resize_w) > max_side_len) { + if (resize_h > resize_w) { + ratio = (float) max_side_len / (float) resize_h; + } else { + ratio = (float) max_side_len / (float) resize_w; + } + } + + resize_h = (int) (resize_h * ratio); + resize_w = (int) (resize_w * ratio); + + if (resize_h % 32 == 0) { + resize_h = resize_h; + } else if (Math.floor((float) resize_h / 32f) <= 1) { + resize_h = 32; + } else { + resize_h = (int) Math.floor((float) resize_h / 32f) * 32; + } + + if (resize_w % 32 == 0) { + resize_w = resize_w; + } else if (Math.floor((float) resize_w / 32f) <= 1) { + resize_w = 32; + } else { + resize_w = (int) Math.floor((float) resize_w / 32f) * 32; + } + + ratio_h = resize_h / (float) h; + ratio_w = resize_w / (float) w; + + img = NDImageUtils.resize(img, resize_w, resize_h); + img = NDImageUtils.toTensor(img); + img = + NDImageUtils.normalize( + img, + new float[]{0.485f, 0.456f, 0.406f}, + new float[]{0.229f, 0.224f, 0.225f}); + img = img.expandDims(0); + return new NDList(img); + } + + @Override + public Batchifier getBatchifier() { + return null; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OcrV3Detection.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OcrV3Detection.java new file mode 100644 index 00000000..4573c345 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/OcrV3Detection.java @@ -0,0 +1,34 @@ +package jnpf.ocr_sdk.utils.detection; + +import ai.djl.modality.cv.Image; +import ai.djl.ndarray.NDList; +import ai.djl.repository.zoo.Criteria; +import ai.djl.training.util.ProgressBar; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.concurrent.ConcurrentHashMap; + +public final class OcrV3Detection { + + private static final Logger logger = LoggerFactory.getLogger(OcrV3Detection.class); + + public OcrV3Detection() { + } + + public Criteria detectCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, NDList.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv3_det_infer.zip") + // .optModelUrls( + // "/Users/calvin/Documents/build/paddle_models/ppocr/ch_PP-OCRv2_det_infer") + .optTranslator(new OCRDetectionTranslator(new ConcurrentHashMap())) + .optProgress(new ProgressBar()) + .build(); + + return criteria; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/PpWordDetectionTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/PpWordDetectionTranslator.java new file mode 100644 index 00000000..c3f5e2b2 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/detection/PpWordDetectionTranslator.java @@ -0,0 +1,120 @@ +/* + * Copyright 2021 Amazon.com, Inc. or its affiliates. All Rights Reserved. + * + * Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance + * with the License. A copy of the License is located at + * + * http://aws.amazon.com/apache2.0/ + * + * or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES + * OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions + * and limitations under the License. + */ +package jnpf.ocr_sdk.utils.detection; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.types.DataType; +import ai.djl.ndarray.types.Shape; +import ai.djl.paddlepaddle.zoo.cv.objectdetection.BoundFinder; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; + +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import java.util.stream.IntStream; + +public class PpWordDetectionTranslator implements Translator { + + private final int max_side_len; + + public PpWordDetectionTranslator(Map arguments) { + max_side_len = + arguments.containsKey("maxLength") + ? Integer.parseInt(arguments.get("maxLength").toString()) + : 960; + } + + @Override + public DetectedObjects processOutput(TranslatorContext ctx, NDList list) { + NDArray result = list.singletonOrThrow(); + result = result.squeeze().mul(255f).toType(DataType.UINT8, true).gt(0.3); // thresh=0.3 + boolean[] flattened = result.toBooleanArray(); + Shape shape = result.getShape(); + int w = (int) shape.get(0); + int h = (int) shape.get(1); + boolean[][] grid = new boolean[w][h]; + IntStream.range(0, flattened.length) + .parallel() + .forEach(i -> grid[i / h][i % h] = flattened[i]); + List boxes = new BoundFinder(grid).getBoxes(); + List names = new ArrayList<>(); + List probs = new ArrayList<>(); + int boxSize = boxes.size(); + for (int i = 0; i < boxSize; i++) { + names.add("word"); + probs.add(1.0); + } + return new DetectedObjects(names, probs, boxes); + } + + @Override + public NDList processInput(TranslatorContext ctx, Image input) { + NDArray img = input.toNDArray(ctx.getNDManager()); + int h = input.getHeight(); + int w = input.getWidth(); + int resize_w = w; + int resize_h = h; + + // limit the max side + float ratio = 1.0f; + if (Math.max(resize_h, resize_w) > max_side_len) { + if (resize_h > resize_w) { + ratio = (float) max_side_len / (float) resize_h; + } else { + ratio = (float) max_side_len / (float) resize_w; + } + } + + resize_h = (int) (resize_h * ratio); + resize_w = (int) (resize_w * ratio); + + if (resize_h % 32 == 0) { + resize_h = resize_h; + } else if (Math.floor((float) resize_h / 32f) <= 1) { + resize_h = 32; + } else { + resize_h = (int) Math.floor((float) resize_h / 32f) * 32; + } + + if (resize_w % 32 == 0) { + resize_w = resize_w; + } else if (Math.floor((float) resize_w / 32f) <= 1) { + resize_w = 32; + } else { + resize_w = (int) Math.floor((float) resize_w / 32f) * 32; + } + + img = NDImageUtils.resize(img, resize_w, resize_h); + img = NDImageUtils.toTensor(img); + img = + NDImageUtils.normalize( + img, + new float[]{0.485f, 0.456f, 0.406f}, + new float[]{0.229f, 0.224f, 0.225f}); + img = img.expandDims(0); + return new NDList(img); + } + + @Override + public Batchifier getBatchifier() { + return null; + } + +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetection.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetection.java new file mode 100644 index 00000000..b7ff2131 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetection.java @@ -0,0 +1,32 @@ +package jnpf.ocr_sdk.utils.layout; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.repository.zoo.Criteria; +import ai.djl.training.util.ProgressBar; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +public final class LayoutDetection { + + private static final Logger logger = LoggerFactory.getLogger(LayoutDetection.class); + + public LayoutDetection() {} + + public Criteria criteria() { + + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, DetectedObjects.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ppyolov2_r50vd_dcn_365e_publaynet_infer.zip") + // .optModelUrls( + // "/Users/calvin/.paddledet/inference_model/ppyolov2_r50vd_dcn_365e_publaynet/ppyolov2_r50vd_dcn_365e_publaynet_infer") + .optTranslator(new LayoutDetectionTranslator()) + .optProgress(new ProgressBar()) + .build(); + + return criteria; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetectionTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetectionTranslator.java new file mode 100644 index 00000000..80efcaa8 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/layout/LayoutDetectionTranslator.java @@ -0,0 +1,104 @@ +package jnpf.ocr_sdk.utils.layout; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.types.DataType; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; + +import java.util.ArrayList; +import java.util.List; + +public class LayoutDetectionTranslator implements Translator { + + private int width; + private int height; + + public LayoutDetectionTranslator() {} + + @Override + public DetectedObjects processOutput(TranslatorContext ctx, NDList list) { + NDArray result = list.get(0); // np_boxes + long rows = result.size(0); + + List boxes = new ArrayList<>(); + List names = new ArrayList<>(); + List probs = new ArrayList<>(); + + for (long i = 0; i < rows; i++) { + NDArray row = result.get(i); + float[] array = row.toFloatArray(); + if (array[1] <= 0.5 || array[0] <= -1) continue; + int clsid = (int) array[0]; + double score = array[1]; + String name = ""; + switch (clsid) { + case 0: + name = "Text"; + break; + case 1: + name = "Title"; + break; + case 2: + name = "List"; + break; + case 3: + name = "Table"; + break; + case 4: + name = "Figure"; + break; + default: + name = "Unknown"; + } + + float x = array[2] / width; + float y = array[3] / height; + float w = (array[4] - array[2]) / width; + float h = (array[5] - array[3]) / height; + + Rectangle rect = new Rectangle(x, y, w, h); + boxes.add(rect); + names.add(name); + probs.add(score); + } + + return new DetectedObjects(names, probs, boxes); + } + + @Override + public NDList processInput(TranslatorContext ctx, Image input) { + NDArray img = input.toNDArray(ctx.getNDManager()); + width = input.getWidth(); + height = input.getHeight(); + + img = NDImageUtils.resize(img, 640, 640); + img = img.transpose(2, 0, 1).div(255); + img = + NDImageUtils.normalize( + img, new float[] {0.485f, 0.456f, 0.406f}, new float[] {0.229f, 0.224f, 0.225f}); + img = img.expandDims(0); + + NDArray scale_factor = ctx.getNDManager().create(new float[] {640f / height, 640f / width}); + scale_factor = scale_factor.toType(DataType.FLOAT32, false); + scale_factor = scale_factor.expandDims(0); + + NDArray im_shape = ctx.getNDManager().create(new float[] {640f, 640f}); + im_shape = im_shape.toType(DataType.FLOAT32, false); + im_shape = im_shape.expandDims(0); + + // im_shape, image, scale_factor + return new NDList(im_shape, img, scale_factor); + } + + @Override + public Batchifier getBatchifier() { + return null; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/NDArrayUtils.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/NDArrayUtils.java new file mode 100644 index 00000000..1da0badb --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/NDArrayUtils.java @@ -0,0 +1,64 @@ +package jnpf.ocr_sdk.utils.opencv; + +import ai.djl.ndarray.NDArray; +import org.bytedeco.javacpp.indexer.DoubleRawIndexer; +import org.bytedeco.opencv.global.opencv_core; +import org.bytedeco.opencv.opencv_core.Mat; +import org.bytedeco.opencv.opencv_core.Point2f; + +import java.util.List; + +public class NDArrayUtils { + // NDArray 转 opencv_core.Mat + public static Mat toOpenCVMat(NDArray points, int rows, int cols) { + double[] doubleArray = points.toDoubleArray(); + // CV_32F = FloatRawIndexer + // CV_64F = DoubleRawIndexer + Mat mat = new Mat(rows, cols, opencv_core.CV_64F); + + DoubleRawIndexer ldIdx = mat.createIndexer(); + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + ldIdx.put(i, j, doubleArray[i * cols + j]); + } + } + ldIdx.release(); + + return mat; + } + + // NDArray 转 opencv_core.Point2f + public static Point2f toOpenCVPoint2f(NDArray points, int rows) { + double[] doubleArray = points.toDoubleArray(); + Point2f points2f = new Point2f(rows); + + for (int i = 0; i < rows; i++) { + points2f.position(i).x((float) doubleArray[i * 2]).y((float) doubleArray[i * 2 + 1]); + } + + return points2f; + } + + // Double array 转 opencv_core.Point2f + public static Point2f toOpenCVPoint2f(double[] doubleArray, int rows) { + Point2f points2f = new Point2f(rows); + + for (int i = 0; i < rows; i++) { + points2f.position(i).x((float) doubleArray[i * 2]).y((float) doubleArray[i * 2 + 1]); + } + + return points2f; + } + + // list 转 opencv_core.Point2f + public static Point2f toOpenCVPoint2f(List points, int rows) { + Point2f points2f = new Point2f(points.size()); + + for (int i = 0; i < rows; i++) { + ai.djl.modality.cv.output.Point point = points.get(i); + points2f.position(i).x((float) point.getX()).y((float) point.getY()); + } + + return points2f; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/OpenCVUtils.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/OpenCVUtils.java new file mode 100644 index 00000000..92a7731c --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/opencv/OpenCVUtils.java @@ -0,0 +1,72 @@ +package jnpf.ocr_sdk.utils.opencv; + +import org.bytedeco.opencv.global.opencv_imgproc; +import org.bytedeco.opencv.opencv_core.Mat; +import org.bytedeco.opencv.opencv_core.Point2f; +import org.opencv.core.CvType; +import org.opencv.imgproc.Imgproc; + +import java.awt.image.BufferedImage; +import java.awt.image.DataBufferByte; +import java.awt.image.WritableRaster; + + +public class OpenCVUtils { + + public static Mat perspectiveTransform( + Mat src, Point2f srcPoints, Point2f dstPoints) { + Mat dst = src.clone(); + Mat warp_mat = opencv_imgproc.getPerspectiveTransform(srcPoints.position(0), dstPoints.position(0)); + opencv_imgproc.warpPerspective(src, dst, warp_mat, dst.size()); + warp_mat.release(); + + return dst; + } + + /** + * Mat to BufferedImage + * + * @param mat + * @return + */ + public static BufferedImage mat2Image(org.opencv.core.Mat mat) { + int width = mat.width(); + int height = mat.height(); + byte[] data = new byte[width * height * (int) mat.elemSize()]; + Imgproc.cvtColor(mat, mat, 4); + mat.get(0, 0, data); + BufferedImage ret = new BufferedImage(width, height, 5); + ret.getRaster().setDataElements(0, 0, width, height, data); + return ret; + } + + public static BufferedImage matToBufferedImage(org.opencv.core.Mat frame) { + int type = 0; + if (frame.channels() == 1) { + type = BufferedImage.TYPE_BYTE_GRAY; + } else if (frame.channels() == 3) { + type = BufferedImage.TYPE_3BYTE_BGR; + } + BufferedImage image = new BufferedImage(frame.width(), frame.height(), type); + WritableRaster raster = image.getRaster(); + DataBufferByte dataBuffer = (DataBufferByte) raster.getDataBuffer(); + byte[] data = dataBuffer.getData(); + frame.get(0, 0, data); + return image; + } + + /** + * BufferedImage to Mat + * + * @param img + * @return + */ + public static org.opencv.core.Mat image2Mat(BufferedImage img) { + int width = img.getWidth(); + int height = img.getHeight(); + byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData(); + org.opencv.core.Mat mat = new org.opencv.core.Mat(height, width, CvType.CV_8UC3); + mat.put(0, 0, data); + return mat; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3AlignedRecognition.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3AlignedRecognition.java new file mode 100644 index 00000000..0ac9fc9f --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3AlignedRecognition.java @@ -0,0 +1,129 @@ +package jnpf.ocr_sdk.utils.recognition; + +import ai.djl.inference.Predictor; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import ai.djl.paddlepaddle.zoo.cv.objectdetection.PpWordDetectionTranslator; +import ai.djl.repository.zoo.Criteria; +import ai.djl.training.util.ProgressBar; +import ai.djl.translate.TranslateException; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.ArrayList; +import java.util.List; +import java.util.concurrent.ConcurrentHashMap; + +public final class OcrV3AlignedRecognition { + + private static final Logger logger = LoggerFactory.getLogger(OcrV3AlignedRecognition.class); + + public OcrV3AlignedRecognition() { + } + + public DetectedObjects predict( + Image image, Predictor detector, Predictor recognizer) + throws TranslateException { + DetectedObjects detections = detector.predict(image); + + List boxes = detections.items(); + + List names = new ArrayList<>(); + List prob = new ArrayList<>(); + List rect = new ArrayList<>(); + + long timeInferStart = System.currentTimeMillis(); + for (int i = 0; i < boxes.size(); i++) { + Image subImg = getSubImage(image, boxes.get(i).getBoundingBox()); + if (subImg.getHeight() * 1.0 / subImg.getWidth() > 1.5) { + subImg = rotateImg(subImg); + } +// ImageUtils.saveImage(subImg, i + ".png", "build/output"); + String name = recognizer.predict(subImg); + names.add(name); + prob.add(-1.0); + rect.add(boxes.get(i).getBoundingBox()); + } + long timeInferEnd = System.currentTimeMillis(); + System.out.println("time: " + (timeInferEnd - timeInferStart)); + + DetectedObjects detectedObjects = new DetectedObjects(names, prob, rect); + + return detectedObjects; + } + + public Criteria detectCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, DetectedObjects.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv3_det_infer.zip") + // .optModelUrls( + // "/Users/calvin/Documents/build/paddle_models/ppocr/ch_PP-OCRv2_det_infer") + .optTranslator(new PpWordDetectionTranslator(new ConcurrentHashMap())) + .optProgress(new ProgressBar()) + .build(); + + return criteria; + } + + public Criteria recognizeCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, String.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv3_rec_infer.zip") + .optProgress(new ProgressBar()) + .optTranslator(new PpWordRecognitionTranslator((new ConcurrentHashMap()))) + .build(); + + return criteria; + } + + private Image getSubImage(Image img, BoundingBox box) { + Rectangle rect = box.getBounds(); + double[] extended = extendRect(rect.getX(), rect.getY(), rect.getWidth(), rect.getHeight()); + int width = img.getWidth(); + int height = img.getHeight(); + int[] recovered = { + (int) (extended[0] * width), + (int) (extended[1] * height), + (int) (extended[2] * width), + (int) (extended[3] * height) + }; + + return img.getSubImage(recovered[0], recovered[1], recovered[2], recovered[3]); + } + + private double[] extendRect(double xmin, double ymin, double width, double height) { + double centerx = xmin + width / 2; + double centery = ymin + height / 2; + if (width > height) { + width += height * 2.0; + height *= 3.0; + } else { + height += width * 2.0; + width *= 3.0; + } + double newX = centerx - width / 2 < 0 ? 0 : centerx - width / 2; + double newY = centery - height / 2 < 0 ? 0 : centery - height / 2; + double newWidth = newX + width > 1 ? 1 - newX : width; + double newHeight = newY + height > 1 ? 1 - newY : height; + return new double[]{newX, newY, newWidth, newHeight}; + } + + private Image rotateImg(Image image) { + try (NDManager manager = NDManager.newBaseManager()) { + NDArray rotated = NDImageUtils.rotate90(image.toNDArray(manager), 1); + return ImageFactory.getInstance().fromNDArray(rotated); + } + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3MultiThreadRecognition.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3MultiThreadRecognition.java new file mode 100644 index 00000000..b2e33798 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3MultiThreadRecognition.java @@ -0,0 +1,194 @@ +package jnpf.ocr_sdk.utils.recognition; + +import ai.djl.inference.Predictor; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import ai.djl.paddlepaddle.zoo.cv.objectdetection.PpWordDetectionTranslator; +import ai.djl.repository.zoo.Criteria; +import ai.djl.repository.zoo.ZooModel; +import ai.djl.training.util.ProgressBar; +import ai.djl.translate.TranslateException; +import jnpf.ocr_sdk.utils.common.ImageInfo; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.ArrayList; +import java.util.List; +import java.util.concurrent.*; + +public final class OcrV3MultiThreadRecognition { + + private static final Logger logger = LoggerFactory.getLogger(OcrV3MultiThreadRecognition.class); + + public OcrV3MultiThreadRecognition() { + } + + public DetectedObjects predict( + Image image, List recModels, Predictor detector, int threadNum) + throws TranslateException { + DetectedObjects detections = detector.predict(image); + + List boxes = detections.items(); + + ConcurrentLinkedQueue queue = new ConcurrentLinkedQueue<>(); + for (int i = 0; i < boxes.size(); i++) { + BoundingBox box = boxes.get(i).getBoundingBox(); + Image subImg = getSubImage(image, box); + if (subImg.getHeight() * 1.0 / subImg.getWidth() > 1.5) { + subImg = rotateImg(subImg); + } + ImageInfo imageInfo = new ImageInfo(subImg, box); + queue.add(imageInfo); + } + + List callables = new ArrayList<>(threadNum); + for (int i = 0; i < threadNum; i++) { + callables.add(new InferCallable(recModels.get(i), queue)); + } + + ExecutorService es = Executors.newFixedThreadPool(threadNum); + List resultList = new ArrayList<>(); + try { + List>> futures = new ArrayList<>(); + long timeInferStart = System.currentTimeMillis(); + for (InferCallable callable : callables) { + futures.add(es.submit(callable)); + } + + for (Future> future : futures) { + List subList = future.get(); + if (subList != null) { + resultList.addAll(subList); + } + } + + long timeInferEnd = System.currentTimeMillis(); + System.out.println("time: " + (timeInferEnd - timeInferStart)); + + for (InferCallable callable : callables) { + callable.close(); + } + } catch (InterruptedException | ExecutionException e) { + logger.error("", e); + } finally { + es.shutdown(); + } + + List names = new ArrayList<>(); + List prob = new ArrayList<>(); + List rect = new ArrayList<>(); + for (ImageInfo imageInfo : resultList) { + names.add(imageInfo.getName()); + prob.add(imageInfo.getProb()); + rect.add(imageInfo.getBox()); + } + DetectedObjects detectedObjects = new DetectedObjects(names, prob, rect); + + return detectedObjects; + } + + public Criteria detectCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, DetectedObjects.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv3_det_infer.zip") + // .optModelUrls( + // "/Users/calvin/Documents/build/paddle_models/ppocr/ch_PP-OCRv2_det_infer") + .optTranslator(new PpWordDetectionTranslator(new ConcurrentHashMap())) + .optProgress(new ProgressBar()) + .build(); + + return criteria; + } + + public Criteria recognizeCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, String.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv3_rec_infer.zip") + .optProgress(new ProgressBar()) + .optTranslator(new PpWordRecognitionTranslator((new ConcurrentHashMap()))) + .build(); + + return criteria; + } + + private static class InferCallable implements Callable> { + private Predictor recognizer; + private ConcurrentLinkedQueue queue; + private List resultList = new ArrayList<>(); + + public InferCallable(ZooModel recognitionModel, ConcurrentLinkedQueue queue){ + recognizer = recognitionModel.newPredictor(); + this.queue = queue; + } + + public List call() { + try { + ImageInfo imageInfo = queue.poll(); + while (imageInfo != null) { + String name = recognizer.predict(imageInfo.getImage()); + imageInfo.setName(name); + imageInfo.setProb(-1.0); + resultList.add(imageInfo); + imageInfo = queue.poll(); + } + } catch (Exception e) { + e.printStackTrace(); + } + return resultList; + } + + public void close() { + recognizer.close(); + } + } + + private Image getSubImage(Image img, BoundingBox box) { + Rectangle rect = box.getBounds(); + double[] extended = extendRect(rect.getX(), rect.getY(), rect.getWidth(), rect.getHeight()); + int width = img.getWidth(); + int height = img.getHeight(); + int[] recovered = { + (int) (extended[0] * width), + (int) (extended[1] * height), + (int) (extended[2] * width), + (int) (extended[3] * height) + }; + return img.getSubImage(recovered[0], recovered[1], recovered[2], recovered[3]); + } + + private double[] extendRect(double xmin, double ymin, double width, double height) { + double centerx = xmin + width / 2; + double centery = ymin + height / 2; + if (width > height) { + width += height * 2.0; + height *= 3.0; + } else { + height += width * 2.0; + width *= 3.0; + } + double newX = centerx - width / 2 < 0 ? 0 : centerx - width / 2; + double newY = centery - height / 2 < 0 ? 0 : centery - height / 2; + double newWidth = newX + width > 1 ? 1 - newX : width; + double newHeight = newY + height > 1 ? 1 - newY : height; + return new double[]{newX, newY, newWidth, newHeight}; + } + + private Image rotateImg(Image image) { + try (NDManager manager = NDManager.newBaseManager()) { + NDArray rotated = NDImageUtils.rotate90(image.toNDArray(manager), 1); + return ImageFactory.getInstance().fromNDArray(rotated); + } + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3Recognition.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3Recognition.java new file mode 100644 index 00000000..89687b9b --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/OcrV3Recognition.java @@ -0,0 +1,140 @@ +package jnpf.ocr_sdk.utils.recognition; + +import ai.djl.inference.Predictor; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.Point; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.NDManager; +import ai.djl.opencv.OpenCVImageFactory; +import ai.djl.repository.zoo.Criteria; +import ai.djl.training.util.ProgressBar; +import ai.djl.translate.TranslateException; +import jnpf.ocr_sdk.utils.common.RotatedBox; +import jnpf.ocr_sdk.utils.opencv.NDArrayUtils; +import jnpf.ocr_sdk.utils.opencv.OpenCVUtils; +import org.bytedeco.javacv.Java2DFrameConverter; +import org.bytedeco.javacv.OpenCVFrameConverter; +import org.bytedeco.opencv.opencv_core.Point2f; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.awt.image.BufferedImage; +import java.util.ArrayList; +import java.util.List; +import java.util.concurrent.ConcurrentHashMap; + +public final class OcrV3Recognition { + + private static final Logger logger = LoggerFactory.getLogger(OcrV3Recognition.class); + + public OcrV3Recognition() { + } + + public Criteria recognizeCriteria() { + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, String.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/ch_PP-OCRv3_rec_infer.zip") + .optProgress(new ProgressBar()) + .optTranslator(new PpWordRecognitionTranslator((new ConcurrentHashMap()))) + .build(); + return criteria; + } + + public List predict( + Image image, Predictor detector, Predictor recognizer) + throws TranslateException { + NDList boxes = detector.predict(image); + + List result = new ArrayList<>(); + long timeInferStart = System.currentTimeMillis(); + + OpenCVFrameConverter.ToMat cv = new OpenCVFrameConverter.ToMat(); + OpenCVFrameConverter.ToMat converter1 = new OpenCVFrameConverter.ToMat(); + OpenCVFrameConverter.ToOrgOpenCvCoreMat converter2 = new OpenCVFrameConverter.ToOrgOpenCvCoreMat(); + + for (int i = 0; i < boxes.size(); i++) { + NDArray box = boxes.get(i); +// BufferedImage bufferedImage = get_rotate_crop_image(image, box); + + float[] pointsArr = box.toFloatArray(); + float[] lt = java.util.Arrays.copyOfRange(pointsArr, 0, 2); + float[] rt = java.util.Arrays.copyOfRange(pointsArr, 2, 4); + float[] rb = java.util.Arrays.copyOfRange(pointsArr, 4, 6); + float[] lb = java.util.Arrays.copyOfRange(pointsArr, 6, 8); + int img_crop_width = (int) Math.max(distance(lt, rt), distance(rb, lb)); + int img_crop_height = (int) Math.max(distance(lt, lb), distance(rt, rb)); + List srcPoints = new ArrayList<>(); + srcPoints.add(new Point(lt[0], lt[1])); + srcPoints.add(new Point(rt[0], rt[1])); + srcPoints.add(new Point(rb[0], rb[1])); + srcPoints.add(new Point(lb[0], lb[1])); + List dstPoints = new ArrayList<>(); + dstPoints.add(new Point(0, 0)); + dstPoints.add(new Point(img_crop_width, 0)); + dstPoints.add(new Point(img_crop_width, img_crop_height)); + dstPoints.add(new Point(0, img_crop_height)); + + Point2f srcPoint2f = NDArrayUtils.toOpenCVPoint2f(srcPoints, 4); + Point2f dstPoint2f = NDArrayUtils.toOpenCVPoint2f(dstPoints, 4); + + BufferedImage bufferedImage = OpenCVUtils.matToBufferedImage((org.opencv.core.Mat) image.getWrappedImage()); + // try { + // File outputfile = new File("build/output/srcImage.jpg"); + // ImageIO.write(bufferedImage, "jpg", outputfile); + // } catch (IOException e) { + // e.printStackTrace(); + // } + org.bytedeco.opencv.opencv_core.Mat mat = cv.convertToMat(new Java2DFrameConverter().convert(bufferedImage)); + org.bytedeco.opencv.opencv_core.Mat dstMat = OpenCVUtils.perspectiveTransform(mat, srcPoint2f, dstPoint2f); + org.opencv.core.Mat cvMat = converter2.convert(converter1.convert(dstMat)); + Image subImg = OpenCVImageFactory.getInstance().fromImage(cvMat); +// ImageUtils.saveImage(subImg, i + ".png", "build/output"); + + subImg = subImg.getSubImage(0,0,img_crop_width,img_crop_height); + if (subImg.getHeight() * 1.0 / subImg.getWidth() > 1.5) { + subImg = rotateImg(subImg); + } + + String name = recognizer.predict(subImg); + RotatedBox rotatedBox = new RotatedBox(box, name); + result.add(rotatedBox); + + mat.release(); + dstMat.release(); + cvMat.release(); + srcPoint2f.releaseReference(); + dstPoint2f.releaseReference(); + } + cv.close(); + converter1.close(); + converter2.close(); + long timeInferEnd = System.currentTimeMillis(); + System.out.println("time: " + (timeInferEnd - timeInferStart)); + + return result; + } + + private BufferedImage get_rotate_crop_image(Image image, NDArray box) { + return null; + } + + private float distance(float[] point1, float[] point2) { + float disX = point1[0] - point2[0]; + float disY = point1[1] - point2[1]; + float dis = (float) Math.sqrt(disX * disX + disY * disY); + return dis; + } + + private Image rotateImg(Image image) { + try (NDManager manager = NDManager.newBaseManager()) { + NDArray rotated = NDImageUtils.rotate90(image.toNDArray(manager), 1); + return ImageFactory.getInstance().fromNDArray(rotated); + } + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/PpWordRecognitionTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/PpWordRecognitionTranslator.java new file mode 100644 index 00000000..5d886ac6 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/recognition/PpWordRecognitionTranslator.java @@ -0,0 +1,108 @@ +package jnpf.ocr_sdk.utils.recognition; + +import ai.djl.Model; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.index.NDIndex; +import ai.djl.ndarray.types.DataType; +import ai.djl.ndarray.types.Shape; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; +import ai.djl.util.Utils; + +import java.io.IOException; +import java.io.InputStream; +import java.util.Arrays; +import java.util.List; +import java.util.Map; + +public class PpWordRecognitionTranslator implements Translator { + private List table; + private final boolean use_space_char; + + public PpWordRecognitionTranslator(Map arguments) { + use_space_char = + arguments.containsKey("use_space_char") + ? Boolean.parseBoolean(arguments.get("use_space_char").toString()) + : false; + } + + @Override + public void prepare(TranslatorContext ctx) throws IOException { + Model model = ctx.getModel(); + try (InputStream is = model.getArtifact("ppocr_keys_v1.txt").openStream()) { + table = Utils.readLines(is, true); + table.add(0, "blank"); + if(use_space_char) + table.add(" "); + else + table.add(""); + } + } + + @Override + public String processOutput(TranslatorContext ctx, NDList list) throws IOException { + StringBuilder sb = new StringBuilder(); + NDArray tokens = list.singletonOrThrow(); + + long[] indices = tokens.get(0).argMax(1).toLongArray(); + boolean[] selection = new boolean[indices.length]; + Arrays.fill(selection, true); + for (int i = 1; i < indices.length; i++) { + if (indices[i] == indices[i - 1]) { + selection[i] = false; + } + } + + // 字符置信度 +// float[] probs = new float[indices.length]; +// for (int row = 0; row < indices.length; row++) { +// NDArray value = tokens.get(0).get(new NDIndex(""+ row +":" + (row + 1) +"," + indices[row] +":" + ( indices[row] + 1))); +// probs[row] = value.toFloatArray()[0]; +// } + + int lastIdx = 0; + for (int i = 0; i < indices.length; i++) { + if (selection[i] == true && indices[i] > 0 && !(i > 0 && indices[i] == lastIdx)) { + sb.append(table.get((int) indices[i])); + } + } + return sb.toString(); + } + + @Override + public NDList processInput(TranslatorContext ctx, Image input) { + NDArray img = input.toNDArray(ctx.getNDManager(), Image.Flag.COLOR); + int imgC = 3; + int imgH = 48; + int imgW = 320;//192 320 + + int h = input.getHeight(); + int w = input.getWidth(); + float ratio = (float) w / (float) h; + imgW = (int)(imgH * ratio); + + int resized_w; + if (Math.ceil(imgH * ratio) > imgW) { + resized_w = imgW; + } else { + resized_w = (int) (Math.ceil(imgH * ratio)); + } + img = NDImageUtils.resize(img, resized_w, imgH); + img = img.transpose(2, 0, 1).div(255).sub(0.5f).div(0.5f); + NDArray padding_im = ctx.getNDManager().zeros(new Shape(imgC, imgH, imgW), DataType.FLOAT32); + padding_im.set(new NDIndex(":,:,0:" + resized_w), img); + + padding_im = padding_im.expandDims(0); + return new NDList(padding_im); + } + + @Override + public Batchifier getBatchifier() { + return null; + } + +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/rotation/PpWordRotateTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/rotation/PpWordRotateTranslator.java new file mode 100644 index 00000000..3eaffe02 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/rotation/PpWordRotateTranslator.java @@ -0,0 +1,69 @@ +package jnpf.ocr_sdk.utils.rotation; + +import ai.djl.modality.Classifications; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.index.NDIndex; +import ai.djl.ndarray.types.Shape; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; + +import java.util.Arrays; +import java.util.List; + +public class PpWordRotateTranslator implements Translator { + List classes = Arrays.asList("No Rotate", "Rotate"); + + public PpWordRotateTranslator() {} + + public Classifications processOutput(TranslatorContext ctx, NDList list) { + NDArray prob = list.singletonOrThrow(); + return new Classifications(this.classes, prob); + } + + public NDList processInput(TranslatorContext ctx, Image input) throws Exception { + NDArray img = input.toNDArray(ctx.getNDManager()); + img = NDImageUtils.resize(img, 192, 48); + img = NDImageUtils.toTensor(img).sub(0.5F).div(0.5F); + img = img.expandDims(0); + return new NDList(new NDArray[]{img}); + } + + public NDList processInputBak(TranslatorContext ctx, Image input) throws Exception { + NDArray img = input.toNDArray(ctx.getNDManager()); + int imgC = 3; + int imgH = 48; + int imgW = 192; + + NDArray array = ctx.getNDManager().zeros(new Shape(imgC, imgH, imgW)); + + int h = input.getHeight(); + int w = input.getWidth(); + int resized_w = 0; + + float ratio = (float) w / (float) h; + if (Math.ceil(imgH * ratio) > imgW) { + resized_w = imgW; + } else { + resized_w = (int) (Math.ceil(imgH * ratio)); + } + + img = NDImageUtils.resize(img, resized_w, imgH); + + img = NDImageUtils.toTensor(img).sub(0.5F).div(0.5F); + // img = img.transpose(2, 0, 1); + + array.set(new NDIndex(":,:,0:" + resized_w), img); + + array = array.expandDims(0); + + return new NDList(new NDArray[] {array}); + } + + public Batchifier getBatchifier() { + return null; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/ConvertHtml2Excel.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/ConvertHtml2Excel.java new file mode 100644 index 00000000..f2fe29e4 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/ConvertHtml2Excel.java @@ -0,0 +1,235 @@ +package jnpf.ocr_sdk.utils.table; + +import org.apache.commons.lang3.StringUtils; +import org.apache.commons.lang3.math.NumberUtils; +import org.apache.poi.hssf.usermodel.*; +import org.apache.poi.ss.usermodel.BorderStyle; +import org.apache.poi.ss.usermodel.CellType; +import org.apache.poi.ss.usermodel.HorizontalAlignment; +import org.apache.poi.ss.usermodel.VerticalAlignment; +import org.apache.poi.ss.util.CellRangeAddress; +import org.dom4j.Document; +import org.dom4j.DocumentException; +import org.dom4j.DocumentHelper; +import org.dom4j.Element; + +import java.util.ArrayList; +import java.util.List; + +/** + * @Auther: xiaoqiang + * @Date: 2020/12/9 9:16 + * @Description: + */ +public class ConvertHtml2Excel { + /** + * html表格转excel + * + * @param tableHtml 如 + * + * .. + *
+ * @return + */ + public static HSSFWorkbook table2Excel(String tableHtml) { + HSSFWorkbook wb = new HSSFWorkbook(); + HSSFSheet sheet = wb.createSheet(); + List crossRowEleMetaLs = new ArrayList<>(); + int rowIndex = 0; + try { + Document data = DocumentHelper.parseText(tableHtml); + // 生成表头 + Element thead = data.getRootElement().element("thead"); + HSSFCellStyle titleStyle = getTitleStyle(wb); + int ls=0;//列数 + if (thead != null) { + List trLs = thead.elements("tr"); + for (Element trEle : trLs) { + HSSFRow row = sheet.createRow(rowIndex); + List thLs = trEle.elements("td"); + ls=thLs.size(); + makeRowCell(thLs, rowIndex, row, 0, titleStyle, crossRowEleMetaLs); + rowIndex++; + } + } + // 生成表体 + Element tbody = data.getRootElement().element("tbody"); + HSSFCellStyle contentStyle = getContentStyle(wb); + if (tbody != null) { + List trLs = tbody.elements("tr"); + for (Element trEle : trLs) { + HSSFRow row = sheet.createRow(rowIndex); + List thLs = trEle.elements("th"); + int cellIndex = makeRowCell(thLs, rowIndex, row, 0, titleStyle, crossRowEleMetaLs); + List tdLs = trEle.elements("td"); + makeRowCell(tdLs, rowIndex, row, cellIndex, contentStyle, crossRowEleMetaLs); + rowIndex++; + } + } + // 合并表头 + for (CrossRangeCellMeta crcm : crossRowEleMetaLs) { + sheet.addMergedRegion(new CellRangeAddress(crcm.getFirstRow(), crcm.getLastRow(), crcm.getFirstCol(), crcm.getLastCol())); + setRegionStyle(sheet, new CellRangeAddress(crcm.getFirstRow(), crcm.getLastRow(), crcm.getFirstCol(), crcm.getLastCol()),titleStyle); + } + for(int i=0;i tdLs, int rowIndex, HSSFRow row, int startCellIndex, HSSFCellStyle cellStyle, + List crossRowEleMetaLs) { + int i = startCellIndex; + for (int eleIndex = 0; eleIndex < tdLs.size(); i++, eleIndex++) { + int captureCellSize = getCaptureCellSize(rowIndex, i, crossRowEleMetaLs); + while (captureCellSize > 0) { + for (int j = 0; j < captureCellSize; j++) {// 当前行跨列处理（补单元格） + row.createCell(i); + i++; + } + captureCellSize = getCaptureCellSize(rowIndex, i, crossRowEleMetaLs); + } + Element thEle = tdLs.get(eleIndex); + String val = thEle.getTextTrim(); + if (StringUtils.isBlank(val)) { + Element e = thEle.element("a"); + if (e != null) { + val = e.getTextTrim(); + } + } + HSSFCell c = row.createCell(i); + if (NumberUtils.isNumber(val)) { + c.setCellValue(Double.parseDouble(val)); + c.setCellType(CellType.NUMERIC); + } else { + c.setCellValue(val); + } + int rowSpan = NumberUtils.toInt(thEle.attributeValue("rowspan"), 1); + int colSpan = NumberUtils.toInt(thEle.attributeValue("colspan"), 1); + c.setCellStyle(cellStyle); + if (rowSpan > 1 || colSpan > 1) { // 存在跨行或跨列 + crossRowEleMetaLs.add(new CrossRangeCellMeta(rowIndex, i, rowSpan, colSpan)); + } + if (colSpan > 1) {// 当前行跨列处理（补单元格） + for (int j = 1; j < colSpan; j++) { + i++; + row.createCell(i); + } + } + } + return i; + } + + /** + * 设置合并单元格的边框样式 + * + * @param sheet + * @param region + * @param cs + */ + public static void setRegionStyle(HSSFSheet sheet, CellRangeAddress region, HSSFCellStyle cs) { + for (int i = region.getFirstRow(); i <= region.getLastRow(); i++) { + HSSFRow row = sheet.getRow(i); + for (int j = region.getFirstColumn(); j <= region.getLastColumn(); j++) { + HSSFCell cell = row.getCell(j); + cell.setCellStyle(cs); + } + } + } + + /** + * 获得因rowSpan占据的单元格 + * + * @param rowIndex 行号 + * @param colIndex 列号 + * @param crossRowEleMetaLs 跨行列元数据 + * @return 当前行在某列需要占据单元格 + */ + private static int getCaptureCellSize(int rowIndex, int colIndex, List crossRowEleMetaLs) { + int captureCellSize = 0; + for (CrossRangeCellMeta crossRangeCellMeta : crossRowEleMetaLs) { + if (crossRangeCellMeta.getFirstRow() < rowIndex && crossRangeCellMeta.getLastRow() >= rowIndex) { + if (crossRangeCellMeta.getFirstCol() <= colIndex && crossRangeCellMeta.getLastCol() >= colIndex) { + captureCellSize = crossRangeCellMeta.getLastCol() - colIndex + 1; + } + } + } + return captureCellSize; + } + + /** + * 获得标题样式 + * + * @param workbook + * @return + */ + private static HSSFCellStyle getTitleStyle(HSSFWorkbook workbook) { + //short titlebackgroundcolor = IndexedColors.GREY_25_PERCENT.index; + short fontSize = 12; + String fontName = "宋体"; + HSSFCellStyle style = workbook.createCellStyle(); + style.setVerticalAlignment(VerticalAlignment.CENTER); + style.setAlignment(HorizontalAlignment.CENTER); + style.setBorderBottom(BorderStyle.THIN); //下边框 + style.setBorderLeft(BorderStyle.THIN);//左边框 + style.setBorderTop(BorderStyle.THIN);//上边框 + style.setBorderRight(BorderStyle.THIN);//右边框 + //style.setFillPattern(FillPatternType.SOLID_FOREGROUND); + //style.setFillForegroundColor(titlebackgroundcolor);// 背景色 + + HSSFFont font = workbook.createFont(); + font.setFontName(fontName); + font.setFontHeightInPoints(fontSize); + font.setBold(true); + style.setFont(font); + return style; + } + + /** + * 获得内容样式 + * + * @param wb + * @return + */ + private static HSSFCellStyle getContentStyle(HSSFWorkbook wb) { + short fontSize = 12; + String fontName = "宋体"; + HSSFCellStyle style = wb.createCellStyle(); + style.setBorderBottom(BorderStyle.THIN); //下边框 + style.setBorderLeft(BorderStyle.THIN);//左边框 + style.setBorderTop(BorderStyle.THIN);//上边框 + style.setBorderRight(BorderStyle.THIN);//右边框 + HSSFFont font = wb.createFont(); + font.setFontName(fontName); + font.setFontHeightInPoints(fontSize); + style.setFont(font); + style.setAlignment(HorizontalAlignment.CENTER);//水平居中 + style.setVerticalAlignment(VerticalAlignment.CENTER);//垂直居中 + style.setWrapText(true); + return style; + } +} + diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/CrossRangeCellMeta.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/CrossRangeCellMeta.java new file mode 100644 index 00000000..9d780046 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/CrossRangeCellMeta.java @@ -0,0 +1,42 @@ +package jnpf.ocr_sdk.utils.table; + +/** + * @Auther: xiaoqiang + * @Date: 2020/12/9 9:17 + * @Description: + */ +public class CrossRangeCellMeta { + public CrossRangeCellMeta(int firstRowIndex, int firstColIndex, int rowSpan, int colSpan) { + super(); + this.firstRowIndex = firstRowIndex; + this.firstColIndex = firstColIndex; + this.rowSpan = rowSpan; + this.colSpan = colSpan; + } + + private int firstRowIndex; + private int firstColIndex; + private int rowSpan;// 跨越行数 + private int colSpan;// 跨越列数 + + public int getFirstRow() { + return firstRowIndex; + } + + public int getLastRow() { + return firstRowIndex + rowSpan - 1; + } + + public int getFirstCol() { + return firstColIndex; + } + + public int getLastCol() { + return firstColIndex + colSpan - 1; + } + + public int getColSpan(){ + return colSpan; + } +} + diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableDetection.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableDetection.java new file mode 100644 index 00000000..a4270ed4 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableDetection.java @@ -0,0 +1,227 @@ +package jnpf.ocr_sdk.utils.table; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.repository.zoo.Criteria; +import ai.djl.training.util.ProgressBar; +import org.apache.commons.collections.CollectionUtils; +import org.apache.commons.lang3.StringUtils; +import org.apache.commons.lang3.tuple.Pair; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.*; +import java.util.concurrent.ConcurrentHashMap; + +public final class TableDetection { + + private static final Logger logger = LoggerFactory.getLogger(TableDetection.class); + + public TableDetection() {} + + public Criteria criteria() { + + Criteria criteria = + Criteria.builder() + .optEngine("PaddlePaddle") + .setTypes(Image.class, TableResult.class) + .optModelUrls( + "https://aias-home.oss-cn-beijing.aliyuncs.com/models/ocr_models/en_table.zip") + // .optModelUrls( + // "/Users/calvin/Documents/build/paddle_models/ppocr/en_ppocr_mobile_v2.0_table_structure_infer") + .optOption("removePass", "repeated_fc_relu_fuse_pass") + .optTranslator(new TableStructTranslator(new ConcurrentHashMap())) + .optProgress(new ProgressBar()) + .build(); + + return criteria; + } + + public List cellContents( + DetectedObjects textDetections, List cells, int width, int height) { + List dt_boxes = textDetections.items(); + + // 获取 Cell 与 文本检测框 的对应关系(1:N)。 + Map> matched = new ConcurrentHashMap<>(); + + for (int i = 0; i < dt_boxes.size(); i++) { + DetectedObjects.DetectedObject item = dt_boxes.get(i); + Rectangle textBounds = item.getBoundingBox().getBounds(); + int[] box_1 = rectXYXY(textBounds, width, height); + // 获取两两cell之间的L1距离和 1- IOU + List> distances = new ArrayList<>(); + for (BoundingBox cell : cells) { + Rectangle cellBounds = cell.getBounds(); + int[] box_2 = rectXYXY(cellBounds, width, height); + float distance = distance(box_1, box_2); + float iou = 1 - compute_iou(box_1, box_2); + distances.add(Pair.of(distance, iou)); + } + // 根据距离和IOU挑选最"近"的cell + Pair nearest = sorted(distances); + + // 获取最小距离对应的下标id，也等价于cell的下标id （distances列表是根据遍历cells生成的） + int id = 0; + for (int idx = 0; idx < distances.size(); idx++) { + Pair current = distances.get(idx); + if (current.getLeft().floatValue() == nearest.getLeft().floatValue() + && current.getRight().floatValue() == nearest.getRight().floatValue()) { + id = idx; + break; + } + } + if (!matched.containsKey(id)) { + List textIds = new ArrayList<>(); + textIds.add(i); + // cell id, text id list (dt_boxes index list) + matched.put(id, textIds); + } else { + matched.get(id).add(i); + } + } + + List cell_contents = new ArrayList<>(); + List probs = new ArrayList<>(); + for (int i = 0; i < cells.size(); i++) { + List textIds = matched.get(i); + List contents = new ArrayList<>(); + String content = ""; + if (textIds != null) { + for (Integer id : textIds) { + DetectedObjects.DetectedObject item = dt_boxes.get(id); + contents.add(item.getClassName()); + } + content = StringUtils.join(contents, " "); + } + + cell_contents.add(content); + probs.add(-1.0); + } + return cell_contents; + } + + /** + * Calculate L1 distance + * + * @param box_1 + * @param box_2 + * @return + */ + private int distance(int[] box_1, int[] box_2) { + int x1 = box_1[0]; + int y1 = box_1[1]; + int x2 = box_1[2]; + int y2 = box_1[3]; + int x3 = box_2[0]; + int y3 = box_2[1]; + int x4 = box_2[2]; + int y4 = box_2[3]; + int dis = Math.abs(x3 - x1) + Math.abs(y3 - y1) + Math.abs(x4 - x2) + Math.abs(y4 - y2); + int dis_2 = Math.abs(x3 - x1) + Math.abs(y3 - y1); + int dis_3 = Math.abs(x4 - x2) + Math.abs(y4 - y2); + return dis + Math.min(dis_2, dis_3); + } + + /** + * Get absolute coordinations + * + * @param rect + * @param width + * @param height + * @return + */ + private int[] rectXYXY(Rectangle rect, int width, int height) { + int left = Math.max((int) (width * rect.getX()), 0); + int top = Math.max((int) (height * rect.getY()), 0); + int right = Math.min((int) (width * (rect.getX() + rect.getWidth())), width - 1); + int bottom = Math.min((int) (height * (rect.getY() + rect.getHeight())), height - 1); + return new int[] {left, top, right, bottom}; + } + + /** + * computing IoU + * + * @param rec1: (y0, x0, y1, x1), which reflects (top, left, bottom, right) + * @param rec2: (y0, x0, y1, x1) + * @return scala value of IoU + */ + private float compute_iou(int[] rec1, int[] rec2) { + // computing area of each rectangles + int S_rec1 = (rec1[2] - rec1[0]) * (rec1[3] - rec1[1]); + int S_rec2 = (rec2[2] - rec2[0]) * (rec2[3] - rec2[1]); + + // computing the sum_area + int sum_area = S_rec1 + S_rec2; + + // find the each edge of intersect rectangle + int left_line = Math.max(rec1[1], rec2[1]); + int right_line = Math.min(rec1[3], rec2[3]); + int top_line = Math.max(rec1[0], rec2[0]); + int bottom_line = Math.min(rec1[2], rec2[2]); + + // judge if there is an intersect + if (left_line >= right_line || top_line >= bottom_line) { + return 0.0f; + } else { + float intersect = (right_line - left_line) * (bottom_line - top_line); + return (intersect / (sum_area - intersect)) * 1.0f; + } + } + + /** + * Distance sorted + * + * @param distances + * @return + */ + private Pair sorted(List> distances) { + Comparator> comparator = + new Comparator>() { + @Override + public int compare(Pair a1, Pair a2) { + // 首先根据IoU排序 + if (a1.getRight().floatValue() > a2.getRight().floatValue()) { + return 1; + } else if (a1.getRight().floatValue() == a2.getRight().floatValue()) { + // 然后根据L1距离排序 + if (a1.getLeft().floatValue() > a2.getLeft().floatValue()) { + return 1; + } + return -1; + } + return -1; + } + }; + + // 距离排序 + List> newDistances = new ArrayList<>(); + CollectionUtils.addAll(newDistances, new Object[distances.size()]); + Collections.copy(newDistances, distances); + Collections.sort(newDistances, comparator); + return newDistances.get(0); + } + + /** + * Generate table html + * + * @param pred_structures + * @param cell_contents + * @return + */ + public String get_pred_html(List pred_structures, List cell_contents) { + StringBuffer html = new StringBuffer(); + int td_index = 0; + for (String tag : pred_structures) { + if (tag.contains("")) { + String content = cell_contents.get(td_index); + html.append(content); + td_index++; + } + html.append(tag); + } + + return html.toString(); + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableResult.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableResult.java new file mode 100644 index 00000000..f6e84c2f --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableResult.java @@ -0,0 +1,31 @@ +package jnpf.ocr_sdk.utils.table; + +import ai.djl.modality.cv.output.BoundingBox; + +import java.util.List; + +public class TableResult { + private List structure_str_list; + private List boxes; + + public TableResult(List structure_str_list, List boxes) { + this.structure_str_list = structure_str_list; + this.boxes = boxes; + } + + public List getStructure_str_list() { + return structure_str_list; + } + + public void setStructure_str_list(List structure_str_list) { + this.structure_str_list = structure_str_list; + } + + public List getBoxes() { + return boxes; + } + + public void setBoxes(List boxes) { + this.boxes = boxes; + } +} diff --git a/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableStructTranslator.java b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableStructTranslator.java new file mode 100644 index 00000000..160c6642 --- /dev/null +++ b/SC-boot/linkage-scm/src/main/java/jnpf/ocr_sdk/utils/table/TableStructTranslator.java @@ -0,0 +1,246 @@ +package jnpf.ocr_sdk.utils.table; + +import ai.djl.Model; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.Rectangle; +import ai.djl.modality.cv.util.NDImageUtils; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDArrays; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.index.NDIndex; +import ai.djl.ndarray.types.DataType; +import ai.djl.ndarray.types.Shape; +import ai.djl.translate.Batchifier; +import ai.djl.translate.Translator; +import ai.djl.translate.TranslatorContext; +import ai.djl.util.Utils; +import org.apache.commons.lang3.StringUtils; + +import java.io.IOException; +import java.io.InputStream; +import java.nio.file.Files; +import java.nio.file.Path; +import java.nio.file.Paths; +import java.util.ArrayList; +import java.util.List; +import java.util.Map; +import java.util.concurrent.ConcurrentHashMap; + +public class TableStructTranslator implements Translator { + + private final int maxLength; + private int height; + private int width; + private float xScale = 1.0f; + private float yScale = 1.0f; + + public TableStructTranslator(Map arguments) { + maxLength = + arguments.containsKey("maxLength") + ? Integer.parseInt(arguments.get("maxLength").toString()) + : 488; + } + + private Map dict_idx_character = new ConcurrentHashMap<>(); + private Map dict_character_idx = new ConcurrentHashMap<>(); + private Map dict_idx_elem = new ConcurrentHashMap<>(); + private Map dict_elem_idx = new ConcurrentHashMap<>(); + private String beg_str = "sos"; + private String end_str = "eos"; + + @Override + public void prepare(TranslatorContext ctx) throws IOException { + Model model = ctx.getModel(); + // ppocr_keys_v1.txt + try (InputStream is = model.getArtifact("table_structure_dict.txt").openStream()) { + List lines = Utils.readLines(is, false); + String[] substr = lines.get(0).trim().split("\\t"); + int characterNum = Integer.parseInt(substr[0]); + int elemNum = Integer.parseInt(substr[1]); + + List listCharacter = new ArrayList<>(); + List listElem = new ArrayList<>(); + for (int i = 1; i < 1 + characterNum; i++) { + listCharacter.add(lines.get(i).trim()); + } + for (int i = 1 + characterNum; i < 1 + characterNum + elemNum; i++) { + listElem.add(lines.get(i).trim()); + } + listCharacter.add(0, beg_str); + listCharacter.add(end_str); + listElem.add(0, beg_str); + listElem.add(end_str); + + for (int i = 0; i < listCharacter.size(); i++) { + dict_idx_character.put("" + i, listCharacter.get(i)); + dict_character_idx.put(listCharacter.get(i), "" + i); + } + for (int i = 0; i < listElem.size(); i++) { + dict_idx_elem.put("" + i, listElem.get(i)); + dict_elem_idx.put(listElem.get(i), "" + i); + } + } + } + + @Override + public NDList processInput(TranslatorContext ctx, Image input) { + NDArray img = input.toNDArray(ctx.getNDManager(), Image.Flag.COLOR); + height = input.getHeight(); + width = input.getWidth(); + + // img = ResizeTableImage(img, height, width, maxLength); + // img = PaddingTableImage(ctx, img, maxLength); + + img = NDImageUtils.resize(img, 488, 488); + + // img = NDImageUtils.toTensor(img); + img = img.transpose(2, 0, 1).div(255).flip(0); + img = + NDImageUtils.normalize( + img, new float[] {0.485f, 0.456f, 0.406f}, new float[] {0.229f, 0.224f, 0.225f}); + + img = img.expandDims(0); + return new NDList(img); + } + + @Override + public TableResult processOutput(TranslatorContext ctx, NDList list) { + NDArray locPreds = list.get(0); + NDArray structureProbs = list.get(1); + NDArray structure_idx = structureProbs.argMax(2); + NDArray structure_probs = structureProbs.max(new int[] {2}); + + List> result_list = new ArrayList<>(); + List> result_pos_list = new ArrayList<>(); + List> result_score_list = new ArrayList<>(); + List> result_elem_idx_list = new ArrayList<>(); + List res_html_code_list = new ArrayList<>(); + List res_loc_list = new ArrayList<>(); + + // get ignored tokens + int beg_idx = Integer.parseInt(dict_elem_idx.get(beg_str)); + int end_idx = Integer.parseInt(dict_elem_idx.get(end_str)); + + long batch_size = structure_idx.size(0); // len(text_index) + for (int batch_idx = 0; batch_idx < batch_size; batch_idx++) { + List char_list = new ArrayList<>(); + List elem_pos_list = new ArrayList<>(); + List elem_idx_list = new ArrayList<>(); + List score_list = new ArrayList<>(); + + long len = structure_idx.get(batch_idx).size(); + for (int idx = 0; idx < len; idx++) { + int tmp_elem_idx = (int) structure_idx.get(batch_idx).get(idx).toLongArray()[0]; + if (idx > 0 && tmp_elem_idx == end_idx) { + break; + } + if (tmp_elem_idx == beg_idx || tmp_elem_idx == end_idx) { + continue; + } + + char_list.add(dict_idx_elem.get("" + tmp_elem_idx)); + elem_pos_list.add("" + idx); + score_list.add("" + structure_probs.get(batch_idx, idx).toFloatArray()[0]); + elem_idx_list.add("" + tmp_elem_idx); + } + + result_list.add(char_list); // structure_str + result_pos_list.add(elem_pos_list); + result_score_list.add(score_list); + result_elem_idx_list.add(elem_idx_list); + } + + int batch_num = result_list.size(); + for (int bno = 0; bno < batch_num; bno++) { + NDList res_loc = new NDList(); + int len = result_list.get(bno).size(); + for (int sno = 0; sno < len; sno++) { + String text = result_list.get(bno).get(sno); + if (text.equals("") || text.equals(" boxes = new ArrayList<>(); + + long rows = res_loc_list.get(0).size(0); + for (int rno = 0; rno < rows; rno++) { + float[] arr = res_loc_list.get(0).get(rno).toFloatArray(); + Rectangle rect = new Rectangle(arr[0], arr[1], (arr[2] - arr[0]), (arr[3] - arr[1])); + boxes.add(rect); + } + + List structure_str_list = result_list.get(0); + structure_str_list.add(0, ""); + structure_str_list.add(0, ""); + structure_str_list.add(0, ""); + structure_str_list.add("
"); + structure_str_list.add(""); + structure_str_list.add(""); + + TableResult result = new TableResult(structure_str_list, boxes); + + return result; + } + + @Override + public Batchifier getBatchifier() { + return null; + } + + private NDArray ResizeTableImage(NDArray img, int height, int width, int maxLen) { + int localMax = Math.max(height, width); + float ratio = maxLen * 1.0f / localMax; + int resize_h = (int) (height * ratio); + int resize_w = (int) (width * ratio); + if(width > height){ + xScale = 1.0f; + yScale = ratio; + } else{ + xScale = ratio; + yScale = 1.0f; + } + + img = NDImageUtils.resize(img, resize_w, resize_h); + return img; + } + + private NDArray PaddingTableImage(TranslatorContext ctx, NDArray img, int maxLen) { + + Image srcImg = ImageFactory.getInstance().fromNDArray(img.duplicate()); + saveImage(srcImg, "img.png", "build/output"); + + NDArray paddingImg = ctx.getNDManager().zeros(new Shape(maxLen, maxLen, 3), DataType.UINT8); + // NDManager manager = NDManager.newBaseManager(); + // NDArray paddingImg = manager.zeros(new Shape(maxLen, maxLen, 3), DataType.UINT8); + paddingImg.set( + new NDIndex("0:" + img.getShape().get(0) + ",0:" + img.getShape().get(1) + ",:"), img); + Image image = ImageFactory.getInstance().fromNDArray(paddingImg); + + saveImage(image, "paddingImg.png", "build/output"); + + return paddingImg; + } + + public void saveImage(Image img, String name, String path) { + Path outputDir = Paths.get(path); + Path imagePath = outputDir.resolve(name); + // OpenJDK 不能保存 jpg 图片的 alpha channel + try { + img.save(Files.newOutputStream(imagePath), "png"); + } catch (IOException e) { + e.printStackTrace(); + } + } +}