diff --git a/README.md b/README.md index dd26d60..176dde6 100644 --- a/README.md +++ b/README.md @@ -36,12 +36,13 @@
-

人脸检测

+

人脸检测

+ - 5点人脸关键点定位
- +
@@ -49,6 +50,7 @@

人脸比对1：1

+ - 人脸对齐
@@ -72,7 +74,8 @@
-

人脸比对1：N

+

人脸比对1：N

+ - 人脸对齐
- 人脸注册
- 人脸库查询
- 人脸库删除
@@ -100,6 +103,7 @@
+ ## 🚀 核心亮点 针对 Java 开发者在集成智能算法时常见的两大痛点： @@ -176,9 +180,9 @@ ```xml - ink.numberone + cn.smartjavaai smartjavaai-all - 1.0.10 + 1.0.11 ``` ### 3、完整示例代码 @@ -193,6 +197,7 @@ - **[Seetaface6JNI](https://gitee.com/cnsugar/seetaface6JNI)** - **[Deep Java Library](https://docs.djl.ai)** +- **[AIAS](https://gitee.com/mymagicpower/AIAS)** @@ -216,7 +221,12 @@ ## 更新日志 - +## [v1.0.11] - 2025-04-28 +- FaceNet 特征提取新增人脸对齐 +- 人脸检测新5点人脸关键点定位 +- 特征提取接口支持多人脸和最佳人脸提取 +- 修复人脸框边界精度问题 +- 更新 Maven 发布的 groupId ## [v1.0.10] - 2025-04-19 - 兼容 SeetaFace6 在 Linux 系统下的运行 - 新增全局缓存路径设置功能 diff --git a/pom.xml b/pom.xml index 25be50a..3bfd1e4 100644 --- a/pom.xml +++ b/pom.xml @@ -4,9 +4,9 @@ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> 4.0.0 - ink.numberone + cn.smartjavaai smartjavaai-parent - 1.0.10 + 1.0.11 pom SmartJavaAI @@ -14,6 +14,7 @@ smartjavaai-common smartjavaai-objectdetection smartjavaai-all + smartjavaai-ocr @@ -21,6 +22,7 @@ 11 UTF-8 0.32.0 + @@ -34,15 +36,15 @@ - ink.numberone + cn.smartjavaai smartjavaai-common - 1.0.10 + 1.0.11 - ink.numberone + cn.smartjavaai smartjavaai-face - 1.0.10 + 1.0.11 @@ -173,6 +175,12 @@ ai.djl.onnxruntime onnxruntime-engine + + + ai.djl.opencv + opencv + + ai.djl.ml.xgboost xgboost @@ -196,6 +204,12 @@ 5.8.16 + + gov.nist.math + jama + 1.0.3 + + diff --git a/smartjavaai-all/pom.xml b/smartjavaai-all/pom.xml index d21ec3f..80d86b8 100644 --- a/smartjavaai-all/pom.xml +++ b/smartjavaai-all/pom.xml @@ -4,13 +4,13 @@ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> 4.0.0 - ink.numberone + cn.smartjavaai smartjavaai-parent - 1.0.10 + 1.0.11 smartjavaai-all - 1.0.10 + 1.0.11 smartjavaai-all SmartJavaAI https://github.com/geekwenjie/SmartJavaAI @@ -23,13 +23,13 @@ - ink.numberone + cn.smartjavaai smartjavaai-face ${project.version} - ink.numberone + cn.smartjavaai smartjavaai-objectdetection ${project.version} diff --git a/smartjavaai-common/pom.xml b/smartjavaai-common/pom.xml index eb93c5e..0307960 100644 --- a/smartjavaai-common/pom.xml +++ b/smartjavaai-common/pom.xml @@ -4,9 +4,9 @@ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> 4.0.0 - ink.numberone + cn.smartjavaai smartjavaai-parent - 1.0.10 + 1.0.11 smartjavaai-common diff --git a/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/DetectionRectangle.java b/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/DetectionRectangle.java index 3a4b2e2..4842691 100644 --- a/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/DetectionRectangle.java +++ b/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/DetectionRectangle.java @@ -1,5 +1,7 @@ package cn.smartjavaai.common.entity; +import java.util.List; + /** * 检测结果-矩形区域 * @author dwj @@ -11,9 +13,13 @@ public class DetectionRectangle { public int width; public int height; public float score; - public String className; + /** + * 人脸关键点 + */ + private List keyPoints; + public DetectionRectangle() { } @@ -81,4 +87,12 @@ public class DetectionRectangle { public void setClassName(String className) { this.className = className; } + + public List getKeyPoints() { + return keyPoints; + } + + public void setKeyPoints(List keyPoints) { + this.keyPoints = keyPoints; + } } diff --git a/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/Point.java b/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/Point.java index e2f519d..00dfd7a 100644 --- a/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/Point.java +++ b/smartjavaai-common/src/main/java/cn/smartjavaai/common/entity/Point.java @@ -10,27 +10,27 @@ import java.io.Serializable; */ public class Point implements Serializable { private static final long serialVersionUID = 1L; - private int x; - private int y; + private double x; + private double y; - public Point(int x, int y) { + public Point(double x, double y) { this.x = x; this.y = y; } - public int getX() { + public double getX() { return x; } - public void setX(int x) { + public void setX(double x) { this.x = x; } - public int getY() { + public double getY() { return y; } - public void setY(int y) { + public void setY(double y) { this.y = y; } diff --git a/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/ImageUtils.java b/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/ImageUtils.java index a9e9d92..9e99255 100644 --- a/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/ImageUtils.java +++ b/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/ImageUtils.java @@ -1,13 +1,23 @@ package cn.smartjavaai.common.utils; +import ai.djl.modality.cv.BufferedImageFactory; +import ai.djl.modality.cv.Image; +import ai.djl.ndarray.NDArray; +import cn.smartjavaai.common.entity.DetectionRectangle; +import cn.smartjavaai.common.entity.DetectionResponse; + import javax.imageio.ImageIO; import java.awt.*; import java.awt.image.BufferedImage; //import java.awt.image.ColorConvertOp; import java.awt.image.ComponentSampleModel; +import java.awt.image.ImageObserver; import java.io.File; import java.io.IOException; +import java.util.ArrayList; import java.util.Arrays; +import java.util.List; +import java.util.Objects; /** * 图片处理工具类 @@ -88,6 +98,86 @@ public class ImageUtils { return image != null && image.getWidth() > 0 && image.getHeight() > 0; } + /** + * 画检测框 + * + * @param image + * @param x + * @param y + * @param width + * @param height + */ + 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 + * + * @param image + * @param x + * @param y + * @param width + * @param height + */ + public static void drawImageRect(Image image, int x, int y, int width, int height) { + // 将绘制图像转换为Graphics2D + BufferedImage bufferedImage = (BufferedImage)image.getWrappedImage(); + Graphics2D g = (Graphics2D) bufferedImage.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 + * + * @param image + * @param x + * @param y + * @param width + * @param height + */ + public static void drawImageRect(Image image, DetectionResponse detectionResponse) { + if(Objects.nonNull(detectionResponse) && Objects.nonNull(detectionResponse.getRectangleList()) && !detectionResponse.getRectangleList().isEmpty()){ + // 将绘制图像转换为Graphics2D' + BufferedImage bufferedImage = (BufferedImage)image.getWrappedImage(); + Graphics2D g = (Graphics2D) bufferedImage.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); + for(DetectionRectangle detectionRectangle : detectionResponse.getRectangleList()){ + g.drawRect(detectionRectangle.getX(), detectionRectangle.getY(), detectionRectangle.getWidth(), detectionRectangle.getHeight()); + } + } finally { + g.dispose(); + } + } + } + + + + + + diff --git a/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/OpenCVUtils.java b/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/OpenCVUtils.java new file mode 100644 index 0000000..96ee873 --- /dev/null +++ b/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/OpenCVUtils.java @@ -0,0 +1,119 @@ +package cn.smartjavaai.common.utils; + +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import org.opencv.core.CvType; +import org.opencv.core.Mat; +import org.opencv.core.Point; +import org.opencv.core.Scalar; +import org.opencv.imgproc.Imgproc; + +import java.awt.image.BufferedImage; +import java.awt.image.DataBufferByte; + +/** + * OpenCV 工具类 + */ +public class OpenCVUtils { + /** + * canny算法，边缘检测 + * + * @param src + * @return + */ + public static Mat canny(Mat src) { + Mat mat = src.clone(); + Imgproc.Canny(src, mat, 100, 200); + return mat; + } + + /** + * 画线 + * + * @param mat + * @param point1 + * @param point2 + */ + public static void line(Mat mat, Point point1, Point point2) { + Imgproc.line(mat, point1, point2, new Scalar(255, 255, 255), 1); + } + + /** + * NDArray to opencv_core.Mat + * + * @param manager + * @param srcPoints + * @param dstPoints + * @return + */ + public static Mat toOpenCVMat(NDManager manager, NDArray srcPoints, NDArray dstPoints) { + NDArray svdMat = SVDUtils.transformationFromPoints(manager, srcPoints, dstPoints); + double[] doubleArray = svdMat.toDoubleArray(); + Mat newSvdMat = new Mat(2, 3, CvType.CV_64F); + for (int i = 0; i < 2; i++) { + for (int j = 0; j < 3; j++) { + newSvdMat.put(i, j, doubleArray[i * 3 + j]); + } + } + return newSvdMat; + } + + /** + * double[][] points array to Mat + * @param points + * @return + */ + public static Mat toOpenCVMat(double[][] points) { + Mat mat = new Mat(5, 2, CvType.CV_64F); + for (int i = 0; i < 5; i++) { + for (int j = 0; j < 2; j++) { + mat.put(i, j, points[i * 5 + j]); + } + } + return mat; + } + + /** + * 变换矩阵的逆矩阵 + * + * @param src + * @return + */ + public static Mat invertAffineTransform(Mat src) { + Mat dst = src.clone(); + Imgproc.invertAffineTransform(src, dst); + return dst; + } + + /** + * Mat to BufferedImage + * + * @param mat + * @return + */ + public static BufferedImage mat2Image(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; + } + + /** + * BufferedImage to Mat + * + * @param img + * @return + */ + public static Mat image2Mat(BufferedImage img) { + int width = img.getWidth(); + int height = img.getHeight(); + byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData(); + Mat mat = new Mat(height, width, CvType.CV_8UC3); + mat.put(0, 0, data); + return mat; + } +} diff --git a/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/SVDUtils.java b/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/SVDUtils.java new file mode 100644 index 0000000..2f40321 --- /dev/null +++ b/smartjavaai-common/src/main/java/cn/smartjavaai/common/utils/SVDUtils.java @@ -0,0 +1,119 @@ +package cn.smartjavaai.common.utils; + +import Jama.Matrix; +import Jama.SingularValueDecomposition; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; + +/** + * 仿射变换处理工具 + */ +public class SVDUtils { + /** + * 计算仿射变换矩阵 + * Calculate affine transformation matrix + * + * @param manager + * @param points1 + * @param points2 + * @return + */ + public static NDArray transformationFromPoints( + NDManager manager, NDArray points1, NDArray points2) { + // 按列计算均值 + // Calculate column-wise mean + NDArray c1 = points1.mean(new int[]{0}); // axis=0 列操作 - axis=0 column operation + NDArray c2 = points2.mean(new int[]{0}); // axis=0 列操作 - axis=0 column operation + // 按列减去均值 + // Subtract column-wise mean + points1 = points1.sub(c1); + points2 = points2.sub(c2); + + // 计算全局标准差 + // Calculate global standard deviation + double s1 = std(points1); + double s2 = std(points2); + + // 矩阵除以全局标准差 + // Matrix divided by global standard deviation + NDArray djl_s1 = manager.create(s1); + NDArray djl_s2 = manager.create(s2); + points1 = points1.div(djl_s1); + points2 = points2.div(djl_s2); + + double[] points1D = points1.toDoubleArray(); + double[] points2D = points2.toDoubleArray(); + + // DJL 格式转换成Jamma格式 + // Convert DJL format to Jama format + double[][] m1 = new double[5][2]; + double[][] m2 = new double[5][2]; + for (int i = 0; i < 5; i++) { + for (int j = 0; j < 2; j++) { + m1[i][j] = points1D[i * 2 + j]; + } + } + for (int i = 0; i < 5; i++) { + for (int j = 0; j < 2; j++) { + m2[i][j] = points2D[i * 2 + j]; + } + } + Matrix p1 = new Matrix(m1); + Matrix p2 = new Matrix(m2); + + // 进行奇异值分解 + // Perform singular value decomposition + Matrix p3 = p1.transpose().times(p2); + SingularValueDecomposition s = p3.svd(); + + Matrix U = s.getU(); + Matrix S = s.getS(); + Matrix V = s.getV(); + // TODO 为什么第2列的符号是反的？ + // Why is the sign of the second column opposite? + m1 = U.getArray(); + m1[0][1] = -m1[0][1]; + m1[1][1] = -m1[1][1]; + m2 = V.getArray(); + m2[0][1] = -m2[0][1]; + m2[1][1] = -m2[1][1]; + + Matrix R = (U.times(V)).transpose(); + + double[][] rArray = R.getArray(); + NDArray newR = manager.create(rArray); + // np.vstack([np.hstack(((s2 / s1) * R, c2.T - (s2 / s1) * R * c1.T)), np.matrix([0.,0., 1.])]) + // (s2 / s1) * R + NDArray leftPart = djl_s2.div(djl_s1).mul(newR); + // c2.T - (s2 / s1) * R * c1.T) + NDArray rightPart = c2.reshape(2, 1).sub(leftPart.matMul(c1.reshape(2, 1))); + // numpy.hstack(((s2 / s1) * R, c2.T - (s2 / s1) * R * c1.T)) + NDArray upPart = leftPart.concat(rightPart, 1); + // np.matrix([0.,0., 1.]) + double[] downArray = {0d, 0d, 1d}; + NDArray downPart = manager.create(downArray).reshape(1, 3); + + NDArray all = upPart.concat(downPart, 0); + // System.out.println("all: " + all); + + return upPart; + } + + /** + * 计算全局标准差 + * Calculate global standard deviation + * + * @param points + * @return + */ + public static double std(NDArray points) { + points = points.square(); + double[] doubleResult = points.toDoubleArray(); + double std = 0; + for (int i = 0; i < doubleResult.length; i++) { + std = std + doubleResult[i]; + } + std = (float) Math.sqrt(std / doubleResult.length); + return std; + } +} diff --git a/smartjavaai-face/pom.xml b/smartjavaai-face/pom.xml index cd6eebb..8a9054e 100644 --- a/smartjavaai-face/pom.xml +++ b/smartjavaai-face/pom.xml @@ -4,13 +4,13 @@ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> 4.0.0 - ink.numberone + cn.smartjavaai smartjavaai-parent - 1.0.10 + 1.0.11 smartjavaai-face - 1.0.10 + 1.0.11 smartjavaai-face SmartJavaAI https://github.com/geekwenjie/SmartJavaAI @@ -31,7 +31,7 @@ - ink.numberone + cn.smartjavaai smartjavaai-common ${project.version} @@ -47,6 +47,7 @@ sqlite-jdbc 3.36.0.3 + diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/AbstractFaceModel.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/AbstractFaceModel.java index f4a5a8d..c7a7bd6 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/AbstractFaceModel.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/AbstractFaceModel.java @@ -5,6 +5,7 @@ import cn.smartjavaai.face.entity.FaceResult; import java.awt.image.BufferedImage; import java.io.InputStream; +import java.util.List; /** * 人脸识别算法 @@ -46,16 +47,6 @@ public abstract class AbstractFaceModel implements FaceModel { throw new UnsupportedOperationException("默认不支持该功能"); } - @Override - public float[] featureExtraction(String imagePath) { - throw new UnsupportedOperationException("默认不支持该功能"); - } - - @Override - public float[] featureExtraction(InputStream inputStream) { - throw new UnsupportedOperationException("默认不支持该功能"); - } - @Override public float calculSimilar(float[] feature1, float[] feature2) { throw new UnsupportedOperationException("默认不支持该功能"); @@ -111,15 +102,6 @@ public abstract class AbstractFaceModel implements FaceModel { throw new UnsupportedOperationException("默认不支持该功能"); } - @Override - public float[] featureExtraction(BufferedImage sourceImage) { - throw new UnsupportedOperationException("默认不支持该功能"); - } - - @Override - public float[] featureExtraction(byte[] imageData) { - throw new UnsupportedOperationException("默认不支持该功能"); - } @Override public float featureComparison(BufferedImage sourceImage1, BufferedImage sourceImag2) { @@ -140,4 +122,64 @@ public abstract class AbstractFaceModel implements FaceModel { public FaceResult search(byte[] imageData) { throw new UnsupportedOperationException("默认不支持该功能"); } + + @Override + public List extractFeatures(String imagePath) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public List extractFeatures(byte[] imageData) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public List extractFeatures(BufferedImage image) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public List extractFeatures(BufferedImage image, FaceExtractConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public List extractFeatures(String imagePath, FaceExtractConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public List extractFeatures(byte[] imageData, FaceExtractConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public float[] extractTopFaceFeature(BufferedImage image) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public float[] extractTopFaceFeature(String imagePath) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public float[] extractTopFaceFeature(byte[] imageData) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public float[] extractTopFaceFeature(BufferedImage image, FaceExtractConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public float[] extractTopFaceFeature(String imagePath, FaceExtractConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public float[] extractTopFaceFeature(byte[] imageData, FaceExtractConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } } diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceExtractConfig.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceExtractConfig.java new file mode 100644 index 0000000..d5f5d4d --- /dev/null +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceExtractConfig.java @@ -0,0 +1,38 @@ +package cn.smartjavaai.face; + +import lombok.Data; + +/** + * 人脸特征提取配置 + * @author dwj + * @date 2025/4/24 + */ +@Data +public class FaceExtractConfig { + + /** + * 是否裁剪人脸 + */ + private boolean cropFace = true; + + /** + * 是否对齐人脸 + */ + private boolean align = true; + + /** + * 人脸检测模型配置 + */ + private FaceModelConfig detectModelConfig; + + public FaceExtractConfig() { + } + + public FaceExtractConfig(boolean cropFace, boolean align, FaceModelConfig detectModelConfig) { + this.cropFace = cropFace; + this.align = align; + this.detectModelConfig = detectModelConfig; + } + + +} diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModel.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModel.java index bab6128..7fcad0a 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModel.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModel.java @@ -5,6 +5,7 @@ import cn.smartjavaai.face.entity.FaceResult; import java.awt.image.BufferedImage; import java.io.InputStream; +import java.util.List; /** * 人脸识别算法 @@ -61,34 +62,6 @@ public interface FaceModel { */ BufferedImage detectAndDraw(BufferedImage sourceImage); - /** - * 特征提取 - * @param imagePath 图片路径 - * @return - */ - float[] featureExtraction(String imagePath); - - /** - * 特征提取 - * @param inputStream 输入流 - * @return - */ - float[] featureExtraction(InputStream inputStream); - - /** - * 特征提取 - * @param sourceImage BufferedImage图片数据 - * @return - */ - float[] featureExtraction(BufferedImage sourceImage); - - /** - * 特征提取 - * @param imageData 图片字节流 - * @return - */ - float[] featureExtraction(byte[] imageData); - /** * 计算相似度 * @param feature1 图1特征 @@ -203,4 +176,94 @@ public interface FaceModel { */ long clearFace(); + /** + * 特征提取（使用默认配置） + * @param imagePath 图片路径 + * @return + */ + List extractFeatures(String imagePath); + + /** + * 特征提取（使用默认配置） + * @param imageData 图片字节流 + * @return + */ + List extractFeatures(byte[] imageData); + + /** + * 特征提取（使用默认配置） + * @param image BufferedImage + * @return + */ + List extractFeatures(BufferedImage image); + + /** + * 特征提取（使用自定义配置） + * 强制裁剪操作 + * @param image BufferedImage + * @param config + * @return + */ + List extractFeatures(BufferedImage image, FaceExtractConfig config); + + /** + * 特征提取（使用自定义配置） + * @param imagePath 图片路径 + * @param config + * @return + */ + List extractFeatures(String imagePath, FaceExtractConfig config); + + /** + * 特征提取（使用自定义配置） + * @param imageData 图片字节流 + * @param config + * @return + */ + List extractFeatures(byte[] imageData, FaceExtractConfig config); + + /** + * 提取分数最高人脸特征（使用默认配置） + * @param image BufferedImage + * @return + */ + float[] extractTopFaceFeature(BufferedImage image); + + /** + * 提取分数最高人脸特征（使用默认配置） + * @param imagePath 图片路径 + * @return + */ + float[] extractTopFaceFeature(String imagePath); + + /** + * 提取分数最高人脸特征（使用默认配置） + * @param imageData 图片字节流 + * @return + */ + float[] extractTopFaceFeature(byte[] imageData); + + /** + * 提取分数最高人脸特征（使用自定义配置） + * @param image BufferedImage + * @return + */ + float[] extractTopFaceFeature(BufferedImage image, FaceExtractConfig config); + + /** + * 提取分数最高人脸特征（使用自定义配置） + * @param imagePath 图片路径 + * @param config + * @return + */ + float[] extractTopFaceFeature(String imagePath, FaceExtractConfig config); + + /** + * 提取分数最高人脸特征（使用自定义配置） + * @param imageData 图片字节流 + * @param config + * @return + */ + float[] extractTopFaceFeature(byte[] imageData, FaceExtractConfig config); + } diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModelConfig.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModelConfig.java index 9372527..2186cc9 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModelConfig.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/FaceModelConfig.java @@ -50,6 +50,15 @@ public class FaceModelConfig { */ private int gpuId = 0; + public FaceModelConfig() { + } + public FaceModelConfig(FaceModelEnum modelEnum) { + this.modelEnum = modelEnum; + } + public FaceModelConfig(FaceModelEnum modelEnum, String modelPath) { + this.modelEnum = modelEnum; + this.modelPath = modelPath; + } } diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/factory/SeetaFace6Factory.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/factory/SeetaFace6Factory.java deleted file mode 100644 index 5d56f85..0000000 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/factory/SeetaFace6Factory.java +++ /dev/null @@ -1,34 +0,0 @@ -package cn.smartjavaai.face.factory; - -import ai.djl.inference.Predictor; -import ai.djl.repository.zoo.ZooModel; -import cn.smartjavaai.face.model.SeetaFace6Model; -import com.seetaface.SeetaFace6JNI; -import org.apache.commons.pool2.BasePooledObjectFactory; -import org.apache.commons.pool2.PooledObject; -import org.apache.commons.pool2.impl.DefaultPooledObject; - -/** - * Predictor 工厂类 - * @author dwj - * @date 2025/4/8 - */ -public class SeetaFace6Factory extends BasePooledObjectFactory { - - @Override - public SeetaFace6JNI create() { - return new SeetaFace6JNI(); - } - - @Override - public PooledObject wrap(SeetaFace6JNI obj) { - return new DefaultPooledObject<>(obj); - } - - @Override - public void destroyObject(PooledObject p) { - //p.getObject().dispose(); // 如果需要释放 native 资源 - SeetaFace6JNI object = p.getObject(); - object = null; - } -} diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/FeatureExtractionModel.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/FeatureExtractionModel.java index 7cb5f06..35ed281 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/FeatureExtractionModel.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/FeatureExtractionModel.java @@ -5,31 +5,41 @@ import ai.djl.MalformedModelException; import ai.djl.inference.Predictor; import ai.djl.modality.cv.Image; import ai.djl.modality.cv.ImageFactory; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import ai.djl.opencv.OpenCVImageFactory; import ai.djl.repository.zoo.Criteria; import ai.djl.repository.zoo.ModelNotFoundException; import ai.djl.repository.zoo.ZooModel; import ai.djl.training.util.ProgressBar; +import cn.smartjavaai.common.entity.DetectionRectangle; +import cn.smartjavaai.common.entity.DetectionResponse; import cn.smartjavaai.common.enums.DeviceEnum; import cn.smartjavaai.common.pool.PredictorFactory; import cn.smartjavaai.common.utils.FileUtils; import cn.smartjavaai.common.utils.ImageUtils; -import cn.smartjavaai.face.AbstractFaceModel; -import cn.smartjavaai.face.FaceModelConfig; +import cn.smartjavaai.face.*; import cn.smartjavaai.face.exception.FaceException; import cn.smartjavaai.face.translator.FaceFeatureTranslator; +import cn.smartjavaai.face.utils.FaceAlignUtils; +import cn.smartjavaai.face.utils.FaceUtils; +import cn.smartjavaai.face.utils.OpenCVUtils; import lombok.extern.slf4j.Slf4j; import org.apache.commons.lang3.StringUtils; import org.apache.commons.pool2.ObjectPool; import org.apache.commons.pool2.impl.GenericObjectPool; import org.apache.commons.pool2.impl.GenericObjectPoolConfig; +import org.opencv.core.Mat; import javax.imageio.ImageIO; import java.awt.image.BufferedImage; import java.io.ByteArrayInputStream; +import java.io.File; import java.io.IOException; import java.io.InputStream; import java.nio.file.Paths; import java.time.Duration; +import java.util.ArrayList; import java.util.Arrays; import java.util.List; import java.util.Objects; @@ -117,65 +127,6 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo } - /** - * 特征提取 - * @param imagePath 图片路径 - * @return - */ - @Override - public float[] featureExtraction(String imagePath) { - if(!FileUtils.isFileExists(imagePath)){ - throw new FaceException("图像文件不存在"); - } - Image img = null; - try { - img = ImageFactory.getInstance().fromFile(Paths.get(imagePath)); - } catch (IOException e) { - throw new FaceException("无效图片", e); - } - return featureExtraction(img); - } - - /** - * 特征提取 - * @param inputStream 输入流 - * @return - */ - @Override - public float[] featureExtraction(InputStream inputStream) { - if(Objects.isNull(inputStream)){ - throw new FaceException("图像输入流无效"); - } - Image img = null; - try { - img = ImageFactory.getInstance().fromInputStream(inputStream); - } catch (IOException e) { - throw new FaceException("无效图片输入流", e); - } - return featureExtraction(img); - } - - @Override - public float[] featureExtraction(BufferedImage sourceImage) { - if(!ImageUtils.isImageValid(sourceImage)){ - throw new FaceException("图像无效"); - } - Image img = ImageFactory.getInstance().fromImage(sourceImage); - return featureExtraction(img); - } - - @Override - public float[] featureExtraction(byte[] imageData) { - if(Objects.isNull(imageData)){ - throw new FaceException("图像无效"); - } - try { - return featureExtraction(ImageIO.read(new ByteArrayInputStream(imageData))); - } catch (IOException e) { - throw new FaceException("无效图片字节流", e); - } - } - /** * 计算相似度 * @param feature1 图1特征 @@ -207,34 +158,19 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo if(!FileUtils.isFileExists(imagePath1) || !FileUtils.isFileExists(imagePath2)){ throw new FaceException("图像文件不存在"); } - float[] feature1 = featureExtraction(imagePath1); - float[] feature2 = featureExtraction(imagePath2); + float[] feature1 = extractTopFaceFeature(imagePath1); + float[] feature2 = extractTopFaceFeature(imagePath2); return calculSimilar(feature1, feature2); } - /** - * 特征比较 - * @param inputStream1 图1输入流 - * @param inputStream2 图2输入流 - * @return - */ - @Override - public float featureComparison(InputStream inputStream1, InputStream inputStream2) { - if(Objects.isNull(inputStream1) || Objects.isNull(inputStream2)){ - throw new FaceException("图像输入流无效"); - } - float[] feature1 = featureExtraction(inputStream1); - float[] feature2 = featureExtraction(inputStream2); - return calculSimilar(feature1, feature2); - } @Override public float featureComparison(BufferedImage sourceImage1, BufferedImage sourceImag2) { if(!ImageUtils.isImageValid(sourceImage1) || !ImageUtils.isImageValid(sourceImag2)){ throw new FaceException("图像无效"); } - float[] feature1 = featureExtraction(sourceImage1); - float[] feature2 = featureExtraction(sourceImag2); + float[] feature1 = extractTopFaceFeature(sourceImage1); + float[] feature2 = extractTopFaceFeature(sourceImag2); return calculSimilar(feature1, feature2); } @@ -243,11 +179,203 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo if(Objects.isNull(imageData1) || Objects.isNull(imageData2)){ throw new FaceException("图像无效"); } - float[] feature1 = featureExtraction(imageData1); - float[] feature2 = featureExtraction(imageData2); + float[] feature1 = extractTopFaceFeature(imageData1); + float[] feature2 = extractTopFaceFeature(imageData2); return calculSimilar(feature1, feature2); } + /** + * 获取默认特征提取配置 + * @return + */ + private FaceExtractConfig getDefaultConfig() { + FaceExtractConfig config = new FaceExtractConfig(); + FaceModelConfig detectModelConfig = new FaceModelConfig(); + detectModelConfig.setModelEnum(FaceModelEnum.ULTRA_LIGHT_FAST_GENERIC_FACE); + config.setDetectModelConfig(detectModelConfig); + return config; + } + + @Override + public List extractFeatures(String imagePath) { + return extractFeatures(imagePath, getDefaultConfig()); + } + + @Override + public List extractFeatures(byte[] imageData) { + return extractFeatures(imageData, getDefaultConfig()); + } + + @Override + public List extractFeatures(BufferedImage image) { + return extractFeatures(image, getDefaultConfig()); + } + + + @Override + public List extractFeatures(BufferedImage image, FaceExtractConfig config) { + if(Objects.isNull(config)){ + throw new FaceException("config为null"); + } + List featureList = new ArrayList(); + if(Objects.isNull(config.getDetectModelConfig())){ + throw new FaceException("config.detectModelConfig为null"); + } + FaceModel faceModel = FaceModelFactory.getInstance().getModel(config.getDetectModelConfig()); + DetectionResponse detectedResult = faceModel.detect(image); + if(Objects.isNull(detectedResult) || Objects.isNull(detectedResult.getRectangleList()) || detectedResult.getRectangleList().isEmpty()){ + throw new FaceException("未检测到人脸"); + } + Image djlImage = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(image)); + NDManager manager = NDManager.newBaseManager(); + for (DetectionRectangle rectangle : detectedResult.getRectangleList()){ + float[] features = null; + //裁剪人脸 + Image subImage = djlImage.getSubImage(rectangle.getX(), rectangle.getY() , rectangle.getWidth() , rectangle.getHeight()); + //人脸对齐 + if(config.isAlign()){ + //获取子图中人脸关键点坐标 + double[][] pointsArray = FaceUtils.facePoints(rectangle.getKeyPoints()); + NDArray srcPoints = manager.create(pointsArray); + NDArray dstPoints = FaceUtils.faceTemplate512x512(manager); + // 5点仿射变换 + Mat affine_matrix = OpenCVUtils.toOpenCVMat(manager, srcPoints, dstPoints); + /*Mat sourceMat = OpenCVUtils.image2Mat(image); + Mat mat = FaceAlignUtils.warpAffine(sourceMat, affine_matrix); + //OpenCVUtils.mat2Image(mat); + Image alignedImg = ImageFactory.getInstance().fromImage(mat); + features = featureExtraction(alignedImg);*/ + Mat mat = FaceAlignUtils.warpAffine((Mat) djlImage.getWrappedImage(), affine_matrix); + Image alignedImg = OpenCVImageFactory.getInstance().fromImage(mat); + features = featureExtraction(alignedImg); + }else{ + //不对齐人脸 + features = featureExtraction(subImage); + } + if(Objects.nonNull(features)){ + featureList.add(features); + } + } + return featureList; + } + + @Override + public List extractFeatures(String imagePath, FaceExtractConfig config) { + if(!FileUtils.isFileExists(imagePath)){ + throw new FaceException("图像文件不存在"); + } + // 将图片路径转换为 BufferedImage + BufferedImage image = null; + try { + image = ImageIO.read(new File(Paths.get(imagePath).toAbsolutePath().toString())); + } catch (IOException e) { + throw new FaceException("无效图片路径", e); + } + return extractFeatures(image, config); + } + + @Override + public List extractFeatures(byte[] imageData, FaceExtractConfig config) { + if(Objects.isNull(imageData)){ + throw new FaceException("图像无效"); + } + try { + return extractFeatures(ImageIO.read(new ByteArrayInputStream(imageData)), config); + } catch (IOException e) { + throw new FaceException("错误的图像", e); + } + } + + @Override + public float[] extractTopFaceFeature(BufferedImage image) { + return extractTopFaceFeature(image, getDefaultConfig()); + } + + @Override + public float[] extractTopFaceFeature(String imagePath) { + return extractTopFaceFeature(imagePath, getDefaultConfig()); + } + + @Override + public float[] extractTopFaceFeature(byte[] imageData) { + return extractTopFaceFeature(imageData, getDefaultConfig()); + } + + @Override + public float[] extractTopFaceFeature(BufferedImage image, FaceExtractConfig config) { + if(Objects.isNull(config)){ + throw new FaceException("config为null"); + } + if(Objects.isNull(config.getDetectModelConfig())){ + throw new FaceException("config.detectModelConfig为null"); + } + Image djlImage = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(image)); + float[] features = null; + if(config.isCropFace()){ + FaceModel faceModel = FaceModelFactory.getInstance().getModel(config.getDetectModelConfig()); + DetectionResponse detectedResult = faceModel.detect(image); + if(Objects.isNull(detectedResult) || Objects.isNull(detectedResult.getRectangleList()) || detectedResult.getRectangleList().isEmpty()){ + throw new FaceException("未检测到人脸"); + } + //只取第一个人脸 + DetectionRectangle rectangle = detectedResult.getRectangleList().get(0); + //裁剪人脸 + Image subImage = djlImage.getSubImage(rectangle.getX(), rectangle.getY() , rectangle.getWidth() , rectangle.getHeight()); + //人脸对齐 + if(config.isAlign()){ + NDManager manager = NDManager.newBaseManager(); + //获取子图中人脸关键点坐标 + double[][] pointsArray = FaceUtils.facePoints(rectangle.getKeyPoints()); + NDArray srcPoints = manager.create(pointsArray); + NDArray dstPoints = FaceUtils.faceTemplate512x512(manager); + // 5点仿射变换 + Mat affine_matrix = OpenCVUtils.toOpenCVMat(manager, srcPoints, dstPoints); + /*Mat sourceMat = OpenCVUtils.image2Mat(image); + Mat mat = FaceAlignUtils.warpAffine(sourceMat, affine_matrix); + OpenCVUtils.mat2Image(mat); + Image alignedImg = ImageFactory.getInstance().fromImage(OpenCVUtils.mat2Image(mat)); + features = featureExtraction(alignedImg);*/ + Mat mat = FaceAlignUtils.warpAffine((Mat) djlImage.getWrappedImage(), affine_matrix); + Image alignedImg = OpenCVImageFactory.getInstance().fromImage(mat); + features = featureExtraction(alignedImg); + }else{ + //不对齐人脸 + features = featureExtraction(subImage); + } + }else{ + //不裁剪人脸直接提取特征 + features = featureExtraction(djlImage); + } + return features; + } + + @Override + public float[] extractTopFaceFeature(String imagePath, FaceExtractConfig config) { + if(!FileUtils.isFileExists(imagePath)){ + throw new FaceException("图像文件不存在"); + } + // 将图片路径转换为 BufferedImage + BufferedImage image = null; + try { + image = ImageIO.read(new File(Paths.get(imagePath).toAbsolutePath().toString())); + } catch (IOException e) { + throw new FaceException("无效图片路径", e); + } + return extractTopFaceFeature(image, config); + } + + @Override + public float[] extractTopFaceFeature(byte[] imageData, FaceExtractConfig config) { + if(Objects.isNull(imageData)){ + throw new FaceException("图像无效"); + } + try { + return extractTopFaceFeature(ImageIO.read(new ByteArrayInputStream(imageData)), config); + } catch (IOException e) { + throw new FaceException("错误的图像", e); + } + } + @Override public void close() { if (predictorPool != null) { @@ -255,4 +383,6 @@ public class FeatureExtractionModel extends AbstractFaceModel implements AutoClo } } + + } diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/RetinaFaceModel.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/RetinaFaceModel.java index 718e2b7..7afd83e 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/RetinaFaceModel.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/RetinaFaceModel.java @@ -19,6 +19,7 @@ import cn.smartjavaai.face.*; import cn.smartjavaai.face.exception.FaceException; import cn.smartjavaai.face.translator.FaceDetectionTranslator; import cn.smartjavaai.face.utils.FaceUtils; +import cn.smartjavaai.face.utils.OpenCVUtils; import lombok.extern.slf4j.Slf4j; import org.apache.commons.lang3.StringUtils; import org.apache.commons.pool2.ObjectPool; @@ -144,7 +145,7 @@ public class RetinaFaceModel extends AbstractFaceModel implements AutoCloseable{ if(!ImageUtils.isImageValid(image)){ throw new FaceException("图像无效"); } - Image img = ImageFactory.getInstance().fromImage(image); + Image img = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(image)); DetectedObjects detection = detect(img); return FaceUtils.convertToDetectionResponse(detection,img); } @@ -186,7 +187,7 @@ public class RetinaFaceModel extends AbstractFaceModel implements AutoCloseable{ if(!ImageUtils.isImageValid(sourceImage)){ throw new FaceException("图像无效"); } - Image img = ImageFactory.getInstance().fromImage(sourceImage); + Image img = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(sourceImage)); DetectedObjects detectedObjects = detect(img); if(Objects.isNull(detectedObjects) || detectedObjects.getNumberOfObjects() == 0){ throw new FaceException("未识别到人脸"); diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/SeetaFace6Model.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/SeetaFace6Model.java index 81bd42e..226ebfa 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/SeetaFace6Model.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/SeetaFace6Model.java @@ -1,29 +1,23 @@ package cn.smartjavaai.face.model; -import ai.djl.inference.Predictor; -import ai.djl.modality.cv.Image; -import ai.djl.modality.cv.output.DetectedObjects; -import cn.smartjavaai.common.config.Config; import cn.smartjavaai.common.entity.DetectionResponse; import cn.smartjavaai.common.enums.DeviceEnum; -import cn.smartjavaai.common.pool.PredictorFactory; import cn.smartjavaai.common.utils.FileUtils; import cn.smartjavaai.common.utils.ImageUtils; import cn.smartjavaai.face.AbstractFaceModel; +import cn.smartjavaai.face.FaceExtractConfig; import cn.smartjavaai.face.FaceModelConfig; import cn.smartjavaai.face.dao.FaceDao; import cn.smartjavaai.face.entity.FaceData; import cn.smartjavaai.face.entity.FaceResult; import cn.smartjavaai.face.exception.FaceException; +import cn.smartjavaai.face.utils.FaceAlignUtils; import cn.smartjavaai.face.utils.FaceUtils; import com.seeta.pool.*; import com.seeta.sdk.*; -import com.seetaface.NativeLoader; -import com.seetaface.SeetaFace6JNI; +import cn.smartjavaai.face.seetaface.NativeLoader; import lombok.extern.slf4j.Slf4j; import org.apache.commons.lang3.StringUtils; -import org.apache.commons.pool2.ObjectPool; -import org.apache.commons.pool2.impl.GenericObjectPool; import javax.imageio.ImageIO; import java.awt.image.BufferedImage; @@ -31,6 +25,7 @@ import java.io.*; import java.nio.file.Path; import java.nio.file.Paths; import java.sql.SQLException; +import java.util.ArrayList; import java.util.List; import java.util.Objects; @@ -154,10 +149,19 @@ public class SeetaFace6Model extends AbstractFaceModel { SeetaImageData imageData = new SeetaImageData(image.getWidth(), image.getHeight(), 3); imageData.data = ImageUtils.getMatrixBGR(image); FaceDetector predictor = null; + FaceLandmarker faceLandmarker = null; try { predictor = faceDetectorPool.borrowObject(); + faceLandmarker = faceLandmarkerPool.borrowObject(); SeetaRect[] seetaResult = predictor.Detect(imageData); - return FaceUtils.convertToDetectionResponse(seetaResult, config); + List seetaPointFSList = new ArrayList(); + for(SeetaRect seetaRect : seetaResult){ + //提取人脸的5点人脸标识 + SeetaPointF[] pointFS = new SeetaPointF[faceLandmarker.number()]; + faceLandmarker.mark(imageData, seetaRect, pointFS); + seetaPointFSList.add(pointFS); + } + return FaceUtils.convertToDetectionResponse(seetaResult, config, seetaPointFSList); } catch (Exception e) { throw new FaceException("目标检测错误", e); }finally { @@ -168,6 +172,13 @@ public class SeetaFace6Model extends AbstractFaceModel { log.warn("归还Predictor失败", e); } } + if (faceLandmarker != null) { + try { + faceLandmarkerPool.returnObject(faceLandmarker); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } } } @@ -295,104 +306,6 @@ public class SeetaFace6Model extends AbstractFaceModel { } } - @Override - public float[] featureExtraction(BufferedImage image) { - if(!ImageUtils.isImageValid(image)){ - throw new FaceException("图像无效"); - } - SeetaImageData imageData = new SeetaImageData(image.getWidth(), image.getHeight(), 3); - imageData.data = ImageUtils.getMatrixBGR(image); - FaceDetector faceDetector = null; - FaceLandmarker faceLandmarker = null; - FaceRecognizer faceRecognizer = null; - try { - faceDetector = faceDetectorPool.borrowObject(); - faceLandmarker = faceLandmarkerPool.borrowObject(); - faceRecognizer = faceRecognizerPool.borrowObject(); - //检测人脸 - SeetaRect[] seetaResult = faceDetector.Detect(imageData); - if(Objects.isNull(seetaResult) || seetaResult.length == 0){ - throw new FaceException("未检测到人脸"); - } - //提取第一个人脸的5点人脸标识 - SeetaPointF[] pointFS = new SeetaPointF[faceLandmarker.number()]; - faceLandmarker.mark(imageData, seetaResult[0], pointFS); - - //提取特征 - float[] features = new float[faceRecognizer.GetExtractFeatureSize()]; - boolean isSuccess = faceRecognizer.Extract(imageData, pointFS, features); - if(!isSuccess){ - throw new FaceException("人脸特征提取失败"); - } - return features; - } catch (FaceException e) { - throw e; - } catch (Exception e) { - throw new FaceException("目标检测错误", e); - }finally { - if (faceDetector != null) { - try { - faceDetectorPool.returnObject(faceDetector); //归还 - } catch (Exception e) { - log.warn("归还Predictor失败", e); - } - } - if (faceLandmarker != null) { - try { - faceLandmarkerPool.returnObject(faceLandmarker); //归还 - } catch (Exception e) { - log.warn("归还Predictor失败", e); - } - } - if (faceRecognizer != null) { - try { - faceRecognizerPool.returnObject(faceRecognizer); //归还 - } catch (Exception e) { - log.warn("归还Predictor失败", e); - } - } - } - } - - @Override - public float[] featureExtraction(String imagePath) { - if(!FileUtils.isFileExists(imagePath)){ - throw new FaceException("图像文件不存在"); - } - BufferedImage image = null; - try { - image = ImageIO.read(new File(Paths.get(imagePath).toAbsolutePath().toString())); - } catch (IOException e) { - throw new FaceException("无效图片路径", e); - } - return featureExtraction(image); - } - - @Override - public float[] featureExtraction(InputStream inputStream) { - if(Objects.isNull(inputStream)){ - throw new FaceException("图像输入流无效"); - } - BufferedImage image = null; - try { - image = ImageIO.read(inputStream); - } catch (IOException e) { - throw new FaceException("无效图片输入流", e); - } - return featureExtraction(image); - } - - @Override - public float[] featureExtraction(byte[] imageData) { - if(Objects.isNull(imageData)){ - throw new FaceException("图像无效"); - } - try { - return featureExtraction(ImageIO.read(new ByteArrayInputStream(imageData))); - } catch (IOException e) { - throw new FaceException("错误的图像", e); - } - } @Override public float calculSimilar(float[] feature1, float[] feature2) { @@ -897,4 +810,185 @@ public class SeetaFace6Model extends AbstractFaceModel { pageNo++; } } + + + @Override + public List extractFeatures(String imagePath) { + if(!FileUtils.isFileExists(imagePath)){ + throw new FaceException("图像文件不存在"); + } + // 将图片路径转换为 BufferedImage + BufferedImage image = null; + try { + image = ImageIO.read(new File(Paths.get(imagePath).toAbsolutePath().toString())); + } catch (IOException e) { + throw new FaceException("无效图片路径", e); + } + return extractFeatures(image); + } + + @Override + public List extractFeatures(byte[] imageData) { + if(Objects.isNull(imageData)){ + throw new FaceException("图像无效"); + } + try { + return extractFeatures(ImageIO.read(new ByteArrayInputStream(imageData))); + } catch (IOException e) { + throw new FaceException("错误的图像", e); + } + } + + @Override + public List extractFeatures(BufferedImage image) { + if(!ImageUtils.isImageValid(image)){ + throw new FaceException("图像无效"); + } + List featureList = new ArrayList(); + SeetaImageData imageData = new SeetaImageData(image.getWidth(), image.getHeight(), 3); + imageData.data = ImageUtils.getMatrixBGR(image); + FaceDetector faceDetector = null; + FaceLandmarker faceLandmarker = null; + FaceRecognizer faceRecognizer = null; + try { + faceDetector = faceDetectorPool.borrowObject(); + faceLandmarker = faceLandmarkerPool.borrowObject(); + faceRecognizer = faceRecognizerPool.borrowObject(); + //检测人脸 + SeetaRect[] seetaResult = faceDetector.Detect(imageData); + if(Objects.isNull(seetaResult) || seetaResult.length == 0){ + throw new FaceException("未检测到人脸"); + } + for(SeetaRect seetaRect : seetaResult){ + //提取人脸的5点人脸标识 + SeetaPointF[] pointFS = new SeetaPointF[faceLandmarker.number()]; + faceLandmarker.mark(imageData, seetaRect, pointFS); + //提取特征 + float[] features = new float[faceRecognizer.GetExtractFeatureSize()]; + //CropFaceV2 + ExtractCroppedFace 已包含裁剪+人脸对齐 + boolean isSuccess = faceRecognizer.Extract(imageData, pointFS, features); + if(!isSuccess){ + throw new FaceException("人脸特征提取失败"); + } + featureList.add(features); + } + } catch (FaceException e) { + throw e; + } catch (Exception e) { + throw new FaceException("目标检测错误", e); + }finally { + if (faceDetector != null) { + try { + faceDetectorPool.returnObject(faceDetector); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } + if (faceLandmarker != null) { + try { + faceLandmarkerPool.returnObject(faceLandmarker); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } + if (faceRecognizer != null) { + try { + faceRecognizerPool.returnObject(faceRecognizer); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } + } + return featureList; + } + + + @Override + public float[] extractTopFaceFeature(BufferedImage image) { + if(!ImageUtils.isImageValid(image)){ + throw new FaceException("图像无效"); + } + float[] features = null; + SeetaImageData imageData = new SeetaImageData(image.getWidth(), image.getHeight(), 3); + imageData.data = ImageUtils.getMatrixBGR(image); + FaceDetector faceDetector = null; + FaceLandmarker faceLandmarker = null; + FaceRecognizer faceRecognizer = null; + try { + faceDetector = faceDetectorPool.borrowObject(); + faceLandmarker = faceLandmarkerPool.borrowObject(); + faceRecognizer = faceRecognizerPool.borrowObject(); + //检测人脸 + SeetaRect[] seetaResult = faceDetector.Detect(imageData); + if(Objects.isNull(seetaResult) || seetaResult.length == 0){ + throw new FaceException("未检测到人脸"); + } + //提取人脸的5点人脸标识 + SeetaPointF[] pointFS = new SeetaPointF[faceLandmarker.number()]; + faceLandmarker.mark(imageData, seetaResult[0], pointFS); + //提取特征 + features = new float[faceRecognizer.GetExtractFeatureSize()]; + //CropFaceV2 + ExtractCroppedFace 已包含裁剪+人脸对齐 + boolean isSuccess = faceRecognizer.Extract(imageData, pointFS, features); + if(!isSuccess){ + throw new FaceException("人脸特征提取失败"); + } + } catch (FaceException e) { + throw e; + } catch (Exception e) { + throw new FaceException("目标检测错误", e); + }finally { + if (faceDetector != null) { + try { + faceDetectorPool.returnObject(faceDetector); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } + if (faceLandmarker != null) { + try { + faceLandmarkerPool.returnObject(faceLandmarker); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } + if (faceRecognizer != null) { + try { + faceRecognizerPool.returnObject(faceRecognizer); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + } + } + } + return features; + } + + @Override + public float[] extractTopFaceFeature(String imagePath) { + if(!FileUtils.isFileExists(imagePath)){ + throw new FaceException("图像文件不存在"); + } + // 将图片路径转换为 BufferedImage + BufferedImage image = null; + try { + image = ImageIO.read(new File(Paths.get(imagePath).toAbsolutePath().toString())); + } catch (IOException e) { + throw new FaceException("无效图片路径", e); + } + return extractTopFaceFeature(image); + } + + @Override + public float[] extractTopFaceFeature(byte[] imageData) { + if(Objects.isNull(imageData)){ + throw new FaceException("图像无效"); + } + try { + return extractTopFaceFeature(ImageIO.read(new ByteArrayInputStream(imageData))); + } catch (IOException e) { + throw new FaceException("错误的图像", e); + } + } + + } diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/UltraLightFastGenericFaceModel.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/UltraLightFastGenericFaceModel.java index 7bce773..52f9b9a 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/UltraLightFastGenericFaceModel.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/model/UltraLightFastGenericFaceModel.java @@ -19,6 +19,7 @@ import cn.smartjavaai.face.*; import cn.smartjavaai.face.exception.FaceException; import cn.smartjavaai.face.translator.FaceDetectionTranslator; import cn.smartjavaai.face.utils.FaceUtils; +import cn.smartjavaai.face.utils.OpenCVUtils; import lombok.extern.slf4j.Slf4j; import org.apache.commons.lang3.StringUtils; import org.apache.commons.pool2.ObjectPool; @@ -133,7 +134,7 @@ public class UltraLightFastGenericFaceModel extends AbstractFaceModel implements @Override public DetectionResponse detect(BufferedImage image) { - Image img = ImageFactory.getInstance().fromImage(image); + Image img = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(image)); DetectedObjects detection = detect(img); return FaceUtils.convertToDetectionResponse(detection,img); } @@ -175,7 +176,7 @@ public class UltraLightFastGenericFaceModel extends AbstractFaceModel implements if(!ImageUtils.isImageValid(sourceImage)){ throw new FaceException("图像无效"); } - Image img = ImageFactory.getInstance().fromImage(sourceImage); + Image img = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(sourceImage)); DetectedObjects detectedObjects = detect(img); if(Objects.isNull(detectedObjects) || detectedObjects.getNumberOfObjects() == 0){ throw new FaceException("未识别到人脸"); @@ -222,6 +223,9 @@ public class UltraLightFastGenericFaceModel extends AbstractFaceModel implements } + + + @Override public void close() { if (predictorPool != null) { diff --git a/smartjavaai-face/src/main/java/com/seetaface/NativeLoader.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/seetaface/NativeLoader.java similarity index 78% rename from smartjavaai-face/src/main/java/com/seetaface/NativeLoader.java rename to smartjavaai-face/src/main/java/cn/smartjavaai/face/seetaface/NativeLoader.java index a3c912b..e3b8640 100644 --- a/smartjavaai-face/src/main/java/com/seetaface/NativeLoader.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/seetaface/NativeLoader.java @@ -1,4 +1,4 @@ -package com.seetaface; +package cn.smartjavaai.face.seetaface; import cn.hutool.core.io.FileUtil; @@ -9,18 +9,11 @@ import cn.smartjavaai.common.config.Config; import cn.smartjavaai.common.enums.DeviceEnum; import cn.smartjavaai.face.FaceModelConfig; import cn.smartjavaai.face.exception.FaceException; -import com.seeta.sdk.SeetaDevice; import com.seeta.sdk.util.DllItem; import com.seeta.sdk.util.LoadNativeCore; -import jdk.dynalink.linker.support.Lookup; import lombok.extern.slf4j.Slf4j; -import org.apache.commons.lang3.StringUtils; import java.io.*; -import java.lang.invoke.MethodHandles; -import java.lang.invoke.VarHandle; -import java.lang.reflect.Field; -import java.lang.reflect.Method; import java.nio.file.Files; import java.nio.file.Path; import java.nio.file.Paths; @@ -37,18 +30,9 @@ public class NativeLoader { private static Path seetaface6NativePath; - private static final String[] WIN_LIBS = {"tennis.dll","tennis_haswell.dll","tennis_pentium.dll","tennis_sandy_bridge.dll","SeetaAuthorize.dll","SeetaFaceAntiSpoofingX600.dll","SeetaFaceDetector600.dll","SeetaFaceLandmarker600.dll","SeetaFaceRecognizer610.dll","SeetaFace6JNI.dll"}; - //private static final String[] WIN_LIBS = {"tennis","tennis_haswell","tennis_pentium","tennis_sandy_bridge","SeetaAuthorize","SeetaFaceAntiSpoofingX600","SeetaFaceDetector600","SeetaFaceLandmarker600","SeetaFaceRecognizer610","SeetaFace6JNI"}; - private static final String[] LINUX_CENTOS_LIBS = {"libSeetaAuthorize.so","libtennis.so","libtennis_haswell.so","libtennis_pentium.so","libtennis_sandy_bridge.so","libSeetaFaceDetector600.so","libSeetaAgePredictor600.so","libSeetaEyeStateDetector200.so","libSeetaFaceAntiSpoofingX600.so","libSeetaFaceLandmarker600.so","libSeetaFaceRecognizer610.so","libSeetaGenderPredictor600.so","libSeetaMaskDetector200.so","libSeetaPoseEstimation600.so","libSeetaFaceTracking600.so","libSeetaQualityAssessor300.so"}; - private static final String[] LINUX_UBUNTU_LIBS = {"libSeetaAuthorize.so","libtennis.so","libtennis_haswell.so","libtennis_pentium.so","libtennis_sandy_bridge.so","libSeetaFaceDetector600.so","libSeetaAgePredictor600.so","libSeetaEyeStateDetector200.so","libSeetaFaceAntiSpoofingX600.so","libSeetaFaceLandmarker600.so","libSeetaFaceRecognizer610.so","libSeetaGenderPredictor600.so","libSeetaMaskDetector200.so","libSeetaPoseEstimation600.so","libSeetaFaceTracking600.so","libSeetaQualityAssessor300.so"}; private static final String SEETAFACE_LIB_DIR = "seetaface6"; - public static SeetaFace6JNI seetaFace6SDK; - - public static final String AMD64 = "amd64"; - - public static final String x86_64 = "amd64"; /** * 定义dll 路径和加载顺序的文件 @@ -204,7 +188,7 @@ public class NativeLoader { */ private static File extractLibrary(String libPath) throws IOException { String resourcePath = libPath; - try (InputStream in = com.seetaface.NativeLoader.class.getResourceAsStream(resourcePath)) { + try (InputStream in = NativeLoader.class.getResourceAsStream(resourcePath)) { if (in == null) throw new FileNotFoundException(resourcePath); Path path = Paths.get(resourcePath); String fileName = path.getFileName().toString(); diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceAlignUtils.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceAlignUtils.java new file mode 100644 index 0000000..0809e11 --- /dev/null +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceAlignUtils.java @@ -0,0 +1,68 @@ +package cn.smartjavaai.face.utils; + +import ai.djl.modality.cv.Image; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import ai.djl.opencv.OpenCVImageFactory; +import cn.smartjavaai.common.utils.ImageUtils; +import com.seeta.sdk.SeetaImageData; +import com.seeta.sdk.SeetaPointF; +import org.opencv.core.Mat; +import org.opencv.core.Scalar; +import org.opencv.core.Size; +import org.opencv.imgproc.Imgproc; + +import java.awt.image.BufferedImage; + +/** + * 人脸对齐 + * @author Calvin + */ +public class FaceAlignUtils { + /** + * 根据目标点，进行旋转仿射变换 + * Perform rotation and affine transformation based on the target 5 points + * + * @param src + * @param rot_mat + * @return + */ + public static Mat warpAffine(Mat src, Mat rot_mat) { + Mat rot = new Mat(); + // 进行仿射变换，变换后大小为src的大小 + // Perform affine transformation, the size after transformation is the same as the size of src + Scalar scalar = new Scalar(135, 133, 132); + Size size = new Size(512, 512); + Imgproc.warpAffine(src, rot, rot_mat, size, 0, 0, scalar); + return rot; + } + public static Mat warpAffine(Mat src, Mat rot_mat, int width, int height) { + Mat rot = new Mat(); + Size size = new Size(width, height); + Imgproc.warpAffine(src, rot, rot_mat, size); + return rot; + } + + + public static Mat warpAffine(Mat src, Mat rot_mat, int width, int height, int flags) { + Mat rot = new Mat(); + Size size = new Size(width, height); + Imgproc.warpAffine(src, rot, rot_mat, size, flags); + return rot; + } + + public static SeetaImageData faceAlign(BufferedImage sourceImage, SeetaPointF[] pointFS) { + NDManager manager = NDManager.newBaseManager(); + //获取子图中人脸关键点坐标 + double[][] pointsArray = FaceUtils.facePoints(pointFS); + NDArray srcPoints = manager.create(pointsArray); + NDArray dstPoints = FaceUtils.faceTemplate512x512(manager); + // 5点仿射变换 + Mat affine_matrix = OpenCVUtils.toOpenCVMat(manager, srcPoints, dstPoints); + Mat mat = FaceAlignUtils.warpAffine(OpenCVUtils.image2Mat(sourceImage), affine_matrix); + BufferedImage alignImage = OpenCVUtils.mat2Image(mat); + SeetaImageData imageData = new SeetaImageData(alignImage.getWidth(), alignImage.getHeight(), 3); + imageData.data = ImageUtils.getMatrixBGR(alignImage); + return imageData; + } +} diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceUtils.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceUtils.java index 4f8c0c7..3982512 100644 --- a/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceUtils.java +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/FaceUtils.java @@ -3,12 +3,16 @@ package cn.smartjavaai.face.utils; import ai.djl.modality.cv.Image; import ai.djl.modality.cv.output.BoundingBox; import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; import cn.smartjavaai.common.entity.DetectionResponse; -import cn.smartjavaai.common.entity.Point; import cn.smartjavaai.common.entity.DetectionRectangle; +import cn.smartjavaai.common.entity.Point; import cn.smartjavaai.common.utils.ImageUtils; import cn.smartjavaai.face.FaceModelConfig; import cn.smartjavaai.face.exception.FaceException; +import com.seeta.sdk.SeetaImageData; +import com.seeta.sdk.SeetaPointF; import com.seeta.sdk.SeetaRect; import javax.imageio.ImageIO; @@ -16,10 +20,8 @@ import java.awt.*; import java.awt.image.BufferedImage; import java.io.File; import java.io.IOException; -import java.util.ArrayList; -import java.util.Iterator; +import java.util.*; import java.util.List; -import java.util.Objects; import java.util.stream.Collectors; /** @@ -49,11 +51,21 @@ public class FaceUtils { while(iterator.hasNext()) { DetectedObjects.DetectedObject result = (DetectedObjects.DetectedObject)iterator.next(); BoundingBox box = result.getBoundingBox(); - int x = (int)(box.getBounds().getX() * (double)img.getWidth()); - int y = (int)(box.getBounds().getY() * (double)img.getHeight()); - int width = (int)(box.getBounds().getWidth() * (double)img.getWidth()); - int height = (int)(box.getBounds().getHeight() * (double)img.getHeight()); + List keyPoints = new ArrayList(); + box.getBounds().getPath().forEach(point -> { + keyPoints.add(new Point(point.getX(), point.getY())); + }); + int x = (int)(box.getBounds().getX() * img.getWidth()); + int y = (int)(box.getBounds().getY() * img.getHeight()); + int width = (int)(box.getBounds().getWidth() * img.getWidth()); + int height = (int)(box.getBounds().getHeight() * img.getHeight()); + // 修正边界，防止越界 + if (x < 0) x = 0; + if (y < 0) y = 0; + if (x + width > img.getWidth()) width = img.getWidth() - x; + if (y + height > img.getHeight()) height = img.getHeight() - y; DetectionRectangle rectangle = new DetectionRectangle(x, y, width, height, detection.getProbabilities().get(index).floatValue()); + rectangle.setKeyPoints(keyPoints); rectangleList.add(rectangle); index++; } @@ -66,18 +78,24 @@ public class FaceUtils { * @param seetaResult * @return */ - public static DetectionResponse convertToDetectionResponse(SeetaRect[] seetaResult, FaceModelConfig config){ + public static DetectionResponse convertToDetectionResponse(SeetaRect[] seetaResult, FaceModelConfig config,List seetaPointFSList){ if(Objects.isNull(seetaResult) || seetaResult.length == 0){ return null; } DetectionResponse detectionResponse = new DetectionResponse(); List rectangleList = new ArrayList(); - for(SeetaRect rect : seetaResult){ + for(int i = 0; i < seetaResult.length; i++){ + SeetaRect rect = seetaResult[i]; + SeetaPointF[] seetaPointFS = seetaPointFSList.get(i); //过滤置信度 /*if(config.getConfidenceThreshold() > 0){ continue; }*/ DetectionRectangle rectangle = new DetectionRectangle(rect.x, rect.y, rect.width, rect.height, 0); + List keyPoints = Arrays.stream(seetaPointFS) + .map(p -> new Point(p.x, p.y)) + .collect(Collectors.toList()); + rectangle.setKeyPoints(keyPoints); rectangleList.add(rectangle); } detectionResponse.setRectangleList(rectangleList); @@ -108,6 +126,10 @@ public class FaceUtils { graphics.setColor(Color.RED);// 边框颜色 graphics.drawRect(rectangle.getX(), rectangle.getY(), rectangle.getWidth(), rectangle.getHeight()); drawText(graphics, "face", rectangle.getX(), rectangle.getY(), stroke, 4); + //绘制人脸关键点 + if(rectangle.getKeyPoints() != null){ + drawLandmarks(graphics, rectangle.getKeyPoints()); + } } graphics.dispose(); ImageIO.write(sourceImage, "jpg", new File(savePath)); @@ -136,6 +158,10 @@ public class FaceUtils { graphics.setColor(Color.RED);// 边框颜色 graphics.drawRect(rectangle.getX(), rectangle.getY(), rectangle.getWidth(), rectangle.getHeight()); drawText(graphics, "face", rectangle.getX(), rectangle.getY(), stroke, 4); + //绘制人脸关键点 + if(rectangle.getKeyPoints() != null){ + drawLandmarks(graphics, rectangle.getKeyPoints()); + } } graphics.dispose(); return sourceImage; @@ -163,5 +189,124 @@ public class FaceUtils { g.drawString(text, x + padding, y + ascent); } + /** + * 修正检测框 + * @param rectangle + * @param imageWidth + * @param imageHeight + * @return + */ + public static DetectionRectangle correctRect(DetectionRectangle rectangle, int imageWidth, int imageHeight) { + int x = rectangle.getX(); + int y = rectangle.getY(); + int width = rectangle.getWidth(); + int height = rectangle.getHeight(); + // 修正x, y防止越界 + if (x < 0) x = 0; + if (y < 0) y = 0; + // 宽高不能超出图片范围 + if (x + width > imageWidth) { + width = imageWidth - x; + } + if (y + height > imageHeight) { + height = imageHeight - y; + } + // 防止最终 width 或 height 为负或为 0 + if (width <= 0 || height <= 0) { + return null; // 无效区域 + } + return new DetectionRectangle(x, y, width, height, rectangle.score); + } + + /** + * 子图中人脸关键点坐标 - Coordinates of key points in the image + * + * @param points + * @return + */ + public static double[][] facePoints(List points) { + // 图中关键点坐标 - Coordinates of key points in the image + // 1. left_eye_x , left_eye_y + // 2. right_eye_x , right_eye_y + // 3. nose_x , nose_y + // 4. left_mouth_x , left_mouth_y + // 5. right_mouth_x , right_mouth_y + double[][] pointsArray = new double[5][2]; // 保存人脸关键点 - Save facial key points + int i = 0; + for (Point point : points) { + pointsArray[i][0] = point.getX(); + pointsArray[i][1] = point.getY(); + i++; + } + return pointsArray; + } + + /** + * 子图中人脸关键点坐标 - Coordinates of key points in the image + * + * @param pointFS + * @return + */ + public static double[][] facePoints(SeetaPointF[] pointFS) { + // 图中关键点坐标 - Coordinates of key points in the image + // 1. left_eye_x , left_eye_y + // 2. right_eye_x , right_eye_y + // 3. nose_x , nose_y + // 4. left_mouth_x , left_mouth_y + // 5. right_mouth_x , right_mouth_y + double[][] pointsArray = new double[5][2]; // 保存人脸关键点 - Save facial key points + int i = 0; + for (SeetaPointF point : pointFS) { + pointsArray[i][0] = point.getX(); + pointsArray[i][1] = point.getY(); + i++; + } + return pointsArray; + } + + /** + * 512x512的目标点 - Target point of 512x512 + * standard 5 landmarks for FFHQ faces with 512 x 512 + * + * @param manager + * @return + */ + public static NDArray faceTemplate512x512(NDManager manager) { + double[][] coord5point = { + {192.98138, 239.94708}, // 512x512的目标点 - Target point of 512x512 + {318.90277, 240.1936}, + {256.63416, 314.01935}, + {201.26117, 371.41043}, + {313.08905, 371.15118} + }; + NDArray points = manager.create(coord5point); + return points; + } + + /** + * bgr转图片 + * @return 图片 + */ + public static BufferedImage toBufferedImage(SeetaImageData seetaImageData) { + int type = BufferedImage.TYPE_3BYTE_BGR; + BufferedImage image = new BufferedImage(seetaImageData.width, seetaImageData.height, type); + image.getRaster().setDataElements(0, 0, seetaImageData.width, seetaImageData.height, seetaImageData.data); + return image; + } + + /** + * 绘制人脸关键点 + * @param g + * @param keyPoints + */ + private static void drawLandmarks(Graphics2D g, List keyPoints) { + g.setColor(new Color(246, 96, 0)); + BasicStroke bStroke = new BasicStroke(4.0F, 0, 0); + g.setStroke(bStroke); + for (Point point : keyPoints){ + g.drawRect((int)point.getX(), (int)point.getY(), 2, 2); + } + } + } diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/OpenCVUtils.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/OpenCVUtils.java new file mode 100644 index 0000000..1061ffe --- /dev/null +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/OpenCVUtils.java @@ -0,0 +1,119 @@ +package cn.smartjavaai.face.utils; + +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; +import org.opencv.core.CvType; +import org.opencv.core.Mat; +import org.opencv.core.Point; +import org.opencv.core.Scalar; +import org.opencv.imgproc.Imgproc; + +import java.awt.image.BufferedImage; +import java.awt.image.DataBufferByte; + +/** + * OpenCV 工具类 + */ +public class OpenCVUtils { + /** + * canny算法，边缘检测 + * + * @param src + * @return + */ + public static Mat canny(Mat src) { + Mat mat = src.clone(); + Imgproc.Canny(src, mat, 100, 200); + return mat; + } + + /** + * 画线 + * + * @param mat + * @param point1 + * @param point2 + */ + public static void line(Mat mat, Point point1, Point point2) { + Imgproc.line(mat, point1, point2, new Scalar(255, 255, 255), 1); + } + + /** + * NDArray to opencv_core.Mat + * + * @param manager + * @param srcPoints + * @param dstPoints + * @return + */ + public static Mat toOpenCVMat(NDManager manager, NDArray srcPoints, NDArray dstPoints) { + NDArray svdMat = SVDUtils.transformationFromPoints(manager, srcPoints, dstPoints); + double[] doubleArray = svdMat.toDoubleArray(); + Mat newSvdMat = new Mat(2, 3, CvType.CV_64F); + for (int i = 0; i < 2; i++) { + for (int j = 0; j < 3; j++) { + newSvdMat.put(i, j, doubleArray[i * 3 + j]); + } + } + return newSvdMat; + } + + /** + * double[][] points array to Mat + * @param points + * @return + */ + public static Mat toOpenCVMat(double[][] points) { + Mat mat = new Mat(5, 2, CvType.CV_64F); + for (int i = 0; i < 5; i++) { + for (int j = 0; j < 2; j++) { + mat.put(i, j, points[i * 5 + j]); + } + } + return mat; + } + + /** + * 变换矩阵的逆矩阵 + * + * @param src + * @return + */ + public static Mat invertAffineTransform(Mat src) { + Mat dst = src.clone(); + Imgproc.invertAffineTransform(src, dst); + return dst; + } + + /** + * Mat to BufferedImage + * + * @param mat + * @return + */ + public static BufferedImage mat2Image(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; + } + + /** + * BufferedImage to Mat + * + * @param img + * @return + */ + public static Mat image2Mat(BufferedImage img) { + int width = img.getWidth(); + int height = img.getHeight(); + byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData(); + Mat mat = new Mat(height, width, CvType.CV_8UC3); + mat.put(0, 0, data); + return mat; + } +} diff --git a/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/SVDUtils.java b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/SVDUtils.java new file mode 100644 index 0000000..6eeba75 --- /dev/null +++ b/smartjavaai-face/src/main/java/cn/smartjavaai/face/utils/SVDUtils.java @@ -0,0 +1,119 @@ +package cn.smartjavaai.face.utils; + +import Jama.Matrix; +import Jama.SingularValueDecomposition; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDManager; + +/** + * 仿射变换处理工具 + */ +public class SVDUtils { + /** + * 计算仿射变换矩阵 + * Calculate affine transformation matrix + * + * @param manager + * @param points1 + * @param points2 + * @return + */ + public static NDArray transformationFromPoints( + NDManager manager, NDArray points1, NDArray points2) { + // 按列计算均值 + // Calculate column-wise mean + NDArray c1 = points1.mean(new int[]{0}); // axis=0 列操作 - axis=0 column operation + NDArray c2 = points2.mean(new int[]{0}); // axis=0 列操作 - axis=0 column operation + // 按列减去均值 + // Subtract column-wise mean + points1 = points1.sub(c1); + points2 = points2.sub(c2); + + // 计算全局标准差 + // Calculate global standard deviation + double s1 = std(points1); + double s2 = std(points2); + + // 矩阵除以全局标准差 + // Matrix divided by global standard deviation + NDArray djl_s1 = manager.create(s1); + NDArray djl_s2 = manager.create(s2); + points1 = points1.div(djl_s1); + points2 = points2.div(djl_s2); + + double[] points1D = points1.toDoubleArray(); + double[] points2D = points2.toDoubleArray(); + + // DJL 格式转换成Jamma格式 + // Convert DJL format to Jama format + double[][] m1 = new double[5][2]; + double[][] m2 = new double[5][2]; + for (int i = 0; i < 5; i++) { + for (int j = 0; j < 2; j++) { + m1[i][j] = points1D[i * 2 + j]; + } + } + for (int i = 0; i < 5; i++) { + for (int j = 0; j < 2; j++) { + m2[i][j] = points2D[i * 2 + j]; + } + } + Matrix p1 = new Matrix(m1); + Matrix p2 = new Matrix(m2); + + // 进行奇异值分解 + // Perform singular value decomposition + Matrix p3 = p1.transpose().times(p2); + SingularValueDecomposition s = p3.svd(); + + Matrix U = s.getU(); + Matrix S = s.getS(); + Matrix V = s.getV(); + // TODO 为什么第2列的符号是反的？ + // Why is the sign of the second column opposite? + m1 = U.getArray(); + m1[0][1] = -m1[0][1]; + m1[1][1] = -m1[1][1]; + m2 = V.getArray(); + m2[0][1] = -m2[0][1]; + m2[1][1] = -m2[1][1]; + + Matrix R = (U.times(V)).transpose(); + + double[][] rArray = R.getArray(); + NDArray newR = manager.create(rArray); + // np.vstack([np.hstack(((s2 / s1) * R, c2.T - (s2 / s1) * R * c1.T)), np.matrix([0.,0., 1.])]) + // (s2 / s1) * R + NDArray leftPart = djl_s2.div(djl_s1).mul(newR); + // c2.T - (s2 / s1) * R * c1.T) + NDArray rightPart = c2.reshape(2, 1).sub(leftPart.matMul(c1.reshape(2, 1))); + // numpy.hstack(((s2 / s1) * R, c2.T - (s2 / s1) * R * c1.T)) + NDArray upPart = leftPart.concat(rightPart, 1); + // np.matrix([0.,0., 1.]) + double[] downArray = {0d, 0d, 1d}; + NDArray downPart = manager.create(downArray).reshape(1, 3); + + NDArray all = upPart.concat(downPart, 0); + // System.out.println("all: " + all); + + return upPart; + } + + /** + * 计算全局标准差 + * Calculate global standard deviation + * + * @param points + * @return + */ + public static double std(NDArray points) { + points = points.square(); + double[] doubleResult = points.toDoubleArray(); + double std = 0; + for (int i = 0; i < doubleResult.length; i++) { + std = std + doubleResult[i]; + } + std = (float) Math.sqrt(std / doubleResult.length); + return std; + } +} diff --git a/smartjavaai-face/src/main/java/com/seetaface/SeetaFace6JNI.java b/smartjavaai-face/src/main/java/com/seetaface/SeetaFace6JNI.java deleted file mode 100644 index 935eb93..0000000 --- a/smartjavaai-face/src/main/java/com/seetaface/SeetaFace6JNI.java +++ /dev/null @@ -1,135 +0,0 @@ -package com.seetaface; - - -import com.seetaface.model.RecognizeResult; -import com.seetaface.model.SeetaImageData; -import com.seetaface.model.SeetaPointF; -import com.seetaface.model.SeetaRect; - -/** - * seetaface6 sdk - * @author dwj - */ -public class SeetaFace6JNI { - - /** - * 初始化，指定人脸识别模型文件目录 - * - * @param modelDir - * @return - */ - - public native boolean initModel(String modelDir); - - /** - * 检测人脸 - * - * @param img - * @return - */ - public native SeetaRect[] detect(SeetaImageData img); - - /** - * 根据人脸检测关键点 - * 关键定定位输入的是原始图片和人脸检测结果，给出指定人脸上的关键点的依次坐标。 - * 这里检测到的5点坐标循序依次为，左眼中心、右眼中心、鼻尖、左嘴角和右嘴角。 - * 注意这里的左右是基于图片内容的左右，并不是图片中人的左右，即左眼中心就是图片中左边的眼睛的中心。 - * - * @param img - * @param faces - * @return - */ - public native SeetaPointF[] mark(SeetaImageData img, SeetaRect faces); - - /** - * 1 v 1 人脸比对 - * - * @param img1 - * @param img2 - * @return 相似度范围在0~1,返回负数表示出错 - */ - public native float compare(SeetaImageData img1, SeetaImageData img2); - - /** - * 提取人脸区域特性 - * @param face crop方法返回的人脸图像 - * @return - */ - public native float[] extractCroppedFace(byte[] face); - - /** - * 提取一个图像中最大人脸的特征 - * @param img - * @return - */ - public native float[] extractMaxFace(SeetaImageData img); - - /** - * 计算两个特性的相似度 - * @param features1 - * @param features2 - * @return - */ - public native float calculateSimilarity(float[] features1, float[] features2); - - /** - * 注册人脸 - * - * @param img - * @return The returned value is the index of face database. Reture -1 if failed - */ - public native long register(SeetaImageData img); - - /** - * 注册裁剪后的人脸，推荐使用该方法 - * @param bytes - * @return - */ - public native long registerCroppedFace(byte[] bytes); - - /** - * 从人脸库中搜索，返回相似度最高的索引 - * - * @param img - * @return index saves the index of face databese, which is same as the retured value by Register. similar saves the most similar. - */ - public native RecognizeResult query(SeetaImageData img); - - /** - * 用裁剪后的人脸进行搜索 - * @param bytes - * @return - */ - public native RecognizeResult queryByCroppedFace(byte[] bytes); - - /** - * 将人脸从数据库中删除 - * @param index -1: 删除所有 - * @return 返回删除记录数 - */ - public native long delete(long[] index); - - /** - * 人脸提取 - * - * @param img - * @return The returned value is face data. Reture null if failed - */ - public native byte[][] crop(SeetaImageData img); - - /** - * 图片活体检测 - * @param img - * @return - */ - public native int predictImage(SeetaImageData img); - - public native void dispose(); - - @Override - protected void finalize() throws Throwable { - super.finalize(); - this.dispose(); - } - -} diff --git a/smartjavaai-face/src/main/java/com/seetaface/model/RecognizeResult.java b/smartjavaai-face/src/main/java/com/seetaface/model/RecognizeResult.java deleted file mode 100644 index 09593d8..0000000 --- a/smartjavaai-face/src/main/java/com/seetaface/model/RecognizeResult.java +++ /dev/null @@ -1,10 +0,0 @@ -package com.seetaface.model; - - -/** - * 人脸识别结果 - */ -public class RecognizeResult { - public int index; - public float similar; -} diff --git a/smartjavaai-face/src/main/java/com/seetaface/model/SeetaImageData.java b/smartjavaai-face/src/main/java/com/seetaface/model/SeetaImageData.java deleted file mode 100644 index 8b59514..0000000 --- a/smartjavaai-face/src/main/java/com/seetaface/model/SeetaImageData.java +++ /dev/null @@ -1,27 +0,0 @@ -package com.seetaface.model; - -/** - * 人脸识别参数 - * @author dwj - */ -public class SeetaImageData { - public SeetaImageData() { - - } - - public SeetaImageData(int width, int height, int channels) { - this.data = new byte[width * height * channels]; - this.width = width; - this.height = height; - this.channels = channels; - } - - public SeetaImageData(int width, int height) { - this(width, height, 3); - } - - public byte[] data; - public int width; - public int height; - public int channels; -} diff --git a/smartjavaai-face/src/main/java/com/seetaface/model/SeetaPointF.java b/smartjavaai-face/src/main/java/com/seetaface/model/SeetaPointF.java deleted file mode 100644 index bf16153..0000000 --- a/smartjavaai-face/src/main/java/com/seetaface/model/SeetaPointF.java +++ /dev/null @@ -1,18 +0,0 @@ -package com.seetaface.model; - -/** - * SeetaPointF - * @author dwj - */ -public class SeetaPointF { - public double x; - public double y; - - @Override - public String toString() { - return "{" + - "x=" + x + - ", y=" + y + - '}'; - } -} diff --git a/smartjavaai-face/src/main/java/com/seetaface/model/SeetaRect.java b/smartjavaai-face/src/main/java/com/seetaface/model/SeetaRect.java deleted file mode 100644 index 7e994e3..0000000 --- a/smartjavaai-face/src/main/java/com/seetaface/model/SeetaRect.java +++ /dev/null @@ -1,24 +0,0 @@ -package com.seetaface.model; - -/** - * SeetaPointF - * @author dwj - */ -public class SeetaRect { - public int x; - public int y; - public int width; - public int height; - public float score; - - @Override - public String toString() { - return "SeetaRect{" + - "x=" + x + - ", y=" + y + - ", width=" + width + - ", height=" + height + - ", score=" + score + - '}'; - } -} diff --git a/smartjavaai-objectdetection/pom.xml b/smartjavaai-objectdetection/pom.xml index d160f31..a88bf39 100644 --- a/smartjavaai-objectdetection/pom.xml +++ b/smartjavaai-objectdetection/pom.xml @@ -4,13 +4,13 @@ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> 4.0.0 - ink.numberone + cn.smartjavaai smartjavaai-parent - 1.0.10 + 1.0.11 smartjavaai-objectdetection - 1.0.10 + 1.0.11 smartjavaai-objectdetection SmartJavaAI https://github.com/geekwenjie/SmartJavaAI @@ -31,7 +31,7 @@ - ink.numberone + cn.smartjavaai smartjavaai-common ${project.version} diff --git a/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/DetectorModelConfig.java b/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/DetectorModelConfig.java index c69d8c0..3d3a466 100644 --- a/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/DetectorModelConfig.java +++ b/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/DetectorModelConfig.java @@ -26,4 +26,16 @@ public class DetectorModelConfig { * 设备类型 */ private DeviceEnum device; + + public DetectorModelConfig() { + } + + public DetectorModelConfig(DetectorModelEnum modelEnum, DeviceEnum device) { + this.modelEnum = modelEnum; + this.device = device; + } + + public DetectorModelConfig(DetectorModelEnum modelEnum) { + this.modelEnum = modelEnum; + } } diff --git a/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/model/DetectorModel.java b/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/model/DetectorModel.java index e2172c1..133a57c 100644 --- a/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/model/DetectorModel.java +++ b/smartjavaai-objectdetection/src/main/java/cn/smartjavaai/objectdetection/model/DetectorModel.java @@ -7,6 +7,7 @@ import ai.djl.inference.Predictor; import ai.djl.modality.cv.Image; import ai.djl.modality.cv.ImageFactory; import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.opencv.OpenCVImageFactory; import ai.djl.repository.zoo.Criteria; import ai.djl.repository.zoo.ModelNotFoundException; import ai.djl.repository.zoo.ZooModel; @@ -18,6 +19,7 @@ import cn.smartjavaai.common.pool.ModelPredictorPoolManager; import cn.smartjavaai.common.pool.PredictorFactory; import cn.smartjavaai.common.utils.FileUtils; import cn.smartjavaai.common.utils.ImageUtils; +import cn.smartjavaai.common.utils.OpenCVUtils; import cn.smartjavaai.objectdetection.DetectorConfig; import cn.smartjavaai.objectdetection.DetectorModelConfig; import cn.smartjavaai.objectdetection.exception.DetectionException; @@ -145,7 +147,7 @@ public class DetectorModel implements AutoCloseable{ if(!ImageUtils.isImageValid(image)){ throw new DetectionException("图像无效"); } - Image img = ImageFactory.getInstance().fromImage(image); + Image img = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(image)); DetectedObjects detectedObjects = detect(img); return DetectorUtils.convertToDetectionResponse(detectedObjects, img); } @@ -159,7 +161,7 @@ public class DetectorModel implements AutoCloseable{ if(!ImageUtils.isImageValid(sourceImage)){ throw new DetectionException("图像无效"); } - Image img = ImageFactory.getInstance().fromImage(sourceImage); + Image img = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(sourceImage)); DetectedObjects detectedObjects = detect(img); img.drawBoundingBoxes(detectedObjects); try { diff --git a/smartjavaai-ocr/pom.xml b/smartjavaai-ocr/pom.xml new file mode 100644 index 0000000..5f116f1 --- /dev/null +++ b/smartjavaai-ocr/pom.xml @@ -0,0 +1,149 @@ + + + 4.0.0 + + cn.smartjavaai + smartjavaai-parent + 1.0.11 + + + smartjavaai-ocr + + + 11 + 11 + UTF-8 + 1.5.8 + 5.1.2-1.5.8 + + + + + cn.smartjavaai + smartjavaai-common + ${project.version} + + + org.bytedeco + javacpp + ${javacv.version} + + + org.bytedeco + ffmpeg + ${javacv.ffmpeg.version} + + + ai.djl.opencv + opencv + + + + 1.0.11 + smartjavaai-ocr + SmartJavaAI + https://github.com/geekwenjie/SmartJavaAI + + + MIT License + https://opensource.org/licenses/MIT + + + + + + + org.sonatype.central + central-publishing-maven-plugin + 0.4.0 + true + + dengwenjie + true + ${project.groupId}:${project.artifactId}:${project.version} + + + + + org.apache.maven.plugins + maven-source-plugin + 3.1.0 + + + attach-sources + + jar-no-fork + + + + + + org.apache.maven.plugins + maven-javadoc-plugin + 3.1.0 + + ${java.home}/bin/javadoc + none + + -Xdoclint:none + + + + + attach-javadocs + + jar + + + + + + org.apache.maven.plugins + maven-gpg-plugin + 3.1.0 + + + sign-artifacts + verify + + sign + + + + + + + + + + scm:git:git://github.com/geekwenjie/SmartJavaAI.git + scm:git:ssh://github.com/geekwenjie/SmartJavaAI.git + http://github.com/geekwenjie/SmartJavaAI/tree/master + + + + + + dengwenjie + https://s01.oss.sonatype.org/content/repositories/snapshots + + + dengwenjie + https://s01.oss.sonatype.org/service/local/staging/deploy/maven2/ + + + + + + dengwenjie + 775747758@qq.com + + Project Manager + Architect + + + + + diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/AbstractOcrModel.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/AbstractOcrModel.java new file mode 100644 index 0000000..13d59c7 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/AbstractOcrModel.java @@ -0,0 +1,24 @@ +package cn.smartjavaai.ocr; + +import cn.smartjavaai.common.entity.DetectionResponse; + +/** + * 人脸识别算法 + * @author dwj + */ +public abstract class AbstractOcrModel implements OcrModel { + @Override + public void loadModel(OcrModelConfig config) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public DetectionResponse detect(String imagePath) { + throw new UnsupportedOperationException("默认不支持该功能"); + } + + @Override + public void detectAndDraw(String imagePath, String outputPath) { + throw new UnsupportedOperationException("默认不支持该功能"); + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModel.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModel.java new file mode 100644 index 0000000..026d808 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModel.java @@ -0,0 +1,35 @@ +package cn.smartjavaai.ocr; + +import cn.smartjavaai.common.entity.DetectionResponse; + +import java.awt.image.BufferedImage; +import java.io.InputStream; + +/** + * 人脸识别算法 + * @author dwj + */ +public interface OcrModel { + + /** + * 加载模型 + * @param config + */ + void loadModel(OcrModelConfig config); // 加载模型 + + + /** + * 人脸检测 + * @param imagePath 图片路径 + * @return + */ + DetectionResponse detect(String imagePath); + + /** + * 检测并绘制结果 + * @param imagePath 图片输入路径（包含文件名称） + * @param outputPath 图片输出路径（包含文件名称） + */ + void detectAndDraw(String imagePath, String outputPath); + +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelConfig.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelConfig.java new file mode 100644 index 0000000..78150ea --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelConfig.java @@ -0,0 +1,28 @@ +package cn.smartjavaai.ocr; + +import cn.smartjavaai.common.enums.DeviceEnum; +import lombok.Data; + +/** + * @author dwj + * @date 2025/4/22 + */ +@Data +public class OcrModelConfig { + + /** + * 模型名称 + */ + private OcrModelEnum modelEnum; + + /** + * 设备类型 + */ + private DeviceEnum device; + + /** + * 模型路径 + */ + private String modelPath; + +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelEnum.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelEnum.java new file mode 100644 index 0000000..d81815c --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelEnum.java @@ -0,0 +1,27 @@ +package cn.smartjavaai.ocr; + +/** + * OCR模型枚举 + * @author dwj + * @date 2025/4/4 + */ +public enum OcrModelEnum { + + PADDLEOCR_V4_DET_MODEL; + + + /** + * 根据名称获取枚举 (忽略大小写和下划线变体) + */ + public static OcrModelEnum fromName(String name) { + String formatted = name.trim().toUpperCase().replaceAll("[-_]", ""); + for (OcrModelEnum model : values()) { + if (model.name().replaceAll("_", "").equals(formatted)) { + return model; + } + } + throw new IllegalArgumentException("未知模型名称: " + name); + } + + +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelFactory.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelFactory.java new file mode 100644 index 0000000..d718816 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/OcrModelFactory.java @@ -0,0 +1,95 @@ +package cn.smartjavaai.ocr; + +import cn.smartjavaai.common.config.Config; +import cn.smartjavaai.ocr.exception.OcrException; +import cn.smartjavaai.ocr.model.PaddleOCRV4DetectModel; +import lombok.extern.slf4j.Slf4j; + +import java.util.Map; +import java.util.Objects; +import java.util.concurrent.ConcurrentHashMap; + +/** + * 人脸算法工厂 + * @author dwj + */ +@Slf4j +public class OcrModelFactory { + + // 使用 volatile 和双重检查锁定来确保线程安全的单例模式 + private static volatile OcrModelFactory instance; + + private static final ConcurrentHashMap modelMap = new ConcurrentHashMap<>(); + + /** + * 算法注册表 + */ + private static final Map> registry = + new ConcurrentHashMap<>(); + + + public static OcrModelFactory getInstance() { + if (instance == null) { + synchronized (OcrModelFactory.class) { + if (instance == null) { + instance = new OcrModelFactory(); + } + } + } + return instance; + } + + + + /** + * 注册算法 + * @param name + * @param clazz + */ + private static void registerModel(String name, Class clazz) { + registry.put(name.toLowerCase(), clazz); + } + + + /** + * 获取模型（通过配置） + * @param config + * @return + */ + public OcrModel getModel(OcrModelConfig config) { + if(Objects.isNull(config) || Objects.isNull(config.getModelEnum())){ + throw new OcrException("未配置OCR模型"); + } + return modelMap.computeIfAbsent(config.getModelEnum().name(), k -> { + return createFaceModel(config); + }); + } + + /** + * 使用ModelConfig创建算法 + * @param config + * @return + */ + private OcrModel createFaceModel(OcrModelConfig config) { + Class clazz = registry.get(config.getModelEnum().name().toLowerCase()); + if(clazz == null){ + throw new OcrException("Unsupported model"); + } + OcrModel algorithm = null; + try { + algorithm = (OcrModel) clazz.newInstance(); + } catch (InstantiationException | IllegalAccessException e) { + throw new OcrException(e); + } + algorithm.loadModel(config); + return algorithm; + } + + + // 初始化默认算法 + static { + registerModel("PADDLEOCR_V4_DET_MODEL", PaddleOCRV4DetectModel.class); + log.info("缓存目录：{}", Config.getCachePath()); + } + +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/ImageInfo.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/ImageInfo.java new file mode 100644 index 0000000..6b753a1 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/ImageInfo.java @@ -0,0 +1,50 @@ +package cn.smartjavaai.ocr.entity; + +import ai.djl.modality.cv.Image; +import ai.djl.ndarray.NDArray; +/** + * 图像信息 + */ +public class ImageInfo { + private String name; + private Double prob; + private Image image; + private NDArray box; + + public ImageInfo(Image image, NDArray 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 NDArray getBox() { + return box; + } + + public void setBox(NDArray box) { + this.box = box; + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/RotatedBox.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/RotatedBox.java new file mode 100644 index 0000000..4e08603 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/RotatedBox.java @@ -0,0 +1,46 @@ +package cn.smartjavaai.ocr.entity; + +import ai.djl.ndarray.NDArray; +/** + * 旋转检测框 + */ +public class RotatedBox implements Comparable { + private NDArray box; + private String text; + + public RotatedBox(NDArray box, String text) { + this.box = box; + this.text = text; + } + + /** + * 将左上角 Y 坐标升序排序 + * + * @param o + * @return + */ + @Override + public int compareTo(RotatedBox o) { + NDArray lowBox = this.getBox(); + NDArray highBox = o.getBox(); + float lowY = lowBox.toFloatArray()[1]; + float highY = highBox.toFloatArray()[1]; + return (lowY < highY) ? -1 : 1; + } + + 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/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/RotatedBoxCompX.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/RotatedBoxCompX.java new file mode 100644 index 0000000..763f9cb --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/entity/RotatedBoxCompX.java @@ -0,0 +1,46 @@ +package cn.smartjavaai.ocr.entity; + +import ai.djl.ndarray.NDArray; +/** + * 旋转检测框 - 支持左上角 X 坐标升序排序 + */ +public class RotatedBoxCompX implements Comparable { + private NDArray box; + private String text; + + public RotatedBoxCompX(NDArray box, String text) { + this.box = box; + this.text = text; + } + + /** + * 将左上角 X 坐标升序排序 + * + * @param o + * @return + */ + @Override + public int compareTo(RotatedBoxCompX o) { + NDArray leftBox = this.getBox(); + NDArray rightBox = o.getBox(); + float leftX = leftBox.toFloatArray()[0]; + float rightX = rightBox.toFloatArray()[0]; + return (leftX < rightX) ? -1 : 1; + } + + 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/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/exception/OcrException.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/exception/OcrException.java new file mode 100644 index 0000000..c0f6b1c --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/exception/OcrException.java @@ -0,0 +1,30 @@ +package cn.smartjavaai.ocr.exception; + +/** + * 人脸检测异常 + * @author dwj + * @date 2025/4/4 + */ +public class OcrException extends RuntimeException{ + + public OcrException() { + super(); + } + + public OcrException(String message, Throwable cause, boolean enableSuppression, boolean writableStackTrace) { + super(message, cause, enableSuppression, writableStackTrace); + } + + public OcrException(String message, Throwable cause) { + super(message, cause); + } + + public OcrException(String message) { + super(message); + } + + public OcrException(Throwable cause) { + super(cause); + } + +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/model/PaddleOCRV4DetectModel.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/model/PaddleOCRV4DetectModel.java new file mode 100644 index 0000000..e796d77 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/model/PaddleOCRV4DetectModel.java @@ -0,0 +1,134 @@ +package cn.smartjavaai.ocr.model; + +import ai.djl.MalformedModelException; +import ai.djl.inference.Predictor; +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.NDManager; +import ai.djl.repository.zoo.Criteria; +import ai.djl.repository.zoo.ModelNotFoundException; +import ai.djl.repository.zoo.ModelZoo; +import ai.djl.repository.zoo.ZooModel; +import ai.djl.training.util.ProgressBar; +import ai.djl.translate.TranslateException; +import cn.smartjavaai.common.entity.DetectionResponse; +import cn.smartjavaai.common.pool.PredictorFactory; +import cn.smartjavaai.common.utils.FileUtils; +import cn.smartjavaai.ocr.AbstractOcrModel; +import cn.smartjavaai.ocr.OcrModelConfig; +import cn.smartjavaai.ocr.exception.OcrException; +import cn.smartjavaai.ocr.translator.PaddleOCRV4DetectionTranslator; +import cn.smartjavaai.ocr.utils.ImageUtils; +import cn.smartjavaai.ocr.utils.OcrUtils; +import lombok.extern.slf4j.Slf4j; +import org.apache.commons.lang3.StringUtils; +import org.apache.commons.pool2.ObjectPool; +import org.apache.commons.pool2.impl.GenericObjectPool; +import org.opencv.core.Mat; + +import java.io.IOException; +import java.nio.file.Files; +import java.nio.file.Path; +import java.nio.file.Paths; +import java.util.Objects; +import java.util.concurrent.ConcurrentHashMap; + +/** + * @author dwj + * @date 2025/4/21 + */ +@Slf4j +public class PaddleOCRV4DetectModel extends AbstractOcrModel { + + private ZooModel detectionModel; + + private ObjectPool> predictorPool; + + @Override + public void loadModel(OcrModelConfig config){ + if(StringUtils.isBlank(config.getModelPath())){ + throw new OcrException("modelPath is null"); + } + Criteria criteria = + Criteria.builder() + .optEngine("OnnxRuntime") + .setTypes(Image.class, NDList.class) + .optModelPath(Paths.get(config.getModelPath())) + .optTranslator(new PaddleOCRV4DetectionTranslator(new ConcurrentHashMap())) + .optProgress(new ProgressBar()) + .build(); + try{ + detectionModel = ModelZoo.loadModel(criteria); + // 创建池子：每个线程独享 Predictor + this.predictorPool = new GenericObjectPool<>(new PredictorFactory<>(detectionModel)); + log.info("当前设备: " + detectionModel.getNDManager().getDevice()); + } catch (IOException | ModelNotFoundException | MalformedModelException e) { + throw new OcrException("模型加载失败", e); + } + } + + @Override + public DetectionResponse detect(String imagePath){ + if(!FileUtils.isFileExists(imagePath)){ + throw new OcrException("图像文件不存在"); + } + Image img = null; + try { + img = ImageFactory.getInstance().fromFile(Paths.get(imagePath)); + } catch (IOException e) { + throw new OcrException("无效的图片", e); + } + return detect(img); + } + + /** + * 人脸检测 + * @param image + * @return + */ + private DetectionResponse detect(Image image){ + Predictor predictor = null; + try { + predictor = predictorPool.borrowObject(); + NDList result = predictor.predict(image); + return OcrUtils.convertToDetectionResponse(result, image); + } catch (Exception e) { + throw new OcrException("OCR检测错误", e); + }finally { + if (predictor != null) { + try { + predictorPool.returnObject(predictor); //归还 + } catch (Exception e) { + log.warn("归还Predictor失败", e); + try { + predictor.close(); // 归还失败才销毁 + } catch (Exception ex) { + log.error("关闭Predictor失败", ex); + } + } + } + } + } + + @Override + public void detectAndDraw(String imagePath, String outputPath) { + if(!FileUtils.isFileExists(imagePath)){ + throw new OcrException("图像文件不存在"); + } + try { + Image img = ImageFactory.getInstance().fromFile(Paths.get(imagePath)); + DetectionResponse detectionResponse = detect(img); + if(Objects.isNull(detectionResponse) || Objects.isNull(detectionResponse.getRectangleList()) || detectionResponse.getRectangleList().isEmpty()){ + throw new OcrException("未识别到文字"); + } + ImageUtils.drawRect((Mat)img.getWrappedImage(), detectionResponse); + Path output = Paths.get(outputPath); + log.info("Saving to {}", output.toAbsolutePath().toString()); + img.save(Files.newOutputStream(output), "png"); + } catch (IOException e) { + throw new OcrException(e); + } + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/model/PaddleOCRV4Model.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/model/PaddleOCRV4Model.java new file mode 100644 index 0000000..4d43c13 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/model/PaddleOCRV4Model.java @@ -0,0 +1,27 @@ +package cn.smartjavaai.ocr.model; + +import ai.djl.inference.Predictor; +import ai.djl.modality.cv.Image; +import ai.djl.ndarray.NDList; +import ai.djl.ndarray.NDManager; +import ai.djl.repository.zoo.Criteria; +import ai.djl.repository.zoo.ModelZoo; +import ai.djl.repository.zoo.ZooModel; +import ai.djl.training.util.ProgressBar; +import cn.smartjavaai.ocr.translator.PaddleOCRV4DetectionTranslator; +import org.opencv.core.Mat; + +import java.nio.file.Paths; +import java.util.concurrent.ConcurrentHashMap; + +/** + * @author dwj + * @date 2025/4/21 + */ +public class PaddleOCRV4Model { + + + public void loadModel(){ + + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrNDArrayUtils.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrNDArrayUtils.java new file mode 100644 index 0000000..0673f9d --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrNDArrayUtils.java @@ -0,0 +1,228 @@ +package cn.smartjavaai.ocr.opencv; + +import ai.djl.ndarray.NDArray; +import org.opencv.core.CvType; +import org.opencv.core.Mat; +import org.opencv.core.MatOfPoint; +import org.opencv.core.Point; + +import java.util.ArrayList; +import java.util.List; +/** + * NDArray Utils + * + */ +public class OcrNDArrayUtils { + /** + * Mat To MatOfPoint + * @param mat + * @return + */ + public static MatOfPoint matToMatOfPoint(Mat mat) { + int rows = mat.rows(); + MatOfPoint matOfPoint = new MatOfPoint(); + + List list = new ArrayList<>(); + for (int i = 0; i < rows; i++) { + Point point = new Point((float) mat.get(i, 0)[0], (float) mat.get(i, 1)[0]); + list.add(point); + } + matOfPoint.fromList(list); + + return matOfPoint; + } + + /** + * float NDArray To float[][] Array + * @param ndArray + * @return + */ + public static float[][] floatNDArrayToArray(NDArray ndArray) { + int rows = (int) (ndArray.getShape().get(0)); + int cols = (int) (ndArray.getShape().get(1)); + float[][] arr = new float[rows][cols]; + + float[] arrs = ndArray.toFloatArray(); + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + arr[i][j] = arrs[i * cols + j]; + } + } + return arr; + } + + /** + * Mat To double[][] Array + * @param mat + * @return + */ + public static double[][] matToDoubleArray(Mat mat) { + int rows = mat.rows(); + int cols = mat.cols(); + + double[][] doubles = new double[rows][cols]; + + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + doubles[i][j] = mat.get(i, j)[0]; + } + } + + return doubles; + } + + /** + * Mat To float[][] Array + * @param mat + * @return + */ + public static float[][] matToFloatArray(Mat mat) { + int rows = mat.rows(); + int cols = mat.cols(); + + float[][] floats = new float[rows][cols]; + + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + floats[i][j] = (float) mat.get(i, j)[0]; + } + } + + return floats; + } + + /** + * Mat To byte[][] Array + * @param mat + * @return + */ + public static byte[][] matToUint8Array(Mat mat) { + int rows = mat.rows(); + int cols = mat.cols(); + + byte[][] bytes = new byte[rows][cols]; + + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + bytes[i][j] = (byte) mat.get(i, j)[0]; + } + } + + return bytes; + } + + /** + * float NDArray To float[][] Array + * @param ndArray + * @param cvType + * @return + */ + public static Mat floatNDArrayToMat(NDArray ndArray, int cvType) { + int rows = (int) (ndArray.getShape().get(0)); + int cols = (int) (ndArray.getShape().get(1)); + Mat mat = new Mat(rows, cols, cvType); + + float[] arrs = ndArray.toFloatArray(); + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + mat.put(i, j, arrs[i * cols + j]); + } + } + return mat; + } + + /** + * float NDArray To Mat + * @param ndArray + * @return + */ + public static Mat floatNDArrayToMat(NDArray ndArray) { + int rows = (int) (ndArray.getShape().get(0)); + int cols = (int) (ndArray.getShape().get(1)); + Mat mat = new Mat(rows, cols, CvType.CV_32F); + + float[] arrs = ndArray.toFloatArray(); + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + mat.put(i, j, arrs[i * cols + j]); + } + } + + return mat; + + } + + /** + * uint8 NDArray To Mat + * @param ndArray + * @return + */ + public static Mat uint8NDArrayToMat(NDArray ndArray) { + int rows = (int) (ndArray.getShape().get(0)); + int cols = (int) (ndArray.getShape().get(1)); + Mat mat = new Mat(rows, cols, CvType.CV_8U); + + byte[] arrs = ndArray.toByteArray(); + + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + mat.put(i, j, arrs[i * cols + j]); + } + } + return mat; + } + + /** + * float[][] Array To Mat + * @param arr + * @return + */ + public static Mat floatArrayToMat(float[][] arr) { + int rows = arr.length; + int cols = arr[0].length; + Mat mat = new Mat(rows, cols, CvType.CV_32F); + + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + mat.put(i, j, arr[i][j]); + } + } + + return mat; + } + + /** + * byte[][] Array To Mat + * @param arr + * @return + */ + public static Mat uint8ArrayToMat(byte[][] arr) { + int rows = arr.length; + int cols = arr[0].length; + Mat mat = new Mat(rows, cols, CvType.CV_8U); + + for (int i = 0; i < rows; i++) { + for (int j = 0; j < cols; j++) { + mat.put(i, j, arr[i][j]); + } + } + + return mat; + } + + /** + * List To Mat + * @param points + * @return + */ + public static Mat toMat(List points) { + Mat mat = new Mat(points.size(), 2, CvType.CV_32F); + for (int i = 0; i < points.size(); i++) { + ai.djl.modality.cv.output.Point point = points.get(i); + mat.put(i, 0, (float) point.getX()); + mat.put(i, 1, (float) point.getY()); + } + + return mat; + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrOpenCVUtils.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrOpenCVUtils.java new file mode 100644 index 0000000..38af44e --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrOpenCVUtils.java @@ -0,0 +1,64 @@ +package cn.smartjavaai.ocr.opencv; + +import org.opencv.core.CvType; +import org.opencv.core.Mat; +import org.opencv.imgproc.Imgproc; + +import java.awt.image.BufferedImage; +import java.awt.image.DataBufferByte; + +/** + * OpenCV Utils + * + */ +public class OcrOpenCVUtils { + + /** + * 透视变换 + * + * @param src + * @param srcPoints + * @param dstPoints + * @return + */ + public static Mat perspectiveTransform(Mat src, Mat srcPoints, Mat dstPoints) { + Mat dst = src.clone(); + Mat warp_mat = Imgproc.getPerspectiveTransform(srcPoints, dstPoints); + Imgproc.warpPerspective(src, dst, warp_mat, dst.size()); + warp_mat.release(); + + return dst; + } + + /** + * Mat to BufferedImage + * + * @param mat + * @return + */ + public static BufferedImage mat2Image(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; + } + + /** + * BufferedImage to Mat + * + * @param img + * @return + */ + public static Mat image2Mat(BufferedImage img) { + int width = img.getWidth(); + int height = img.getHeight(); + byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData(); + Mat mat = new Mat(height, width, CvType.CV_8UC3); + mat.put(0, 0, data); + return mat; + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/translator/PaddleOCRV4DetectionTranslator.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/translator/PaddleOCRV4DetectionTranslator.java new file mode 100644 index 0000000..1de5242 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/translator/PaddleOCRV4DetectionTranslator.java @@ -0,0 +1,521 @@ +package cn.smartjavaai.ocr.translator; + +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 cn.smartjavaai.ocr.opencv.OcrNDArrayUtils; +import org.opencv.core.*; +import org.opencv.imgproc.Imgproc; + +import java.util.ArrayList; +import java.util.List; +import java.util.Map; + +/** + * 文字检测前后处理 + * + * @author Calvin + * @mail 179209347@qq.com + * @website www.aias.top + */ +public class PaddleOCRV4DetectionTranslator implements Translator { + // det_algorithm == "DB" + private final float thresh = 0.3f; + private final boolean use_dilation = false; + private final String score_mode = "fast"; + private final String box_type = "quad"; + + private final int limit_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 PaddleOCRV4DetectionTranslator(Map arguments) { + limit_side_len = + arguments.containsKey("limit_side_len") + ? Integer.parseInt(arguments.get("limit_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()) + : 0.6f; // 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.get(0); + pred = pred.squeeze(); + NDArray segmentation = pred.gt(thresh); // thresh=0.3 .mul(255f) + + segmentation = segmentation.toType(DataType.UINT8, true); + Shape shape = segmentation.getShape(); + int rows = (int) shape.get(0); + int cols = (int) shape.get(1); + + Mat newMask = new Mat(); + if (this.use_dilation) { + Mat mask = new Mat(); + //convert from NDArray to Mat + Mat srcMat = OcrNDArrayUtils.uint8NDArrayToMat(segmentation); + // size 越小，腐蚀的单位越小，图片越接近原图 + // Mat dilation_kernel = Imgproc.getStructuringElement(Imgproc.MORPH_RECT, new Size(2, 2)); + Mat dilation_kernel = OcrNDArrayUtils.uint8ArrayToMat(new byte[][]{{1, 1}, {1, 1}}); + /** + * 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。 + */ + Imgproc.dilate(srcMat, mask, dilation_kernel); + //destination Matrix + Scalar scalar = new Scalar(255); + Core.multiply(mask, scalar, newMask); + // release Mat + mask.release(); + srcMat.release(); + dilation_kernel.release(); + } else { + Mat srcMat = OcrNDArrayUtils.uint8NDArrayToMat(segmentation); + //destination Matrix + Scalar scalar = new Scalar(255); + Core.multiply(srcMat, scalar, newMask); + // release Mat + srcMat.release(); + } + + NDArray boxes = boxes_from_bitmap(manager, pred, newMask); + + //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 + newMask.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 bitmap new 'pred' after threshold filtering. + */ + private NDArray boxes_from_bitmap(NDManager manager, NDArray pred, Mat bitmap) { + int dest_height = (int) pred.getShape().get(0); + int dest_width = (int) pred.getShape().get(1); + int height = bitmap.rows(); + int width = bitmap.cols(); + + List contours = new ArrayList<>(); + Mat hierarchy = new Mat(); + // 寻找轮廓 + Imgproc.findContours( + bitmap, + contours, + hierarchy, + Imgproc.RETR_LIST, + Imgproc.CHAIN_APPROX_SIMPLE); + + int num_contours = Math.min(contours.size(), max_candidates); + NDList boxList = new NDList(); + float[] scores = new float[num_contours]; + + for (int index = 0; index < num_contours; index++) { + MatOfPoint contour = contours.get(index); + MatOfPoint2f newContour = new MatOfPoint2f(contour.toArray()); + float[][] pointsArr = new float[4][2]; + int sside = get_mini_boxes(newContour, 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); + + boxList.add(box); + scores[index] = score; + + // release memory + contour.release(); + newContour.release(); + } + + NDArray boxes = NDArrays.stack(boxList); + + // release + hierarchy.release(); + + 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(MatOfPoint2f 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 = Imgproc.minAreaRect(contour); + Mat points = new Mat(); + Imgproc.boxPoints(rect, points); + + float[][] fourPoints = new float[4][2]; + for (int row = 0; row < 4; row++) { + fourPoints[row][0] = (float) points.get(row, 0)[0]; + fourPoints[row][1] = (float) points.get(row, 1)[0]; + } + + 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(); + + 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 + Mat maskMat = OcrNDArrayUtils.uint8NDArrayToMat(mask); + + //mask - convert from NDArray to Mat - 4 rows, 2 cols + Mat boxMat = OcrNDArrayUtils.floatNDArrayToMat(box, CvType.CV_32S); + +// boxMat.reshape(1, new int[]{1, 4, 2}); + List pts = new ArrayList<>(); + MatOfPoint matOfPoint = OcrNDArrayUtils.matToMatOfPoint(boxMat); // new MatOfPoint(boxMat); + pts.add(matOfPoint); + Imgproc.fillPoly(maskMat, pts, new Scalar(1)); + + + NDArray subBitMap = bitmap.get(ymin + ":" + (ymax + 1) + "," + xmin + ":" + (xmax + 1)); + Mat bitMapMat = OcrNDArrayUtils.floatNDArrayToMat(subBitMap); + + Scalar score = Core.mean(bitMapMat, maskMat); + float scoreValue = (float) score.val[0]; + // release + maskMat.release(); + boxMat.release(); + bitMapMat.release(); + + return scoreValue; + } + + @Override + public NDList processInput(TranslatorContext ctx, Image input) { + NDArray img = input.toNDArray(ctx.getNDManager()); + int h = input.getHeight(); + int w = input.getWidth(); + img_height = h; + img_width = w; + + // limit the max side + float ratio = 1.0f; + if (Math.max(h, w) > limit_side_len) { + if (h > w) { + ratio = (float) limit_side_len / (float) h; + } else { + ratio = (float) limit_side_len / (float) w; + } + } + + int resize_h = (int) (h * ratio); + int resize_w = (int) (w * ratio); + + resize_h = Math.round((float) resize_h / 32f) * 32; + resize_w = Math.round((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/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/translator/PaddleOCRV4WordRecTranslator.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/translator/PaddleOCRV4WordRecTranslator.java new file mode 100644 index 0000000..7642e7c --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/translator/PaddleOCRV4WordRecTranslator.java @@ -0,0 +1,123 @@ +package cn.smartjavaai.ocr.translator; + +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; + +/** + * 文字识别前后处理 + * + */ +public class PaddleOCRV4WordRecTranslator implements Translator { + private List table; + private final boolean use_space_char; + + public PaddleOCRV4WordRecTranslator(Map arguments) { + use_space_char = + arguments.containsKey("use_space_char") + ? Boolean.parseBoolean(arguments.get("use_space_char").toString()) + : true; + } + + @Override + public void prepare(TranslatorContext ctx) throws IOException { + Model model = ctx.getModel(); + try (InputStream is = model.getArtifact("dict.txt").openStream()) { + table = Utils.readLines(is, true); + table.add(0, "blank"); + if(use_space_char){ + table.add(" "); + table.add(" "); + } + else{ + table.add(""); + 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; + + float max_wh_ratio = (float) imgW / (float) imgH; + + int h = input.getHeight(); + int w = input.getWidth(); + float wh_ratio = (float) w / (float) h; + + max_wh_ratio = Math.max(max_wh_ratio,wh_ratio); + imgW = (int)(imgH * max_wh_ratio); + + int resized_w; + if (Math.ceil(imgH * wh_ratio) > imgW) { + resized_w = imgW; + } else { + resized_w = (int) (Math.ceil(imgH * wh_ratio)); + } + NDArray resized_image = NDImageUtils.resize(img, resized_w, imgH); + resized_image = resized_image.transpose(2, 0, 1).toType(DataType.FLOAT32,false); + resized_image.divi(255f).subi(0.5f).divi(0.5f); + NDArray padding_im = ctx.getNDManager().zeros(new Shape(imgC, imgH, imgW), DataType.FLOAT32); + padding_im.set(new NDIndex(":,:,0:" + resized_w), resized_image); + + padding_im = padding_im.flip(0); + padding_im = padding_im.expandDims(0); + return new NDList(padding_im); + } + + @Override + public Batchifier getBatchifier() { + return null; + } + +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/utils/ImageUtils.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/utils/ImageUtils.java new file mode 100644 index 0000000..a05db62 --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/utils/ImageUtils.java @@ -0,0 +1,219 @@ +package cn.smartjavaai.ocr.utils; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.ImageFactory; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.ndarray.NDArray; +import cn.smartjavaai.common.entity.DetectionRectangle; +import cn.smartjavaai.common.entity.DetectionResponse; +import cn.smartjavaai.common.utils.OpenCVUtils; +import org.opencv.core.Mat; +import org.opencv.core.Point; +import org.opencv.core.Scalar; +import org.opencv.imgproc.Imgproc; + +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; +import java.util.ArrayList; +import java.util.List; + +/** + * 图像工具类 + */ +public class ImageUtils { + + + /** + * 保存BufferedImage图片 + * + * @param img + * @param name + * @param path + */ + public static void saveImage(BufferedImage img, String name, String path) { + Image djlImg = ImageFactory.getInstance().fromImage(OpenCVUtils.image2Mat(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 + * + * @param img + * @param name + * @param path + */ + 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 + * + * @param img + * @param detection + * @param name + * @param path + * @throws IOException + */ + 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"); + } + + + + + /** + * 画检测框(有倾斜角) + * + * @param image + * @param box + */ + 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 + * + * @param image + * @param box + * @param text + */ + 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 + * + * @param image + * @param x + * @param y + * @param width + * @param height + */ + 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(); + } + } + + /** + * 显示文字 + * + * @param image + * @param text + * @param x + * @param y + */ + 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(); + } + } + + /** + * 画矩形 + * + * @param mat + * @param box + */ + public static void drawRect(Mat mat, DetectionResponse detectionResponse) { + + for(DetectionRectangle detectionRectangle : detectionResponse.getRectangleList()){ + // 左上角点 + Point topLeft = new Point(detectionRectangle.getX(), detectionRectangle.getY()); + // 右下角点 + Point bottomRight = new Point(detectionRectangle.getX() + detectionRectangle.getWidth(), detectionRectangle.getY() + detectionRectangle.getHeight()); + // 绘制矩形（图像、左上角、右下角、颜色（BGR）、线宽） + Imgproc.rectangle(mat, topLeft, bottomRight, new Scalar(0, 255, 0), 1); + } + } +} diff --git a/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/utils/OcrUtils.java b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/utils/OcrUtils.java new file mode 100644 index 0000000..a9c57cf --- /dev/null +++ b/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/utils/OcrUtils.java @@ -0,0 +1,64 @@ +package cn.smartjavaai.ocr.utils; + +import ai.djl.modality.cv.Image; +import ai.djl.modality.cv.output.BoundingBox; +import ai.djl.modality.cv.output.DetectedObjects; +import ai.djl.ndarray.NDArray; +import ai.djl.ndarray.NDList; +import cn.smartjavaai.common.entity.DetectionRectangle; +import cn.smartjavaai.common.entity.DetectionResponse; +import lombok.extern.slf4j.Slf4j; + +import java.math.BigDecimal; +import java.util.ArrayList; +import java.util.Iterator; +import java.util.List; +import java.util.Objects; + +/** + * @author dwj + * @date 2025/4/22 + */ +@Slf4j +public class OcrUtils { + + + /** + * 转换为FaceDetectedResult + * @param dt_boxes + * @param img + * @return + */ + public static DetectionResponse convertToDetectionResponse(NDList dt_boxes, Image img){ + if(Objects.isNull(dt_boxes) || dt_boxes.size() == 0){ + return null; + } + DetectionResponse detectionResponse = new DetectionResponse(); + List rectangleList = new ArrayList(); + for(NDArray box : dt_boxes){ + DetectionRectangle rectangle = new DetectionRectangle(); + float[] points = box.toFloatArray(); + log.info("points: {}", points); + int x = (int)points[0]; + int y = (int)points[1]; + int width = new BigDecimal(points[4]).subtract(new BigDecimal(points[6])).intValue(); + int height = new BigDecimal(points[7]).subtract(new BigDecimal(points[1])).intValue(); + + // 修正边界，防止越界 + if (x < 0) x = 0; + if (y < 0) y = 0; + if (x + width > img.getWidth()) width = img.getWidth() - x; + if (y + height > img.getHeight()) height = img.getHeight() - y; + + rectangle.setX(x); + rectangle.setY(y); + rectangle.setHeight(height); + rectangle.setWidth(width); + rectangleList.add(rectangle); + } + detectionResponse.setRectangleList(rectangleList); + return detectionResponse; + } + + +}