1、FaceNet 特征提取新增人脸对齐

2、人脸检测新5点人脸关键点定位
3、特征提取接口支持多人脸和最佳人脸提取
4、修复人脸框边界精度问题
5、更新 Maven 发布的 groupId

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<Point> 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<ai.djl.modality.cv.output.Point> 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;
+    }
+}