Files
SmartJavaAI/smartjavaai-ocr/src/main/java/cn/smartjavaai/ocr/opencv/OcrNDArrayUtils.java
dengwenjie 42d2943a94 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
2025-04-28 16:13:34 +08:00

229 lines
5.5 KiB
Java

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;
}
}