你看过杰克逊图书馆吗？它允许将JSON / Yaml内容映射到Java POJO。
但是，对于yaml版本指令，由于它似乎无效，因此我不确定如何处理它。在我的示例中，我已预先手动将其删除。当然，可以找到更好的解决方案，但我不知道。
：对于矩阵对象，我做了一个笨拙的POJO，供Jackson用来内部读取brut YAML。然后，我添加了一个转换层（见@JsonSerialize 和 @JsonDeserialize 上anotations OpenCVConfig 类）这个简单的POJO转换为专业OpenCV的矩阵。Jackson提供了多种映射技术（流技术，自定义转换器/解串器，指导注释等），因此您可以探索其功能，以找到最适合您需要的解决方案。
因此，要使该示例正常工作，您将需要两个依赖项（以maven格式给出）：
<!-- (De)serialization engine -->
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>2.10.0</version>
</dependency>
<!-- Yaml support -->
<dependency>
<groupId>com.fasterxml.jackson.dataformat</groupId>
<artifactId>jackson-dataformat-yaml</artifactId>
<version>2.10.0</version>
</dependency>
这是Maven存储库描述页面：
jackson-databind ：通过Maven搜索或通过mvnrepository
Jackson-dataformat-yaml ：通过Maven搜索或通过mvnrepository
注意 ：我的示例包含很多样板，就像我手动（以及IDE）生成的getter / setter一样。您应该通过以下两种方式减少代码量：
使用Java 14记录（不确定当前是否可用）
package fr.amanin.stackoverflow;
import java.util.Arrays; import java.util.stream.Stream;
import com.fasterxml.jackson.core.type.TypeReference; import com.fasterxml.jackson.databind.JavaType; import com.fasterxml.jackson.databind.ObjectMapper; import com.fasterxml.jackson.databind.annotation.JsonDeserialize; import com.fasterxml.jackson.databind.annotation.JsonSerialize; import com.fasterxml.jackson.databind.type.TypeFactory; import com.fasterxml.jackson.databind.util.Converter; import com.fasterxml.jackson.dataformat.yaml.YAMLGenerator; import com.fasterxml.jackson.dataformat.yaml.YAMLMapper; import org.opencv.core.CvType; import org.opencv.core.Mat;
public class YAMLOpenCV { /* * Engine in charge of YAML decoding./ public static final ObjectMapper OPENCV_YAML_MAPPER = new YAMLMapper();
public static void main(String[] args) throws Exception {
nu.pattern.OpenCV.loadShared();
System.loadLibrary(org.opencv.core.Core.NATIVE_LIBRARY_NAME);
final String confStr =
"cameraMatrix: !!opencv-matrix\n" +
" rows: 3\n" +
" cols: 3\n" +
" dt: d\n" +
" data: [ 6.6278599887122368e+02, 0., 3.1244256016006659e+02, 0.,\n" +
" 6.6129276875199082e+02, 2.2747179767124251e+02, 0., 0., 1. ]\n" +
"imageSize_width: 640\n" +
"imageSize_height: 480\n" +
"sensorSize_width: 0\n" +
"sensorSize_height: 0\n" +
"distCoeffs: !!opencv-matrix\n" +
" rows: 5\n" +
" cols: 1\n" +
" dt: d\n" +
" data: [ -1.8848338341464690e-01, 1.0721890419183855e+00,\n" +
" -3.5244467228016116e-03, -7.0195032848241403e-04,\n" +
" -2.0412827999027101e+00 ]\n" +
"reprojectionError: 2.1723265945911407e-01";
OpenCVConfig conf = OPENCV_YAML_MAPPER.readValue(confStr, OpenCVConfig.class);
System.out.println(conf);
String serialized = OPENCV_YAML_MAPPER.writeValueAsString(conf);
System.out.println(serialized);
}
/**
* Java model mirroring YAML configuration. Jackson will fill it
* with values read from YAML configuration file, matching YAML
* fields with this class property names.
*/
public static class OpenCVConfig {
int imageSize_width;
int imageSize_height;
int sensorSize_width;
int sensorSize_height;
double reprojectionError;
/* Special case: Matrix objects are decoded in two passes:
* 1. Jackson will check below converters, and use their input
* type to decode YAML to `Matrix` object (intermediate step).
* 2. Jackson uses converter to delegate to user the mapping
* from this intermediate POJO to specialized target (`Mat` here)
*/
@JsonDeserialize(converter = ToMatConverter.class)
@JsonSerialize(converter = FromMatConverter.class)
Mat cameraMatrix;
@JsonDeserialize(converter = ToMatConverter.class)
@JsonSerialize(converter = FromMatConverter.class)
Mat distCoeffs;
public int getImageSize_width() {
return imageSize_width;
}
public OpenCVConfig setImageSize_width(int imageSize_width) {
this.imageSize_width = imageSize_width;
return this;
}
public int getImageSize_height() {
return imageSize_height;
}
public OpenCVConfig setImageSize_height(int imageSize_height) {
this.imageSize_height = imageSize_height;
return this;
}
public int getSensorSize_width() {
return sensorSize_width;
}
public OpenCVConfig setSensorSize_width(int sensorSize_width) {
this.sensorSize_width = sensorSize_width;
return this;
}
public int getSensorSize_height() {
return sensorSize_height;
}
public OpenCVConfig setSensorSize_height(int sensorSize_height) {
this.sensorSize_height = sensorSize_height;
return this;
}
public double getReprojectionError() {
return reprojectionError;
}
public OpenCVConfig setReprojectionError(double reprojectionError) {
this.reprojectionError = reprojectionError;
return this;
}
public Mat getCameraMatrix() {
return cameraMatrix;
}
public OpenCVConfig setCameraMatrix(Mat cameraMatrix) {
this.cameraMatrix = cameraMatrix;
return this;
}
public Mat getDistCoeffs() {
return distCoeffs;
}
public OpenCVConfig setDistCoeffs(Mat distCoeffs) {
this.distCoeffs = distCoeffs;
return this;
}
@Override
public String toString() {
return "OpenCVConfig{" +
"imageSize_width=" + imageSize_width +
", imageSize_height=" + imageSize_height +
", sensorSize_width=" + sensorSize_width +
", sensorSize_height=" + sensorSize_height +
", camerMatrix=" + cameraMatrix +
", distCoeffs=" + distCoeffs +
'}';
}
}
/**
* Converter used for serialization of Mat objects into YAML.
*/
private static class FromMatConverter implements Converter<Mat, Matrix> {
@Override
public Matrix convert(Mat value) {
final Matrix result = new Matrix();
result.cols = value.cols();
result.rows = value.rows();
final int type = value.type();
result.dt = Stream.of(MatrixDataType.values())
.filter(dt -> dt.mapping == type)
.findAny()
.orElseThrow(() -> new UnsupportedOperationException("No matching datatype found for "+type));
int idx = 0;
result.data = new double[result.rows * result.cols];
for (int r = 0 ; r < result.rows ; r++) {
for (int c = 0; c < result.cols; c++) {
final double[] v = value.get(r, c);
result.data[idx++] = v[0];
}
}
return result;
}
@Override
public JavaType getInputType(TypeFactory typeFactory) {
return typeFactory.constructType(new TypeReference<Mat>() {});
}
@Override
public JavaType getOutputType(TypeFactory typeFactory) {
return typeFactory.constructType(new TypeReference<Matrix>() {});
}
}
/**
* Converter used at read time, to map YAML object to OpenCV Mat.
*/
private static class ToMatConverter implements Converter<Matrix, Mat> {
@Override
public Mat convert(Matrix in) {
final Mat result = new Mat(in.rows, in.cols, in.dt.mapping);
int idx = 0;
for (int r = 0 ; r < in.rows ; r++) {
for (int c = 0; c < in.cols; c++) {
result.put(r, c, in.data[idx++]);
}
}
return result;
}
@Override
public JavaType getInputType(TypeFactory typeFactory) {
return typeFactory.constructType(new TypeReference<Matrix>() {});
}
@Override
public JavaType getOutputType(TypeFactory typeFactory) {
return typeFactory.constructType(new TypeReference<Mat>() {});
}
}
public static class Matrix {
int rows;
int cols;
MatrixDataType dt;
double[] data;
public int getRows() {
return rows;
}
public Matrix setRows(int rows) {
this.rows = rows;
return this;
}
public int getCols() {
return cols;
}
public Matrix setCols(int cols) {
this.cols = cols;
return this;
}
public MatrixDataType getDt() {
return dt;
}
public Matrix setDt(MatrixDataType dt) {
this.dt = dt;
return this;
}
public double[] getData() {
return data;
}
public Matrix setData(double[] data) {
this.data = data;
return this;
}
double at(int x, int y) {
if (x >= cols || y >= rows) throw new IllegalArgumentException("Bad coordinate");
return data[y*rows + x];
}
@Override
public String toString() {
return "Matrix{" +
"rows=" + rows +
", cols=" + cols +
", dt=" + dt +
", data=" + Arrays.toString(data) +
'}';
}
}
/* public static class MatDeserializer extends StdDeserializer
protected MatDeserializer() {
super(Mat.class);
}
@Override
public Mat deserialize(JsonParser p, DeserializationContext ctxt) throws IOException, JsonProcessingException {
final int rows, cols;
final MatrixDataType dtype;
final double[] data;
}
}
public static class MatSerializer extends StdSerializer<Mat> {
protected MatSerializer() {
super(Mat.class);
}
@Override
public void serialize(Mat value, JsonGenerator gen, SerializerProvider provider) throws IOException {
gen.writeNumberField("rows", value.rows());
gen.writeNumberField("cols", value.cols());
gen.writeFieldName("data");
gen.writeStartArray();
gen.writeEndarray();
}
}
*/ public enum MatrixDataType { d(CvType.CV_64F), f(CvType.CV_32F);
public final int mapping;
MatrixDataType(int mapping) {
this.mapping = mapping;
}
}
}
希望能帮助到你，
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