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imgproc
Commit a9ca035e by 陈皓
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更新

parent 4ba97838
Showing with 326 additions and 106 deletions
gateway-server/src/main/resources/application.yml
......@@ -23,4 +23,8 @@ spring:
uri: lb://IMGPROC-SERVER
predicates:
- Path=/imgproc/**
- id: file
uri: lb://IMGPROC-SERVER
predicates:
- Path=/file/**
imgproc-server/pom.xml
......@@ -92,6 +92,11 @@
<version>5.8.19</version>
</dependency>
<dependency>
<groupId>com.alibaba</groupId>
<artifactId>easyexcel</artifactId>
<version>3.3.2</version>
</dependency>
<dependency>
<groupId>com.drewnoakes</groupId>
<artifactId>metadata-extractor</artifactId>
<version>2.18.0</version>
......@@ -111,6 +116,12 @@
<artifactId>springfox-swagger-ui</artifactId>
<version>2.9.2</version>
</dependency>
<!-- guava -->
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
<version>32.1.3-jre</version>
</dependency>
</dependencies>
<build>
......
imgproc-server/src/main/java/com/zq/imgproc/controller/ApiController.java
......@@ -91,17 +91,7 @@ public class ApiController {
// 去黑边
RemoveBlackUtil2.remove(imgPath, savePath);
// 图片弯曲矫正
HashMap<String, Object> map = new HashMap<>();
map.put("file", FileUtil.file(savePath));
String response = HttpUtil.post("http://ddns.gxmailu.com:18888/api/correct", map);
JSONObject res = JSONUtil.parseObj(response);
if (res.get("success", Boolean.class)) {
String base64 = res.get("data", String.class);
return ResultVo.success(base64);
} else {
return ResultVo.fail(res.get("msg", String.class));
}
return ResultVo.success(Base64Encoder.encode(savePath));
}
@ApiOperation("图片灰度化")
......
imgproc-server/src/main/java/com/zq/imgproc/controller/FileController.java 0 → 100644
package com.zq.imgproc.controller;
import cn.hutool.core.util.URLUtil;
import com.zq.imgproc.utils.AssertUtils;
import io.swagger.annotations.Api;
import org.springframework.core.io.FileSystemResource;
import org.springframework.core.io.Resource;
import org.springframework.http.ContentDisposition;
import org.springframework.http.HttpHeaders;
import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.CrossOrigin;
import org.springframework.web.bind.annotation.GetMapping;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import javax.servlet.http.HttpServletRequest;
import java.io.File;
/**
* <p>
*
* </p>
*
* @author zq
* @since 2023/11/15
*/
@Api(tags = "访问文件")
@RestController
@CrossOrigin
@RequestMapping("/")
public class FileController {
@GetMapping(value = "/file/**")
public ResponseEntity<Resource> archive(HttpServletRequest request) {
String requestURI = request.getRequestURI();
requestURI = URLUtil.decode(requestURI);
File file = new File(requestURI);
AssertUtils.isTrue(file.exists(), "访问文件不存在");
String contentDisposition = ContentDisposition
.builder("attachment")
.filename(requestURI)
.build().toString();
return ResponseEntity.ok()
.header(HttpHeaders.CONTENT_DISPOSITION, contentDisposition)
.contentType(MediaType.APPLICATION_OCTET_STREAM)
.body(new FileSystemResource(file));
}
}
imgproc-server/src/main/java/com/zq/imgproc/controller/ImgProcController.java
package com.zq.imgproc.controller;
import cn.hutool.core.convert.Convert;
import cn.hutool.core.io.FileUtil;
import cn.hutool.extra.servlet.ServletUtil;
import com.google.common.cache.Cache;
import com.google.common.cache.CacheBuilder;
import com.zq.imgproc.server.ImgProcService;
import com.zq.imgproc.utils.AssertUtils;
import com.zq.imgproc.utils.DecompressUtil;
......@@ -11,6 +14,8 @@ import com.zq.imgproc.vo.*;
import io.swagger.annotations.Api;
import io.swagger.annotations.ApiOperation;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.core.io.Resource;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.multipart.MultipartFile;
......@@ -18,8 +23,10 @@ import javax.servlet.http.HttpServletResponse;
import java.io.IOException;
import java.io.InputStream;
import java.nio.charset.StandardCharsets;
import java.time.Duration;
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.TimeUnit;
/**
* <p>
......@@ -35,11 +42,20 @@ import java.util.List;
@RestController
public class ImgProcController {
// @Resource
// RedisUtils redisUtils;
// private final double CAST = 1;
// private final double DA = 1;
// private final double CLARITY = 10;
/**
* 普通的缓存 Cache
*/
private final Cache<String, Double> cache = CacheBuilder.newBuilder()
.expireAfterAccess(Duration.ofMinutes(30))
.expireAfterWrite(Duration.ofHours(48))
.maximumSize(1024)
.concurrencyLevel(4)
.initialCapacity(1024)
.build();
private final double START_VALUE = 75;
private final double END_VALUE = 175;
private final double CLARITY = 2.5;
private final ImgProcService service;
@Autowired
......@@ -89,6 +105,12 @@ public class ImgProcController {
return ResultVo.success(service.detection(pathList));
}
@ApiOperation("导出检测结果")
@PostMapping("/getDetection")
public ResponseEntity<Resource> getDetection(@RequestBody List<ImgVO> pathList) throws Exception {
return service.getDetection(pathList);
}
@ApiOperation("图片校正(deskew工具)")
@PostMapping("/imageCorrection")
public ResultVo<?> imageCorrection(@RequestBody List<ImgVO> pathList) throws IOException {
......@@ -107,26 +129,29 @@ public class ImgProcController {
return ResultVo.success(service.removeBlack(pathList));
}
// @ApiOperation("获取配置")
// @PostMapping("/getSetting")
// public ResultVo<?> getSetting() {
// double cast = Convert.toDouble(redisUtils.get("img-cast")) == null ? CAST : Convert.toDouble(redisUtils.get("img-cast"));
// double da = Convert.toDouble(redisUtils.get("img-da")) == null ? DA : Convert.toDouble(redisUtils.get("img-da"));
// double clarity = Convert.toDouble(redisUtils.get("img-clarity")) == null ? CLARITY : Convert.toDouble(redisUtils.get("img-clarity"));
// return ResultVo.success(SettingVO.builder().cast(cast).da(da).clarity(clarity).build());
// }
//
// @ApiOperation("设置配置")
// @PostMapping("/setSetting")
// public ResultVo<?> setSetting(@RequestBody SettingVO setting) {
// if (setting == null) {
// return ResultVo.fail("配置不能为空！");
// }
// redisUtils.setStr("img-cast", String.valueOf(setting.getCast()));
// redisUtils.setStr("img-da", String.valueOf(setting.getDa()));
// redisUtils.setStr("img-clarity", String.valueOf(setting.getClarity()));
// return ResultVo.success();
// }
@ApiOperation("获取配置")
@GetMapping("/getSetting")
public ResultVo<?> getSetting() {
Double temp1 = cache.getIfPresent("img-start");
Double temp2 = cache.getIfPresent("img-end");
Double temp3 = cache.getIfPresent("img-clarity");
double start = temp1 == null ? START_VALUE : temp1;
double end = temp2 == null ? END_VALUE : temp2;
double clarity = temp3 == null ? CLARITY : temp3;
return ResultVo.success(SettingVO.builder().startValue(start).endValue(end).clarity(clarity).build());
}
@ApiOperation("设置配置")
@PostMapping("/setSetting")
public ResultVo<?> setSetting(@RequestBody SettingVO setting) {
if (setting == null) {
return ResultVo.fail("配置不能为空！");
}
cache.put("img-start", setting.getStartValue());
cache.put("img-end", setting.getEndValue());
cache.put("img-clarity", setting.getClarity());
return ResultVo.success();
}
@ApiOperation("图片旋转")
@PostMapping("/rotate")
......
imgproc-server/src/main/java/com/zq/imgproc/server/ImgProcService.java
......@@ -6,6 +6,7 @@ import cn.hutool.core.codec.Base64Encoder;
import cn.hutool.core.convert.Convert;
import cn.hutool.core.img.ImgUtil;
import cn.hutool.core.io.FileUtil;
import com.alibaba.excel.EasyExcel;
import com.drew.imaging.ImageMetadataReader;
import com.drew.metadata.Directory;
import com.drew.metadata.Metadata;
......@@ -23,13 +24,22 @@ import org.opencv.core.MatOfDouble;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.core.io.InputStreamResource;
import org.springframework.core.io.Resource;
import org.springframework.http.ContentDisposition;
import org.springframework.http.HttpHeaders;
import org.springframework.http.MediaType;
import org.springframework.http.ResponseEntity;
import org.springframework.stereotype.Service;
import org.springframework.web.multipart.MultipartFile;
import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.BufferedInputStream;
import java.io.File;
import java.io.IOException;
import java.math.BigDecimal;
import java.math.RoundingMode;
import java.text.SimpleDateFormat;
import java.util.*;
import java.util.regex.Matcher;
......@@ -56,7 +66,6 @@ public class ImgProcService {
public List<ImgVO> detection(List<ImgVO> pathList) throws Exception {
List<ImgVO> res = new ArrayList<>(pathList.size());
for (ImgVO one : pathList) {
DetectionResVo2 vo = new DetectionResVo2();
String path = one.getUrl();
Mat image = Imgcodecs.imread(path);
......@@ -66,13 +75,10 @@ public class ImgProcService {
// 检测图片的DPI
vo.setDpi(getDpi(FileUtil.file(path)));
// 检测图片清晰度
vo.setClarity(ImageUtil.tenengrad(image));
BigDecimal clarity = BigDecimal.valueOf(ImageUtil.tenengrad(image));
vo.setClarity(clarity.setScale(2, RoundingMode.HALF_UP).doubleValue());
// 检测图片的亮度
double[] arr = brightnessDetection(image);
if (arr != null) {
vo.setCast(arr[0]);
vo.setDa(arr[1]);
}
vo.setBrightness(Convert.toInt(ImageUtil.brightness(image)));
// 检测图片倾斜角度
vo.setAngle(getAngle(image));
// 检测图片的黑边
......@@ -438,7 +444,7 @@ public class ImgProcService {
index++;
}
// 修正
return ImageUtil.correct(pathList);
return pathList;
}
public List<ImgVO> deskew(List<ImgVO> pathList) {
......@@ -693,5 +699,45 @@ public class ImgProcService {
return Base64Encoder.encode(FileUtil.readBytes(dst));
}
public ResponseEntity<Resource> getDetection(List<ImgVO> pathList) throws Exception {
if (pathList == null || pathList.size() == 0) {
return ResponseEntity.badRequest().build();
}
pathList = detection(pathList);
String filePath = "/data/temp/" + UuidUtils.uuidNoDash() + ".xlsx";
EasyExcel.write(filePath, DetectionDTO.class).sheet("图片检测报告").doWrite(getData(pathList));
BufferedInputStream stream = FileUtil.getInputStream(filePath);
if (stream == null) {
return ResponseEntity.notFound().build();
}
String contentDisposition = ContentDisposition
.builder("attachment")
.filename("图片检测报告.xlsx")
.build().toString();
return ResponseEntity.ok()
.header(HttpHeaders.CONTENT_DISPOSITION, contentDisposition)
.contentType(MediaType.APPLICATION_OCTET_STREAM)
.body(new InputStreamResource(stream));
}
private List<DetectionDTO> getData(List<ImgVO> pathList) {
List<DetectionDTO> dtos = new ArrayList<>(pathList.size());
for (ImgVO imgVO : pathList) {
DetectionResVo2 detectionRes = imgVO.getDetectionRes();
DetectionDTO dto = new DetectionDTO();
dto.setFilename(imgVO.getFileName());
dto.setResolution(detectionRes.getWidthResolution() + " x " + detectionRes.getHeightResolution());
dto.setDpi(detectionRes.getDpi());
dto.setBrightness(detectionRes.getBrightness());
dto.setClarity(detectionRes.getClarity());
dto.setAngle(detectionRes.getAngle());
dto.setBlack(detectionRes.getBlack() ? "是" : "否");
dtos.add(dto);
}
return dtos;
}
}
imgproc-server/src/main/java/com/zq/imgproc/utils/Deskew.java
......@@ -10,9 +10,6 @@ import java.util.HashMap;
import java.util.List;
import java.util.Map;
import static org.opencv.highgui.HighGui.imshow;
import static org.opencv.highgui.HighGui.waitKey;
public class Deskew {
public static void main(String[] args) {
......@@ -136,6 +133,9 @@ public class Deskew {
int w = image.cols();
int h = image.rows();
if (angle < 0) {
angle = 360 + angle;
}
Point center = new Point((double) w / 2, (double) h / 2);
double scale = 1.0;
......
imgproc-server/src/main/java/com/zq/imgproc/utils/ImageUtil.java
......@@ -152,14 +152,17 @@ public class ImageUtil {
// 灰度化
Mat mat = Imgcodecs.imread(src);
Mat gray = mat.clone();
if (mat.channels() == 4 || mat.channels() == 3) {
// if (mat.channels() == 4 || mat.channels() == 3) {
// Imgproc.cvtColor(mat, gray, Imgproc.COLOR_BGR2GRAY);
// } else if (mat.channels() == 2) {
// Imgproc.cvtColor(mat, gray, Imgproc.COLOR_BGR5652GRAY);
// } else {
// gray = mat;
// }
Imgproc.cvtColor(mat, gray, Imgproc.COLOR_BGR2GRAY);
} else if (mat.channels() == 2) {
Imgproc.cvtColor(mat, gray, Imgproc.COLOR_BGR5652GRAY);
} else {
gray = mat;
}
saveImage(gray, dst);
gray.release();
mat.release();
}
/**
......@@ -383,7 +386,7 @@ public class ImageUtil {
}
/**
* 计算图片平均亮度
* 计算图片平均亮度，范围是0到255
*
* @param path 图片路径
* @return 图片平均亮度
......
imgproc-server/src/main/java/com/zq/imgproc/utils/RemoveBlackUtil.java
......@@ -17,14 +17,12 @@ import java.util.Random;
* @author chenhao
* @since 2023/3/8 9:31
*/
@SuppressWarnings("all")
public class RemoveBlackUtil {
public static void main(String[] args) {
long start = System.currentTimeMillis();
String testImg = "C:\\Users\\11419\\Desktop\\project\\company\\test\\9.jpg";
String resImg = "C:\\Users\\11419\\Desktop\\project\\company\\test\\res9.jpg";
System.load("C:\\Users\\11419\\Desktop\\project\\company\\imgproc\\lib\\opencv_java460.dll");
String testImg = "C:\\Users\\11419\\Desktop\\test\\a.jpg";
String resImg = "C:\\Users\\11419\\Desktop\\test\\8.jpg";
System.load("D:\\project\\imgproc\\lib\\opencv_java460.dll");
remove(testImg, resImg);
}
......@@ -36,21 +34,21 @@ public class RemoveBlackUtil {
Mat greyImg = img.clone();
//1.彩色转灰色
Imgproc.cvtColor(img, greyImg, Imgproc.COLOR_BGR2GRAY);
// ImageUtil.saveImage(greyImg, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\1.jpg");
ImageUtil.saveImage(greyImg, "C:\\Users\\11419\\Desktop\\test\\1.jpg");
Mat gaussianBlurImg = greyImg.clone();
// 2.高斯滤波，降噪
Imgproc.GaussianBlur(greyImg, gaussianBlurImg, new Size(3,3),2,2);
// ImageUtil.saveImage(gaussianBlurImg, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\2.jpg");
Mat cannyImg = gaussianBlurImg.clone();
Imgproc.GaussianBlur(greyImg, gaussianBlurImg, new Size(3,3),0);
ImageUtil.saveImage(greyImg, "C:\\Users\\11419\\Desktop\\test\\2.jpg");
// 3.Canny边缘检测
Imgproc.Canny(gaussianBlurImg, cannyImg, 20, 60, 3, false);
// ImageUtil.saveImage(cannyImg, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\3.jpg");
Mat cannyImg = gaussianBlurImg.clone();
Imgproc.Canny(gaussianBlurImg, cannyImg, 50, 200);
ImageUtil.saveImage(cannyImg, "C:\\Users\\11419\\Desktop\\test\\3.jpg");
// 4.膨胀，连接边缘
Mat dilateImg = cannyImg.clone();
Imgproc.dilate(cannyImg, dilateImg, new Mat(), new Point(-1, -1), 2, 1, new Scalar(1));
// ImageUtil.saveImage(dilateImg, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\4.jpg");
Imgproc.dilate(cannyImg, dilateImg, new Mat(), new Point(-1, -1), 3, 1, new Scalar(1));
ImageUtil.saveImage(dilateImg, "C:\\Users\\11419\\Desktop\\test\\4.jpg");
//5.对边缘检测的结果图再进行轮廓提取
List<MatOfPoint> contours = new ArrayList<>();
List<MatOfPoint> drawContours = new ArrayList<>();
......@@ -64,8 +62,7 @@ public class RemoveBlackUtil {
MatOfPoint2f approx = new MatOfPoint2f();
approx.convertTo(approx, CvType.CV_32F);
for (int i = 0; i < contours.size(); i++) {
MatOfPoint contour = contours.get(i);
for (MatOfPoint contour : contours) {
// 边框的凸包
Imgproc.convexHull(contour, hull);
// 用凸包计算出新的轮廓点
......@@ -78,7 +75,7 @@ public class RemoveBlackUtil {
MatOfPoint2f contourHull = new MatOfPoint2f();
contourHull.fromList(newPoints);
// 多边形拟合凸包边框(此时的拟合的精度较低)
Imgproc.approxPolyDP(contourHull, approx, Imgproc.arcLength(contourHull, true)*0.02, true);
Imgproc.approxPolyDP(contourHull, approx, Imgproc.arcLength(contourHull, true) * 0.02, true);
MatOfPoint mat = new MatOfPoint();
mat.fromArray(approx.toArray());
drawContours.add(mat);
......@@ -89,7 +86,7 @@ public class RemoveBlackUtil {
Imgproc.isContourConvex(approxf1)) {
double maxCosine = 0;
for (int j = 2; j < 5; j++) {
double cosine = Math.abs(getAngle(approxf1.toArray()[j%4], approxf1.toArray()[j-2], approxf1.toArray()[j-1]));
double cosine = Math.abs(getAngle(approxf1.toArray()[j % 4], approxf1.toArray()[j - 2], approxf1.toArray()[j - 1]));
maxCosine = Math.max(maxCosine, cosine);
}
// 角度大概72度
......@@ -103,38 +100,35 @@ public class RemoveBlackUtil {
}
//这里是把提取出来的轮廓通过不同颜色的线描述出来，具体效果可以自己去看
Random r = new Random();
// for (int i = 0; i < drawContours.size(); i++) {
// Imgproc.drawContours(linePic, drawContours, i, new Scalar(r.nextInt(255),r.nextInt(255), r.nextInt(255)));
// }
// ImageUtil.saveImage(linePic, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\5.jpg");
for (int i = 0; i < drawContours.size(); i++) {
Imgproc.drawContours(linePic, drawContours, i, new Scalar(r.nextInt(255),r.nextInt(255), r.nextInt(255)));
}
ImageUtil.saveImage(linePic, "C:\\Users\\11419\\Desktop\\test\\5.jpg");
//7.找出最大的矩形
int index = findLargestSquare(squares);
MatOfPoint largest_square = null;
if(squares != null && squares.size() > 0){
MatOfPoint largest_square;
if(squares.size() > 0){
largest_square = squares.get(index);
}else{
System.out.println("图片无法识别");
return;
}
Mat polyPic = Mat.zeros(img.size(), CvType.CV_8UC3);
// Imgproc.drawContours(polyPic, squares, index, new Scalar(0, 0,255), 2);
// ImageUtil.saveImage(polyPic, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\6.jpg");
Imgproc.drawContours(polyPic, squares, index, new Scalar(0, 0,255), 2);
ImageUtil.saveImage(polyPic, "C:\\Users\\11419\\Desktop\\test\\6.jpg");
//存储矩形的四个凸点
hull = new MatOfInt();
Imgproc.convexHull(largest_square, hull, false);
List<Integer> hullList = hull.toList();
List<Point> polyContoursList = largest_square.toList();
List<Point> hullPointList = new ArrayList<>();
List<Point> lastHullPointList = new ArrayList<>();
for(int i = 0; i < hullList.size();i++){
Imgproc.circle(polyPic, polyContoursList.get(hullList.get(i)), 10, new Scalar(r.nextInt(255),r.nextInt(255), r.nextInt(255), 3));
hullPointList.add(polyContoursList.get(hullList.get(i)));
for (Integer integer : hullList) {
Imgproc.circle(polyPic, polyContoursList.get(integer), 10, new Scalar(r.nextInt(255), r.nextInt(255), r.nextInt(255), 3));
hullPointList.add(polyContoursList.get(integer));
}
Core.addWeighted(polyPic, 1, img, 1, 0, img);
// ImageUtil.saveImage(img, "C:\\Users\\11419\\Desktop\\project\\company\\test\\guoc\\7.jpg");
for(int i = 0; i < hullPointList.size(); i++){
lastHullPointList.add(hullPointList.get(i));
}
ImageUtil.saveImage(img, "C:\\Users\\11419\\Desktop\\test\\7.jpg");
List<Point> lastHullPointList = new ArrayList<>(hullPointList);
//dstPoints储存的是变换后各点的坐标，依次为左上，右上，右下， 左下
//srcPoints储存的是上面得到的四个角的坐标
Point[] dstPoints = {new Point(0,0), new Point(img.cols(),0), new Point(img.cols(),img.rows()), new Point(0,img.rows())};
......
imgproc-server/src/main/java/com/zq/imgproc/utils/RemoveBlackUtil2.java
......@@ -18,7 +18,7 @@ public class RemoveBlackUtil2 {
/**
* 去黑边"全黑"阈值
*/
private static final Integer BLACK_VALUE = 200;
private static final Integer BLACK_VALUE = 100;
public static void remove(String src, String dst) {
Mat mat = Imgcodecs.imread(src);
......
imgproc-server/src/main/java/com/zq/imgproc/utils/Test2.java 0 → 100644
package com.zq.imgproc.utils;
import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import java.io.IOException;
/**
* <p>
*
* </p>
*
* @author chenhao
* @since 2023/11/20
*/
public class Test2 {
public static void main(String[] args) throws IOException {
System.load("D:\\project\\imgproc\\lib\\opencv_java460.dll");
String src = "C:\\Users\\11419\\Desktop\\Deskew\\TestImages\\6.png";
String dst = "C:\\Users\\11419\\Desktop\\Deskew\\TestImages\\6res.png";
// 读取输入图像
Mat inputImage = Imgcodecs.imread(src);
// 将图像转换为灰度图像
Mat grayImage = new Mat();
Imgproc.cvtColor(inputImage, grayImage, Imgproc.COLOR_BGR2GRAY);
// 对灰度图像进行高斯模糊处理
Mat blurredImage = new Mat();
Imgproc.GaussianBlur(grayImage, blurredImage, new org.opencv.core.Size(3, 3), 0);
// 使用拉普拉斯算子进行边缘检测
Mat laplacianImage = new Mat();
Imgproc.Laplacian(blurredImage, laplacianImage, CvType.CV_16S, 3, 1, 0, Core.BORDER_DEFAULT);
Core.convertScaleAbs(laplacianImage, laplacianImage);
// 对滤波后的图像进行阈值处理，找到孤立点
double threshold = 30.0;
Mat binaryImage = new Mat();
Imgproc.threshold(laplacianImage, binaryImage, threshold, 255, Imgproc.THRESH_BINARY);
// 计算检测到的孤立点数量
int isolatedPointCount = Core.countNonZero(binaryImage);
// 输出孤立点数量
System.out.println("检测到的孤立点数量：" + isolatedPointCount);
// 可以在结果图像上标记检测到的孤立点，或者保存结果图像以便查看
Imgcodecs.imwrite(dst, binaryImage);
}
}
imgproc-server/src/main/java/com/zq/imgproc/vo/DetectionDTO.java 0 → 100644
package com.zq.imgproc.vo;
import com.alibaba.excel.annotation.ExcelIgnore;
import com.alibaba.excel.annotation.ExcelProperty;
import io.swagger.annotations.ApiModelProperty;
import lombok.Data;
import lombok.EqualsAndHashCode;
/**
* <p>
*
* </p>
*
* @author chenhao
* @since 2023/11/24
*/
@Data
@EqualsAndHashCode
public class DetectionDTO {
@ExcelProperty("文件名称")
private String filename;
@ExcelProperty("分辨率")
private String resolution;
@ExcelProperty("DPI")
private Integer dpi;
@ExcelProperty("平均亮度值")
private double brightness;
@ExcelProperty("清晰度值")
private double clarity;
@ExcelProperty("倾斜角度")
private double angle;
@ExcelProperty("黑边情况")
private String black;
}
imgproc-server/src/main/java/com/zq/imgproc/vo/DetectionResVo2.java
......@@ -27,11 +27,8 @@ public class DetectionResVo2 {
@ApiModelProperty("图片的DPI")
private Integer dpi;
@ApiModelProperty("亮度值")
private double cast;
@ApiModelProperty("亮度异常值")
private double da;
@ApiModelProperty("平均亮度值")
private double brightness;
@ApiModelProperty("图片的清晰度指标，值越大越清晰")
private double clarity;
......
imgproc-server/src/main/java/com/zq/imgproc/vo/SettingVO.java
......@@ -20,11 +20,11 @@ import lombok.NoArgsConstructor;
@Builder
public class SettingVO {
@ApiModelProperty("亮度值")
private double cast;
@ApiModelProperty("亮度值起始范围")
private double startValue;
@ApiModelProperty("亮度异常值")
private double da;
@ApiModelProperty("亮度值结束范围")
private double endValue;
@ApiModelProperty("图片的清晰度指标，值越大越清晰")
private double clarity;
......
imgproc-server/src/main/resources/application.yml
......@@ -18,12 +18,12 @@ spring:
ip:
local-parsing: true
#imgconfig:
# opencv: /opt/services/tianjin-backend/lib/opencv_java460.so
# deskew: /opt/services/tianjin-backend/lib/Deskew/Bin/deskew
# deskewpy: /opt/tianjin/lib/correct.py
imgconfig:
opencv: D:/project/imgproc/lib/opencv_java460.dll
deskew: C:/Users/11419/Desktop/Deskew/Bin/deskew.exe
deskewpy: D:/project/imgproc/lib/correct.py
opencv: /opt/tianjin/lib/opencv_java460.so
deskew: /opt/tianjin/lib/Deskew/Bin/deskew
deskewpy: /opt/tianjin/lib/correct.py
#imgconfig:
# opencv: D:/project/imgproc/lib/opencv_java460.dll
# deskew: C:/Users/11419/Desktop/Deskew/Bin/deskew.exe
# deskewpy: D:/project/imgproc/lib/correct.py
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