Я использую этот учебник для JNI в Eclipse:
https://www3.ntu.edu.sg/home/ehchua/programming/java/JavaNativeInterface.html#zz-2.6
(я использую только часть "2.6 JNI в Eclipse").
Пример из этого урока (HelloJNI) работал для меня, а также для моего проекта.
Затем я сделал одно изменение в заголовочном файле - я добавил строку:
#include <vector>
И собрал его заново, следуя инструкции в руководстве:
Запустите make-файл для цели "all", щелкнув правой кнопкой мыши на make-файле ⇒ Make> Targets ⇒ Build ⇒ Выберите цель "all" ⇒ Build
И он заменил мой заголовочный файл оригинальным заголовочным файлом ......
Я не понимаю, почему это происходит, потому что зависимостью целевого SPImageProc.h является SPImageProc.class, и я не изменил SPImageProc.class, я только изменил SPImageProc.h.
Среда разработки
+ Eclipse IDE для разработчиков Java (32-разрядная версия) Версия: Kepler Service Release 2.
+ CDT плагин для Eclipse
+ Windows 10 64-разрядная (я использую 32-разрядное затмение, потому что в какой-то момент 64-разрядное затмение не могло открыться, и решение состояло в том, чтобы использовать 32-разрядное затмение)
Makefile
# Define a variable for classpath
CLASS_PATH = ../bin
# Define a virtual path for .class in the bin directory
vpath %.class $(CLASS_PATH)
all : spimageproc.dll
# $@ matches the target, $< matches the first dependency
spimageproc.dll : SPImageProc.o
g++ -Wl,--add-stdcall-alias -shared -o $@ $<
# $@ matches the target, $< matches the first dependency
SPImageProc.o : SPImageProc.cpp SPImageProc.h
g++ -I"C:\Program Files (x86)\Java\jdk1.8.0_212\include" -I"C:\Program Files (x86)\Java\jdk1.8.0_212\include\win32" -c $< -o $@
# $* matches the target filename without the extension
SPImageProc.h : SPImageProc.class
javah -classpath $(CLASS_PATH) $*
clean :
rm SPImageProc.h SPImageProc.o spimageproc.dll
SPImageProc.h
/* DO NOT EDIT THIS FILE - it is machine generated */
#include <jni.h>
/* Header for class SPImageProc */
#ifndef _Included_SPImageProc
#define _Included_SPImageProc
#ifdef __cplusplus
extern "C" {
#endif
/*
* Class: SPImageProc
* Method: cppFunc
* Signature: ()V
*/
JNIEXPORT void JNICALL Java_SPImageProc_cppFunc
(JNIEnv *, jobject);
#ifdef __cplusplus
}
#endif
#endif
SPImageProc.cpp
#include <jni.h>
#include <stdio.h>
#include "SPImageProc.h"
JNIEXPORT void JNICALL Java_SPImageProc_cppFunc(JNIEnv *env, jobject thisObj) {
printf("After adding include vector to header !\n");
return;
}
SPImageProc.java
public class SPImageProc {
static {
System.loadLibrary("spimageproc"); // spimageproc.dll
}
// Declare native method
private native void cppFunc();
public static void function() {
new SPImageProc().cppFunc(); // Allocate an instance and invoke the native
// method
}
}
CBIR.java
public class CBIR {
public static void main(String[] args) {
SPImageProc.function();
}
}
Редактировать
Это оригинальные файлы, которые я хотел использовать (именно поэтому я решил использовать jni):
* * SPImageProc.cpp тысяча сорок-девять
#include <cstdlib>
#include <cassert>
#include <cstring>
#include <opencv2/xfeatures2d.hpp>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/highgui.hpp>
#include <cstdio>
#include "SPImageProc.h"
extern "C" {
#include "SPLogger.h"
}
using namespace cv;
using namespace std;
#define PCA_MEAN_STR "mean"
#define PCA_EIGEN_VEC_STR "e_vectors"
#define PCA_EIGEN_VAL_STR "e_values"
#define STRING_LENGTH 1024
#define WARNING_MSG_LENGTH 2048
#define GENERAL_ERROR_MSG "An error occurred"
#define PCA_DIM_ERROR_MSG "PCA dimension couldn't be resolved"
#define PCA_FILE_NOT_EXIST "PCA file doesn't exist"
#define PCA_FILE_NOT_RESOLVED "PCA filename couldn't be resolved"
#define NUM_OF_IMAGES_ERROR "Number of images couldn't be resolved"
#define NUM_OF_FEATS_ERROR "Number of features couldn't be resolved"
#define MINIMAL_GUI_ERROR "Minimal GUI mode couldn't be resolved"
#define IMAGE_PATH_ERROR "Image path couldn't be resolved"
#define IMAGE_NOT_EXIST_MSG ": Images doesn't exist"
#define MINIMAL_GUI_NOT_SET_WARNING "Cannot display images in non-Minimal-GUI mode"
#define ALLOC_ERROR_MSG "Allocation error"
#define INVALID_ARG_ERROR "Invalid arguments"
void sp::ImageProc::initFromConfig(const SPConfig config) {
SP_CONFIG_MSG msg = SP_CONFIG_SUCCESS;
pcaDim = spConfigGetPCADim(config, &msg);
if (msg != SP_CONFIG_SUCCESS) {
spLoggerPrintError(PCA_DIM_ERROR_MSG, __FILE__, __func__, __LINE__);
throw Exception();
}
numOfImages = spConfigGetNumOfImages(config, &msg);
if (msg != SP_CONFIG_SUCCESS) {
spLoggerPrintError(NUM_OF_IMAGES_ERROR, __FILE__, __func__, __LINE__);
throw Exception();
}
numOfFeatures = spConfigGetNumOfFeatures(config, &msg);
if (msg != SP_CONFIG_SUCCESS) {
spLoggerPrintError(NUM_OF_FEATS_ERROR, __FILE__, __func__, __LINE__);
throw Exception();
}
minimalGui = spConfigMinimalGui(config, &msg);
if (msg != SP_CONFIG_SUCCESS) {
spLoggerPrintError(MINIMAL_GUI_ERROR, __FILE__, __func__, __LINE__);
throw Exception();
}
}
void sp::ImageProc::getImagesMat(vector<Mat>& images, const SPConfig config) {
char warningMSG[WARNING_MSG_LENGTH] = { '\0' };
for (int i = 0; i < numOfImages; i++) {
char imagePath[STRING_LENGTH + 1] = { '\0' };
if (spConfigGetImagePath(imagePath, config, i) != SP_CONFIG_SUCCESS) {
spLoggerPrintError(IMAGE_PATH_ERROR, __FILE__, __func__, __LINE__);
throw Exception();
}
Mat img = imread(imagePath, IMREAD_GRAYSCALE);
if (img.empty()) {
sprintf(warningMSG, "%s %s", imagePath, IMAGE_NOT_EXIST_MSG);
spLoggerPrintWarning(warningMSG, __FILE__, __func__, __LINE__);
continue;
}
images.push_back(img);
}
}
void sp::ImageProc::getFeatures(vector<Mat>& images, Mat& features) {
//To store the keypoints that will be extracted by SIFT
vector<KeyPoint> keypoints;
//To store the SIFT descriptor of current image
Mat descriptor;
//To store all the descriptors that are extracted from all the images.
//The SIFT feature extractor and descriptor
Ptr<xfeatures2d::SiftDescriptorExtractor> detector =
xfeatures2d::SIFT::create(numOfFeatures);
//feature descriptors and build the vocabulary
for (int i = 0; i < static_cast<int>(images.size()); i++) {
//detect feature points
detector->detect(images[i], keypoints);
//compute the descriptors for each keypoint
detector->compute(images[i], keypoints, descriptor);
//put the all feature descriptors in a single Mat object
features.push_back(descriptor);
}
}
void sp::ImageProc::preprocess(const SPConfig config) {
try {
vector<Mat> images;
Mat features;
char pcaPath[STRING_LENGTH + 1] = { '\0' };
getImagesMat(images, config);
getFeatures(images, features);
pca = PCA(features, Mat(), CV_PCA_DATA_AS_ROW, pcaDim);
if (spConfigGetPCAPath(pcaPath, config) != SP_CONFIG_SUCCESS) {
spLoggerPrintError(PCA_FILE_NOT_RESOLVED, __FILE__, __func__,
__LINE__);
throw Exception();
}
FileStorage fs(pcaPath, FileStorage::WRITE);
fs << PCA_EIGEN_VEC_STR << pca.eigenvectors;
fs << PCA_EIGEN_VAL_STR << pca.eigenvalues;
fs << PCA_MEAN_STR << pca.mean;
fs.release();
} catch (...) {
spLoggerPrintError(GENERAL_ERROR_MSG, __FILE__, __func__, __LINE__);
throw Exception();
}
}
void sp::ImageProc::initPCAFromFile(const SPConfig config) {
if (!config) {
spLoggerPrintError(GENERAL_ERROR_MSG, __FILE__, __func__, __LINE__);
throw Exception();
}
char pcaFilename[STRING_LENGTH + 1] = { '\0' };
if (spConfigGetPCAPath(pcaFilename, config) != SP_CONFIG_SUCCESS) {
spLoggerPrintError(PCA_FILE_NOT_RESOLVED, __FILE__, __func__, __LINE__);
throw Exception();
}
FileStorage fs(pcaFilename, FileStorage::READ);
if (!fs.isOpened()) {
spLoggerPrintError(PCA_FILE_NOT_EXIST, __FILE__, __func__, __LINE__);
throw Exception();
}
fs[PCA_EIGEN_VEC_STR] >> pca.eigenvectors;
fs[PCA_EIGEN_VAL_STR] >> pca.eigenvalues;
fs[PCA_MEAN_STR] >> pca.mean;
fs.release();
}
sp::ImageProc::ImageProc(const SPConfig config) {
try {
if (!config) {
spLoggerPrintError(INVALID_ARG_ERROR, __FILE__, __func__, __LINE__);
throw Exception();
}
SP_CONFIG_MSG msg;
bool preprocMode = false;
initFromConfig(config);
if ((preprocMode = spConfigIsExtractionMode(config, &msg))) {
preprocess(config);
} else {
initPCAFromFile(config);
}
} catch (...) {
spLoggerPrintError(GENERAL_ERROR_MSG, __FILE__, __func__, __LINE__);
throw Exception();
}
}
SPPoint* sp::ImageProc::getImageFeatures(const char* imagePath, int index,
int* numOfFeats) {
vector<KeyPoint> keypoints;
Mat descriptor, img, points;
double* pcaSift = NULL;
char errorMSG[STRING_LENGTH * 2];
Ptr<xfeatures2d::SiftDescriptorExtractor> detector;
if (!imagePath || !numOfFeats) {
spLoggerPrintError(INVALID_ARG_ERROR, __FILE__, __func__, __LINE__);
return NULL;
}
img = imread(imagePath, IMREAD_GRAYSCALE);
if (img.empty()) {
sprintf(errorMSG, "%s %s", imagePath, IMAGE_NOT_EXIST_MSG);
spLoggerPrintError(errorMSG, __FILE__, __func__, __LINE__);
return NULL;
}
detector = xfeatures2d::SIFT::create(numOfFeatures);
detector->detect(img, keypoints);
detector->compute(img, keypoints, descriptor);
points = pca.project(descriptor);
pcaSift = (double*) malloc(sizeof(double) * pcaDim);
if (!pcaSift) {
spLoggerPrintError(ALLOC_ERROR_MSG, __FILE__, __func__, __LINE__);
return NULL;
}
*numOfFeats = points.rows;
SPPoint* resPoints = (SPPoint*) malloc(sizeof(*resPoints) * points.rows);
if (!resPoints) {
free(pcaSift);
spLoggerPrintError(ALLOC_ERROR_MSG, __FILE__, __func__, __LINE__);
return NULL;
}
for (int i = 0; i < points.rows; i++) {
for (int j = 0; j < points.cols; j++) {
pcaSift[j] = (double) points.at<float>(i, j);
}
resPoints[i] = spPointCreate(pcaSift, pcaDim, index);
}
free(pcaSift);
return resPoints;
}
void sp::ImageProc::showImage(const char* imgPath) {
if (minimalGui) {
Mat img = imread(imgPath, cv::IMREAD_COLOR);
if (img.empty()) {
spLoggerPrintWarning(IMAGE_NOT_EXIST_MSG, __FILE__, __func__,
__LINE__);
return;
}
imshow(windowName, img);
waitKey(0);
destroyAllWindows();
} else {
spLoggerPrintWarning(MINIMAL_GUI_NOT_SET_WARNING, __FILE__, __func__,
__LINE__);
}
}
SPImageProc.h
#ifndef SPIMAGEPROC_H_
#define SPIMAGEPROC_H_
#include <opencv2/core.hpp>
#include <opencv2/imgcodecs.hpp>
#include <vector>
extern "C" {
#include "SPConfig.h"
#include "SPPoint.h"
}
namespace sp {
/**
* A class which supports different image processing functionalites.
*/
class ImageProc {
private:
const char* windowName = "Software Project CBIR";
int pcaDim;
int numOfImages;
int numOfFeatures;
cv::PCA pca;
bool minimalGui;
void initFromConfig(const SPConfig);
void getImagesMat(std::vector<cv::Mat>&, const SPConfig);
void getFeatures(std::vector<cv::Mat>&,
cv::Mat&);
void preprocess(const SPConfig config);
void initPCAFromFile(const SPConfig config);
public:
/**
* Creates a new object for the purpose of image processing based
* on the configuration file.
* @param config - the configuration file from which the object is created
*/
ImageProc(const SPConfig config);
/**
* Returns an array of features for the image imagePath. All SPPoint elements
* will have the index given by index. The actual number of features extracted
* for this image will be stored in the pointer given by numOfFeats.
*
* @param imagePath - the target imagePath
* @param index - the index of the image in the database
* @param numOfFeats - a pointer in which the actual number of feats extracted
* will be stored
* @return
* An array of the actual features extracted. NULL is returned in case of
* an error.
*/
SPPoint* getImageFeatures(const char* imagePath,int index,int* numOfFeats);
/**
* Displays the image given by imagePath. Notice that this function works
* only in MinimalGUI mode (otherwise a warnning message is printed).
*
* @param imagePath - the path of the image to be displayed
*/
void showImage(const char* imagePath);
};
}
#endif