Android 利用OpenCV 的Stitcher做全景图片拼接（支持平面和球面）
2024-04-20 07:47:13
开发项目中遇到一个需求 就是用手机按照顺序拍几张图片 然后将图片拼接成一张全景的照片 百度了一下 看到OpenCV 的Stitcher工具支持全景图片拼接 于是研究了一下OpenCV 花了差不多一周时间才研究出来 呕心沥血的成果分享给大家 本篇文章将带给大家的知识点：
（1）.Windows上利用AndroidStudio进行ndk编译
（2）.使用静态库的方式导入OpenCV（生成的包更小，传统的导入方式需要java的moudle和so或者opencvmanager，生成的包非常臃肿）
（3）.在 C代码里将OpenCV的mat转换成bitmap 上传给java层
废话不多说 开始撸代码
GitHub 地址：https://github.com/yu12mang/OpenCvStitcher
1.准备工作
保证AndroidStudio安装了ndk
在AndroidStudio中新建一个空的android项目
下载Opencv-android-sdk:可以在opencv官网下载 不过下载速度是龟速 所以我建议去github上面下载：https://github.com/opencv/opencv/releases 最好下载3.2版本 因为我是在3.2版本上撸出来的 下载完成后放进项目中 如图：
2.在src/main目录下创建jni文件夹（可命名为cpp或者其他文件件名 jni是通用文件名），接下来编写ndk编译的必要文件Android.mk和Application.mk
Android.mk 代码如下：
LOCAL_PATH := $(call my-dir)include $(CLEAR_VARS)OpenCV_INSTALL_MODULES := on
OpenCV_CAMERA_MODULES := off#SHARED使用动态库 STATIC使用静态库
OPENCV_LIB_TYPE :=STATICifeq ("$(wildcard $(OPENCV_MK_PATH))","")
include ../../../../native/jni/OpenCV.mk
else
include $(OPENCV_MK_PATH)
endif#生成的动态库的名称
LOCAL_MODULE := Stitcher#需要链接的cpp文件
LOCAL_SRC_FILES := native-lib.cppLOCAL_LDLIBS += -lm -llog -landroid
LOCAL_LDFLAGS += -ljnigraphicsinclude $(BUILD_SHARED_LIBRARY)Application.mk
APP_STL := gnustl_static
APP_CPPFLAGS := -frtti -fexceptions
#需要编译的平台 我只需要arm64-v8a和armeabi-v7a 你可以自行设置
APP_ABI := arm64-v8a armeabi-v7a
APP_PLATFORM := android-83.编写app目录下的build.gradle 这是我的build.gradle 你需要将包名改成自己的 其他的你自己看着改：
apply plugin: 'com.android.application'android {compileSdkVersion 24buildToolsVersion '25.0.0'defaultConfig {applicationId "com.logan.opencvforandroid"minSdkVersion 15targetSdkVersion 24versionCode 1versionName "1.0"testInstrumentationRunner "android.support.test.runner.AndroidJUnitRunner"}buildTypes {release {minifyEnabled falseproguardFiles getDefaultProguardFile('proguard-android.txt'), 'proguard-rules.pro'}}sourceSets { main { jni.srcDirs = ['src/main/jni', 'src/main/jni/'] } }sourceSets.main.jni.srcDirs = []//禁止自带的ndk功能sourceSets.main.jniLibs.srcDirs = ['src/main/libs', 'src/main/jniLibs']//重定向so目录为src/main/libs和src/main/jniLibs，原来为src/main/jniLibstask ndkBuild(type: Exec, description: 'Compile JNI source with NDK') {Properties properties = new Properties()properties.load(project.rootProject.file('local.properties').newDataInputStream())def ndkDir = properties.getProperty('ndk.dir')if (org.apache.tools.ant.taskdefs.condition.Os.isFamily(org.apache.tools.ant.taskdefs.condition.Os.FAMILY_WINDOWS)) {commandLine "$ndkDir/ndk-build.cmd", '-C', file('src/main/jni').absolutePath} else {commandLine "$ndkDir/ndk-build", '-C', file('src/main/jni').absolutePath}}tasks.withType(JavaCompile) {compileTask -> compileTask.dependsOn ndkBuild}task ndkClean(type: Exec, description: 'Clean NDK Binaries') {Properties properties = new Properties()properties.load(project.rootProject.file('local.properties').newDataInputStream())def ndkDir = properties.getProperty('ndk.dir')if (org.apache.tools.ant.taskdefs.condition.Os.isFamily(org.apache.tools.ant.taskdefs.condition.Os.FAMILY_WINDOWS)) {commandLine "$ndkDir/ndk-build.cmd", 'clean', '-C', file('src/main/jni').absolutePath} else {commandLine "$ndkDir/ndk-build", 'clean', '-C', file('src/main/jni').absolutePath}}clean.dependsOn 'ndkClean'
}dependencies {compile fileTree(dir: 'libs', include: ['*.jar'])androidTestCompile('com.android.support.test.espresso:espresso-core:2.2.2', {exclude group: 'com.android.support', module: 'support-annotations'})testCompile 'junit:junit:4.12'compile 'com.android.support:appcompat-v7:24.2.0'compile 'com.android.support:design:24.2.0'compile 'com.android.support:cardview-v7:24.2.0'
}4.编写java层的jni接口 直接调用StitchImages函数即可
package com.fimi.gh2.tracker;import android.graphics.Bitmap;
import android.support.annotation.NonNull;import java.io.File;public class ImagesStitchUtil {public final static int OK = 0;public final static int ERR_NEED_MORE_IMGS = 1;public final static int ERR_HOMOGRAPHY_EST_FAIL = 2;public final static int ERR_CAMERA_PARAMS_ADJUST_FAIL = 3;static {System.loadLibrary("Stitcher");}public static void StitchImages(String paths[], @NonNull onStitchResultListener listener) {for (String path : paths) {if (!new File(path).exists()) {listener.onError("无法读取文件或文件不存在:" + path);return;}}int wh[] = stitchImages(paths);switch (wh[0]) {case OK: {Bitmap bitmap = Bitmap.createBitmap(wh[1], wh[2], Bitmap.Config.ARGB_8888);int result = getBitmap(bitmap);if (result == OK && bitmap != null){listener.onSuccess(bitmap);}else{listener.onError("图片合成失败");}}break;case ERR_NEED_MORE_IMGS: {listener.onError("需要更多图片");return;}case ERR_HOMOGRAPHY_EST_FAIL: {listener.onError("图片对应不上");return;}case ERR_CAMERA_PARAMS_ADJUST_FAIL: {listener.onError("图片参数处理失败");return;}}}private native static int[] stitchImages(String path[]);private native static void getMat(long mat);private native static int getBitmap(Bitmap bitmap);public interface onStitchResultListener {void onSuccess(Bitmap bitmap);void onError(String errorMsg);}}5.最后一步编写cpp文件 也是最重要的一步 这是我代码 你也可以根据需求自己进行修改 native-lib.cpp：
#include <jni.h>
#include <opencv2/opencv.hpp>
#include <opencv2/core/base.hpp>
#import "opencv2/stitching.hpp"
#import "opencv2/imgcodecs.hpp"#define BORDER_GRAY_LEVEL 0#include <android/log.h>
#include <android/bitmap.h>#define LOG_TAG "DDLog-jni"
#define LOGI(...) __android_log_print(ANDROID_LOG_INFO,LOG_TAG, __VA_ARGS__)
#define LOGD(...) __android_log_print(ANDROID_LOG_DEBUG,LOG_TAG, __VA_ARGS__)
#define LOGW(...) __android_log_print(ANDROID_LOG_WARN,LOG_TAG, __VA_ARGS__)
#define LOGE(...) __android_log_print(ANDROID_LOG_ERROR,LOG_TAG, __VA_ARGS__)
#define LOGF(...) __android_log_print(ANDROID_LOG_FATAL,LOG_TAG, __VA_ARGS__)
using namespace cv;
using namespace std;
char filepath1[100] = "/storage/emulated/0/panorama_stitched.jpg";cv::Mat finalMat;extern "C"
JNIEXPORT jintArray JNICALL
Java_com_fimi_gh2_tracker_ImagesStitchUtil_stitchImages(JNIEnv *env, jclass type,jobjectArray paths) {jstring jstr;jsize len = env->GetArrayLength(paths);std::vector<cv::Mat> mats;for (int i = 0; i < len; i++) {jstr = (jstring) env->GetObjectArrayElement(paths, i);const char *path = (char *) env->GetStringUTFChars(jstr, 0);LOGI("path %s", path);cv::Mat mat = cv::imread(path);
// cvtColor(mat, mat, CV_RGBA2RGB);mats.push_back(mat);}LOGI("开始拼接......");cv::Stitcher stitcher = cv::Stitcher::createDefault(false);//stitcher.setRegistrationResol(0.6);// stitcher.setWaveCorrection(false);/*=match_conf默认是0.65，我选0.8，选太大了就没特征点啦,0.8都失败了*/detail::BestOf2NearestMatcher *matcher = new detail::BestOf2NearestMatcher(false, 0.5f);stitcher.setFeaturesMatcher(matcher);stitcher.setBundleAdjuster(new detail::BundleAdjusterRay());stitcher.setSeamFinder(new detail::NoSeamFinder);stitcher.setExposureCompensator(new detail::NoExposureCompensator());//曝光补偿stitcher.setBlender(new detail::FeatherBlender());Stitcher::Status state = stitcher.stitch(mats, finalMat);//此时finalMat是bgr类型LOGI("拼接结果: %d", state);
// finalMat = clipping(finalMat);jintArray jint_arr = env->NewIntArray(3);jint *elems = env->GetIntArrayElements(jint_arr, NULL);elems[0] = state;//状态码elems[1] = finalMat.cols;//宽elems[2] = finalMat.rows;//高if (state == cv::Stitcher::OK){LOGI("拼接成功: OK");}else{LOGI("拼接失败:fail code %d",state);}//同步env->ReleaseIntArrayElements(jint_arr, elems, 0);
// bool isSave = cv::imwrite(filepath1, finalMat);
// LOGI("是否存储成功:%d",isSave);return jint_arr;}extern "C"
JNIEXPORT void JNICALL
Java_com_fimi_gh2_tracker_ImagesStitchUtil_getMat(JNIEnv *env, jclass type, jlong mat) {LOGI("开始获取mat...");Mat *res = (Mat *) mat;res->create(finalMat.rows, finalMat.cols, finalMat.type());memcpy(res->data, finalMat.data, finalMat.rows * finalMat.step);LOGI("获取成功");}//将mat转化成bitmap
void MatToBitmap(JNIEnv *env, Mat &mat, jobject &bitmap, jboolean needPremultiplyAlpha) {AndroidBitmapInfo info;void *pixels = 0;Mat &src = mat;try {LOGD("nMatToBitmap");CV_Assert(AndroidBitmap_getInfo(env, bitmap, &info) >= 0);LOGD("nMatToBitmap1");CV_Assert(info.format == ANDROID_BITMAP_FORMAT_RGBA_8888 ||info.format == ANDROID_BITMAP_FORMAT_RGB_565);LOGD("nMatToBitmap2 :%d : %d :%d", src.dims, src.rows, src.cols);CV_Assert(src.dims == 2 && info.height == (uint32_t) src.rows &&info.width == (uint32_t) src.cols);LOGD("nMatToBitmap3");CV_Assert(src.type() == CV_8UC1 || src.type() == CV_8UC3 || src.type() == CV_8UC4);LOGD("nMatToBitmap4");CV_Assert(AndroidBitmap_lockPixels(env, bitmap, &pixels) >= 0);LOGD("nMatToBitmap5");CV_Assert(pixels);LOGD("nMatToBitmap6");if (info.format == ANDROID_BITMAP_FORMAT_RGBA_8888) {Mat tmp(info.height, info.width, CV_8UC4, pixels);
// Mat tmp(info.height, info.width, CV_8UC3, pixels);if (src.type() == CV_8UC1) {LOGD("nMatToBitmap: CV_8UC1 -> RGBA_8888");cvtColor(src, tmp, COLOR_GRAY2RGBA);} else if (src.type() == CV_8UC3) {LOGD("nMatToBitmap: CV_8UC3 -> RGBA_8888");
// cvtColor(src, tmp, COLOR_RGB2RGBA);
// cvtColor(src, tmp, COLOR_RGB2RGBA);cvtColor(src, tmp, COLOR_BGR2RGBA);
// src.copyTo(tmp);} else if (src.type() == CV_8UC4) {LOGD("nMatToBitmap: CV_8UC4 -> RGBA_8888");if (needPremultiplyAlpha)cvtColor(src, tmp, COLOR_RGBA2mRGBA);elsesrc.copyTo(tmp);}} else {// info.format == ANDROID_BITMAP_FORMAT_RGB_565Mat tmp(info.height, info.width, CV_8UC2, pixels);if (src.type() == CV_8UC1) {LOGD("nMatToBitmap: CV_8UC1 -> RGB_565");cvtColor(src, tmp, COLOR_GRAY2BGR565);} else if (src.type() == CV_8UC3) {LOGD("nMatToBitmap: CV_8UC3 -> RGB_565");
// src.copyTo(tmp);cvtColor(src, tmp, COLOR_RGB2BGR565);} else if (src.type() == CV_8UC4) {LOGD("nMatToBitmap: CV_8UC4 -> RGB_565");cvtColor(src, tmp, COLOR_RGBA2BGR565);}}AndroidBitmap_unlockPixels(env, bitmap);return;} catch (const cv::Exception &e) {AndroidBitmap_unlockPixels(env, bitmap);LOGE("nMatToBitmap catched cv::Exception: %s", e.what());jclass je = env->FindClass("org/opencv/core/CvException");if (!je) je = env->FindClass("java/lang/Exception");env->ThrowNew(je, e.what());return;} catch (...) {AndroidBitmap_unlockPixels(env, bitmap);LOGE("nMatToBitmap catched unknown exception (...)");jclass je = env->FindClass("java/lang/Exception");env->ThrowNew(je, "Unknown exception in JNI code {nMatToBitmap}");return;}
}extern "C"
JNIEXPORT jint JNICALL
Java_com_fimi_gh2_tracker_ImagesStitchUtil_getBitmap(JNIEnv *env, jclass type, jobject bitmap) {if (finalMat.dims != 2){return -1;}MatToBitmap(env,finalMat,bitmap,false);return 0;}好了 点击编译 不出意外的话会生成一个Stitcher.so的文件 如图所示：
大功告成 ！！！ 是不是很简单
另外如果你觉得拼接时间过长可以调整native-lib.cpp中的该部位：
具体调整方法 支持球面全景图片拼接：
//false是禁止gpu加速 可改成trueStitcher stitcher = Stitcher::createDefault(false);stitcher.setRegistrationResol(0.6);//为了加速，我选0.1,默认是0.6,最大值1最慢，此方法用于特征点检测阶段，如果找不到特征点，调高吧//stitcher.setSeamEstimationResol(0.1);//默认是0.1//stitcher.setCompositingResol(-1);//默认是-1，用于特征点检测阶段，找不到特征点的话，改-1stitcher.setPanoConfidenceThresh(1);//默认是1,见过有设0.6和0.4的stitcher.setWaveCorrection(false);//默认是true，为加速选false，表示跳过WaveCorrection步骤//stitcher.setWaveCorrectKind(detail::WAVE_CORRECT_HORIZ);//还可以选detail::WAVE_CORRECT_VERT ,波段修正(wave correction)功能（水平方向/垂直方向修正）。因为setWaveCorrection设的false，此语句没用//找特征点surf算法，此算法计算量大,但对刚体运动、缩放、环境影响等情况下较为稳定detail::SurfFeaturesFinder *featureFinder = new detail::SurfFeaturesFinder();stitcher.setFeaturesFinder(featureFinder);//找特征点ORB算法,但是发现草地这组图，这个算法不能完成拼接//detail::OrbFeaturesFinder *featureFinder = new detail::OrbFeaturesFinder();//stitcher.setFeaturesFinder(featureFinder);//Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf.detail::BestOf2NearestMatcher *matcher = new detail::BestOf2NearestMatcher(false, 0.5f/*=match_conf默认是0.65，我选0.8，选太大了就没特征点啦,0.8都失败了*/);stitcher.setFeaturesMatcher(matcher);// Rotation Estimation,It takes features of all images, pairwise matches between all images and estimates rotations of all cameras.//Implementation of the camera parameters refinement algorithm which minimizes sum of the distances between the rays passing through the camera center and a feature,这个耗时短stitcher.setBundleAdjuster(new detail::BundleAdjusterRay());//Implementation of the camera parameters refinement algorithm which minimizes sum of the reprojection error squares.//stitcher.setBundleAdjuster(new detail::BundleAdjusterReproj());//Seam Estimation//Minimum graph cut-based seam estimator//stitcher.setSeamFinder(new detail::GraphCutSeamFinder(detail::GraphCutSeamFinderBase::COST_COLOR));//默认就是这个//stitcher.setSeamFinder(new detail::GraphCutSeamFinder(detail::GraphCutSeamFinderBase::COST_COLOR_GRAD));//GraphCutSeamFinder的第二种形式//啥SeamFinder也不用，Stub seam estimator which does nothing.stitcher.setSeamFinder(new detail::NoSeamFinder);//Voronoi diagram-based seam estimator.//stitcher.setSeamFinder(new detail::VoronoiSeamFinder);//exposure compensators曝光补偿//stitcher.setExposureCompensator(new detail::BlocksGainCompensator());//默认的就是这个//不要曝光补偿stitcher.setExposureCompensator(new detail::NoExposureCompensator());//Exposure compensator which tries to remove exposure related artifacts by adjusting image intensities//stitcher.setExposureCompensator(new detail::detail::GainCompensator());//Exposure compensator which tries to remove exposure related artifacts by adjusting image block intensities //stitcher.setExposureCompensator(new detail::detail::BlocksGainCompensator()); //Image Blenders//Blender which uses multi-band blending algorithm stitcher.setBlender(new detail::MultiBandBlender(try_use_gpu));//默认的是这个//Simple blender which mixes images at its borders//stitcher.setBlender(new detail::FeatherBlender());//这个简单，耗时少//柱面？球面OR平面？默认为球面//PlaneWarper* cw = new PlaneWarper();//SphericalWarper* cw = new SphericalWarper();//CylindricalWarper* cw = new CylindricalWarper();//stitcher.setWarper(cw);Stitcher::Status status = stitcher.estimateTransform(imgs);if (status != Stitcher::OK){cout << "Can't stitch images, error code = " << int(status) << endl;return -1;}status = stitcher.composePanorama(pano);if (status != Stitcher::OK){cout << "Can't stitch images, error code = " << int(status) << endl;return -1;}看到这里了给个赞鼓励鼓励吧 或者关注一波 我会陆续将我劳动成果分享给大家！
感谢拨冗翻阅拙作,敬请斧正.
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