安卓上使用FFMPEG解码视频并处理
【嵌牛导读】：安卓上OPENCV是经过剪切的，部分功能如VideoCapture不能使用。本文使用首先将FFMPEG封装呈.so库，然后使用JNI调用C语言实现了视频的解码处理。
【嵌牛鼻子】：FFMPEG android JNI 视频解码
【嵌牛提问】：安卓上使用FFMPEG进行视频解码
【嵌牛正文】：
JNI调用NATIVE的FFMPEG
Android的opencv不支持videocapture解码视频，是因为Android上的opencv没有集成ffmpeg这个解码的库。所以需要自己把ffmpeg的源码打包成.so文件，在Android中使用JNI调用.so库，然后再c++中读取手机中的视频解码以后转为一个一个的MAT矩阵，以方便后期处理。下面是步骤
一． 将ffmpeg源码编译成.so库。我使用的是别人编译好的库。具体编译方法看这个网页。https://www.2cto.com/kf/201804/739639.html
二． 编写NATIVE函数
1.新建一个类FFmpegDecode的类，写两个native函数
2.使用Android studio上的终端。转到app\build\intermediates\classes\debug文件夹下
3.生成java的native函数所对应的c++函数头文件
4.然后在app\build\intermediates\classes\debug目录下找到生成的.h头文件
三．安卓上配置NDK。
1修改工程下的gradle.properties
修改app下的build.gradle
sourceSets.main.jni.srcDirs= []
sourceSets.main.jniLibs.srcDirs = ['src/main/libs','src/main/jniLibs']
//禁止自带的ndk功能task 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
}
}
defaultConfig {
multiDexEnabled true
}
clean.dependsOn 'ndkClean'
2修改工程下的local.properties
3在app/src/main下新建jni文件夹。在jni文件夹下新建两个文件Android.mk和Application.mk。
4.将刚才生成的头文件复制到jni文件夹下。同时新建对应的.cpp文件。
5.在jni文件夹下面新建一个include文件夹，把ffmpeg的源码拷贝到该文件夹下
6.将之前编译好的.so文件放到jni文件夹下面
7.编写Android.mk文件
LOCAL_PATH := $(call my-dir)
#ffmpeg lib
include $(CLEAR_VARS)
LOCAL_MODULE := avcodec
LOCAL_SRC_FILES := libavcodec-56.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := avdevice
LOCAL_SRC_FILES := libavdevice-56.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := avfilter
LOCAL_SRC_FILES := libavfilter-5.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := avformat
LOCAL_SRC_FILES := libavformat-56.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := avutil
LOCAL_SRC_FILES := libavutil-54.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := postproc
LOCAL_SRC_FILES := libpostproc-53.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := swresample
LOCAL_SRC_FILES := libswresample-1.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := swscale
LOCAL_SRC_FILES := libswscale-3.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := yuv
LOCAL_SRC_FILES := libyuv.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
LOCAL_MODULE := opencv_java
LOCAL_SRC_FILES := libopencv_java.so
include $(PREBUILT_SHARED_LIBRARY)
include $(CLEAR_VARS)
#OPENCV_CAMERA_MODULES:=on
#OPENCV_INSTALL_MODULES:=off
include ..\..\..\..\native\jni\OpenCV.mk
LOCAL_MODULE :=ffmdecode
LOCAL_SRC_FILES :=com_tinymonster_ffmpegstudy1_FFmpegDecode.cpp
LOCAL_C_INCLUDES += $(LOCAL_PATH)/include/ffmpeg
LOCAL_C_INCLUDES += $(LOCAL_PATH)/include/libyuv
LOCAL_LDLIBS += -llog -ldl
LOCAL_SHARED_LIBRARIES := avcodec avdevice avfilter avformat avutil postprocswresample swscale yuv
include $(BUILD_SHARED_LIBRARY)
8.编写Application文件
APP_STL := gnustl_static
APP_CPPFLAGS := -frtti -fexceptions
APP_ABI := armeabi
9.将opencv的native库放到工程目录下。
10.点击屏幕右侧的gradle中的ndkbuild。
11.然后会看到jni下面生成了libs和obj两个文件夹。这两个文件夹下面生成的是对应的.so库
12.编写c代码，读取手机视频，解码视频，并转为OPENCV的MAT。
#define LOGI(FORMAT,...) __android_log_print(ANDROID_LOG_INFO,"ccj",FORMAT,##__VA_ARGS__);
#define LOGE(FORMAT,...) __android_log_print(ANDROID_LOG_ERROR,"ccj",FORMAT,##__VA_ARGS__);
using namespace cv;
JNIEXPORT jint JNICALLJava_com_tinymonster_ffmpegstudy1_FFmpegDecode_DecodeFile
(JNIEnv* env, jclassobj, jstring input_){
LOGE("%s","1");
const
char *filename= env->GetStringUTFChars(input_, 0);
AVCodec*pCodec; //
解码器指针
AVCodecContext* pCodecCtx; //ffmpeg解码类的类成员
AVFrame* pAvFrame; //多媒体帧，保存解码后的数据帧
AVFormatContext* pFormatCtx; //保存视频流的信息
av_register_all(); //注册库中所有可用的文件格式和编码器
pFormatCtx= avformat_alloc_context();
if(avformat_open_input(&pFormatCtx, filename, NULL, NULL) != 0) { //检查文件头部
LOGE("%s","Can'tfind the stream!");
}
if(avformat_find_stream_info(pFormatCtx,NULL) < 0) { //查找流信息
LOGE("%s","Can'tfind the stream information !");
}
intvideoindex= -1;
for(int i=0; i< pFormatCtx->nb_streams; ++i) //遍历各个流，找到第一个视频流,并记录该流的编码信息
{
if (pFormatCtx->streams[i]->codec->codec_type== AVMEDIA_TYPE_VIDEO) {
videoindex= I;
break;
}
}
if(videoindex==
-1) {
LOGE("%s","Don'tfind a video stream !");
return 1;
}
pCodecCtx= pFormatCtx->streams[videoindex]->codec; //得到一个指向视频流的上下文指针
pCodec= avcodec_find_decoder(pCodecCtx->codec_id); //到该格式的解码器
if (pCodec== NULL) {
LOGE("%s","Cant'tfind the decoder !");
return 2;
}
if(avcodec_open2(pCodecCtx,pCodec,NULL) < 0) { //打开解码器
LOGE("%s","Can't open the decoder !");
return 3;
}
pAvFrame= avcodec_alloc_frame(); //分配帧存储空间
AVFrame* pFrameBGR= avcodec_alloc_frame(); //存储解码后转换的RGB数据
//
保存BGR，opencv中是按BGR来保存的
int size=avpicture_get_size(AV_PIX_FMT_BGR24, pCodecCtx->width, pCodecCtx->height);
uint8_t*out_buffer= (uint8_t*)av_malloc(size);
avpicture_fill((AVPicture*)pFrameBGR, out_buffer, AV_PIX_FMT_BGR24, pCodecCtx->width, pCodecCtx->height);
AVPacket* packet= (AVPacket*)malloc(sizeof(AVPacket));
LOGI("视频的文件格式：%s",pFormatCtx->iformat->name);
LOGI("视频时长：%d", (pFormatCtx->duration)/1000000);
LOGI("视频的宽高：%d,%d",pCodecCtx->width,pCodecCtx->height);
LOGI("解码器的名称：%s",pCodec->name);
struct SwsContext*img_convert_ctx;
img_convert_ctx= sws_getContext(pCodecCtx->width, pCodecCtx->height, pCodecCtx->pix_fmt, pCodecCtx->width, pCodecCtx->height, AV_PIX_FMT_BGR24, SWS_BICUBIC, NULL, NULL, NULL);
//opencv
cv::Mat pCvMat;
pCvMat.create(cv::Size(pCodecCtx->width, pCodecCtx->height), CV_8UC3);
int ret;
int got_picture;
//读取每一帧
int frame_count= 0;
while (av_read_frame(pFormatCtx, packet) >= 0)
{
if(packet->stream_index==videoindex)
{
ret= avcodec_decode_video2(pCodecCtx, pAvFrame, &got_picture, packet);
if(ret< 0)
{
printf("Decode Error.（解码错误）\n");
return 4;
}
LOGI("解码第%d帧",frame_count);
if (got_picture)
{
//YUV to RGB
sws_scale(img_convert_ctx, (const uint8_t* const*)pAvFrame->data, pAvFrame->linesize, 0, pCodecCtx->height, pFrameBGR->data, pFrameBGR->linesize);
memcpy(pCvMat.data, out_buffer, size);//拷贝
frame_count++;
LOGI("解码第%d帧",frame_count);
}
}
av_free_packet(packet);
}
av_free(out_buffer);
av_free(pFrameBGR);
av_free(pAvFrame);
avcodec_close(pCodecCtx);
avformat_close_input(&pFormatCtx);
sws_freeContext(img_convert_ctx);
retur 0;
}
13.这样就可以在JAVA代码中调用C++代码处理视频了
