android jni中将大数据回调到java层的时候用法,比如视频流，音频流等，图片流等比如我用ffmpeg解码好视频流，想送到java层使用opengGL进行显示，opencv进行人脸识别等等

java层

//将解码好后的视频流回调回来    public void CallBack_VideoDecodeData(Object object, int len) {        //这里强制转换为ByteBuffer即可        ByteBuffer buffer = (ByteBuffer) object;        if (videoDecodeSteamCallBack != null) {            videoDecodeSteamCallBack.onVideoDecodeData(buffer, len);        }    }

jni层

g_CallBack_VideoDecodeData = (*env)->GetMethodID(env,clazz, "CallBack_VideoDecodeData", "(Ljava/lang/Object;I)V");

/*** 直播的时候视频回调,这个是解码好后的视频*/int RT_VideoDecodeDataCallBack(uint8_t *data,int len){    JNIEnv *env;    int cRet= RT_GetEnv(&env);    if(cRet==-1){        return 0;    }    if(g_CallBack_VideoDecodeData == NULL){        LOGE("[%s:%d]g_CallBack_VideoDecodeData=NULL!\n",__FUNCTION__,__LINE__);        return 0;    }#if 0    /*    使用这种方式，效率很低，并且内存抖动非常大    */    jbyteArray bytes = 0;    bytes = (*env)->NewByteArray(env, len);    if (bytes != NULL) {        (*env)->SetByteArrayRegion(env, bytes, 0, len,(jbyte *)data);    }    (*env)->CallVoidMethod(env,g_callBackHandle.callBackObj,g_CallBack_VideoDecodeData,bytes,len);    (*env)->DeleteLocalRef (env,bytes);#else    /*    使用这种方式回调回去，效率会高很多，少了内存的拷贝，使用上面这种方式是要经过内存拷贝的    */    jobject _buf = (jobject)0;    _buf = (*env)->NewDirectByteBuffer(env,data,len);    (*env)->CallVoidMethod(env,g_callBackHandle.callBackObj,g_CallBack_VideoDecodeData,_buf ,len);    (*env)->DeleteLocalRef (env,_buf);#endif    //如果是绑定的方式，要解绑    if(cRet){        (*g_callBackHandle.javaVM)->DetachCurrentThread(g_callBackHandle.javaVM);    }    return 0;}

android openGL glMapBufferRange源码也是这样用的

// C function GLvoid * glMapBufferRange ( GLenum target, GLintptr offset, GLsizeiptr length, GLbitfield access )    public static native java.nio.Buffer glMapBufferRange(        int target,        int offset,        int length,        int access    );

对应的jni层

/* GLvoid * glMapBufferRange ( GLenum target, GLintptr offset, GLsizeiptr length, GLbitfield access ) */static jobjectandroid_glMapBufferRange__IIII(JNIEnv *_env, jobject _this, jint target, jint offset, jint length, jint access) {   GLvoid* _p = glMapBufferRange((GLenum)target,           (GLintptr)offset, (GLsizeiptr)length, (GLbitfield)access);   jobject _buf = (jobject)0;    if (_p) {        _buf = _env->NewDirectByteBuffer(_p, length);    }    return _buf;}

唯一区别的是它不需要手动的释放，因为它是以返回值的方式返回，会由java虚拟机自动回收，如果像我这样的写的话，必须要调用(*env)->DeleteLocalRef (env,_buf);要不很快就会

A/art: art/runtime/indirect_reference_table.cc:115] JNI ERROR (app bug): local reference table overflow (max=512) A/art: art/runtime/indirect_reference_table.cc:115] local reference table dump: A/art: art/runtime/indirect_reference_table.cc:115]   Last 10 entries (of 512): A/art: art/runtime/indirect_reference_table.cc:115]       511: 0x12e09500 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       510: 0x12e094c0 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       509: 0x12e09480 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       508: 0x12e09440 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       507: 0x12e09400 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       506: 0x12e093c0 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       505: 0x12e09380 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       504: 0x12e09340 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       503: 0x12e09300 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]       502: 0x12e092c0 java.nio.DirectByteBuffer A/art: art/runtime/indirect_reference_table.cc:115]   Summary: A/art: art/runtime/indirect_reference_table.cc:115]       512 of java.nio.DirectByteBuffer (512 unique instances)

android jni中将大数据回调到java层的时候用法,比如视频流，音频流等，图片流等比如我用ffmpeg解码好视频流，想送到java层使用opengGL进行显示，opencv进行人脸识别等等

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android jni中将大数据回调到java层的时候用法,比如视频流，音频流等，图片流等 比如我用ffmpeg解码好视频流，想送到java层使用opengGL进行显示，opencv进行人脸识别等等

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随机推荐

android jni中将大数据回调到java层的时候用法,比如视频流，音频流等，图片流等比如我用ffmpeg解码好视频流，想送到java层使用opengGL进行显示，opencv进行人脸识别等等