详解HDI Implementation中的预览流程

作者：润和软件 郭新星

相机作为智能手机上少有的成长空间不错的，能够做出差异化的功能，每年都能成为各大Android手机厂商争相宣传的亮点。众所周知Android采用Linux 作为其内核，而Linux采用的开源协议具有传染性[1]，导致Android HAL[2]成为了手机厂商们竞争的重要战场。随着OpenHarmony 3.1[3]的发布，相机模块也逐渐完善起来，目前提供了基础预览和拍照的能力。OpenHarmony中，相机用户态驱动框架承担了和Android Camera HAL一样的角色，这部分位于OpenHarmony的HDF[4]中，对上实现相机HDI[5]接口，对下实现相机Pipeline模型，管理相机各个硬件设备。

相机用户态驱动框架（下图的CameraHost 部分）总体可以分为三层，HDI实现层，实现相机标准南向接口；框架层，对接HDI实现层的控制、流的转发，实现数据通路的搭建、管理相机各个硬件设备等功能；适配层，屏蔽底层芯片和OS差异，支持多平台适配。

模块介绍
HDI Implementation：对上实现HDI接口，向下调用框架层的接口，完成HDI接口任务的转发。

Buffer Manager ：屏蔽不同内存管理的差异，为子系统提供统一的操作接口，同时提供buffer轮转的功能。

Pipeline Core ：解析HCS配置完成pipeline的搭建，调度pipeline中的各个node完成流的处理
Device Manager：通过调用底层硬件适配层接口，实现查询控制底层设备、枚举监听底层设备的功能。

Platform Adaption ：屏蔽硬件差异，为Device Manager提供统一的操作底层硬件的能力。

目录结构

Shelldrivers/peripheral/camera|-- README_zh.md|-- bundle.json|-- figures|  `-- logic-view-of-modules-related-to-this-repository_zh.png|-- hal|  |-- BUILD.gn|  |-- adapter|  |-- buffer_manager|  |-- camera.gni|  |-- device_manager|  |-- hdi_impl|  |-- include|  |-- init|  |-- pipeline_core|  |-- test|  `-- utils|-- hal_c|  |-- BUILD.gn|  |-- camera.gni|  |-- hdi_cif|  `-- include`-- inteRFaces  |-- hdi_ipc  |-- hdi_passthrough  `-- include

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HDI Implementation中的预览流程

接下来我们通过已经发布的OpenHarmony 3.1开源代码，来看看预览是怎么完成的吧

drivers/peripheral/camera/hal/test/v4l2/src /preview_test.cpp存放了针对v4l2的预览测试代码，入口如下：

C++TEST_F(UtestPreviewTest, camera_preview_0001){  std::cout << "==========[test log] Preview stream, expected success." << std::endl;  // Get the stream manager  display_->AchieveStreamOperator(); // 获取stream operator  // start stream  display_->intents = {Camera::PREVIEW}; // 预览流  display_->StartStream(display_->intents); // 起流  // Get preview  display_->StartCapture(display_->streamId_preview, display_->captureId_preview, false, true);  // release stream  display_->captureIds = {display_->captureId_preview};  display_->streamIds = {display_->streamId_preview};  display_->StopStream(display_->captureIds, display_->streamIds);}

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先获取stream operator实例

C++void testdisplay::achievestreamoperator(){  // create and get streamoperator information  std::shared_ptr streamoperatorcallback =    std::make_shared();  rc = cameradevice->getstreamoperator(streamoperatorcallback, streamoperator);     // ........}

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通过前文的streamOperator创建流

C++void TestDisplay::StartStream(std::vector intents){  // ..............................  for (auto& intent : intents) {    if (intent == 0) {      std::shared_ptr producer = IBufferProducer::CreateBufferQueue();      producer->SetQueueSize(8); // 创建buffer的生产端，并和相应的流进行绑定      auto callback = [this](std::shared_ptr Prebuffer) {        BufferCallback(Prebuffer, preview_mode);        return;      };      producer->SetCallback(callback);      streamInfo->streamId_ = streamId_preview;      streamInfo->width_ = 640; // 640:picture width      streamInfo->height_ = 480; // 480:picture height      streamInfo->format_ = CAMERA_FORMAT_YUYV_422_PKG;      streamInfo->datasapce_ = 8; // 8:picture datasapce      streamInfo->intent_ = intent;      streamInfo->tunneledMode_ = 5; // 5:tunnel mode      streamInfo->bufferQueue_ = producer;      streamInfos.push_back(streamInfo);    } else if (intent == 1) {   // .......................  }  rc = streamOperator->CreateStreams(streamInfos); // 创建流  // ................................  rc = streamOperator->CommitStreams(Camera::NORMAL, ability); // 提交流  // .................................}

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下面我们正式进入到hal的源代码中看看是怎么创建流的吧

C++CamRetCode StreamOperator::CreateStreams(const std::vector<std::shared_ptr>& streamInfos){ // .....  for (auto it : streamInfos) {//....    std::shared_ptr stream = StreamFactory::Instance().CreateShared(      IStream::g_availableStreamType[it->intent_], it->streamId_, it->intent_, pipelineCore_, messenger_); // 创建流实例// ...    StreamConfiguration scg;    scg.id = it->streamId_;    scg.type = it->intent_;    scg.width = it->width_;    scg.height = it->height_;    PixelFormat pf = static_cast(it->format_);    scg.format = BufferAdapter::PixelFormatToCameraFormat(pf);    scg.dataspace = it->datasapce_;    scg.tunnelMode = it->tunneledMode_;    scg.minFrameDuration = it->minFrameDuration_;    scg.encodeType = it->encodeType_;
    RetCode rc = stream->ConfigStream(scg); // 依据上文的流信息配置流// ...    if (it->bufferQueue_ != nullptr) { // 绑定前文的生产端      auto tunnel = std::make_shared();      CHECK_IF_PTR_NULL_RETURN_VALUE(tunnel, INSUFFICIENT_RESOURCES);      RetCode rc = tunnel->AttachBufferQueue(it->bufferQueue_);      CHECK_IF_NOT_EQUAL_RETURN_VALUE(rc, RC_OK, INVALID_ARGUMENT);      if (stream->AttachStreamTunnel(tunnel) != RC_OK) {        CAMERA_LOGE("attach buffer queue to stream [id = %{public}d] failed", it->streamId_);        return INVALID_ARGUMENT;      }    }    {      std::lock_guard<std::mutex> l(streamLock_);      streamMap_[stream->GetStreamId()] = stream; // 保存流实例    }// ...}

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从上面可以看出，消费端传递到了hal，那必然是由hal从bufferproducer获取buffer，并触发预览的启动流程。那看看AttachStreamTunnel 的实现吧

C++RetCode StreamBase::AttachStreamTunnel(std::shared_ptr& tunnel){  if (state_ == STREAM_STATE_BUSY || state_ == STREAM_STATE_OFFLINE) {    return RC_ERROR;  }
  tunnel_ = tunnel; // 绑定生产端  CHECK_IF_PTR_NULL_RETURN_VALUE(tunnel_, RC_ERROR);  tunnel_->SetBufferCount(GetBufferCount()); // 配置轮转的buffer个数  TunnelConfig config = {(uint32_t)streamConfig_.width, (uint32_t)streamConfig_.height,    (uint32_t)streamConfig_.format, streamConfig_.usage};  tunnel_->Config(config);
  streamConfig_.tunnelMode = true;  return RC_OK;}

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CreateStream之后便是CommitStream，这里的CommitStream 做了些什么事情呢，我们接着往下看

C++CamRetCode StreamOperator::CommitStreams(OperationMode mode,                     const std::shared_ptr& modeSetting){// ......  std::vector configs = {};  {    std::lock_guard<std::mutex> l(streamLock_);    for (auto it : streamMap_) { // 获取流的配置，前文CreateStrea时保存的流      configs.emplace_back(it.second->GetStreamAttribute());    }  } // 检查流是否被支持  DynamicStreamSwitchMode method = streamPipeline_->CheckStreamsSupported(mode, modeSetting, configs);  if (method == DYNAMIC_STREAM_SWITCH_NOT_SUPPORT) {    return INVALID_ARGUMENT;  }  if (method == DYNAMIC_STREAM_SWITCH_NEED_INNER_RESTART) {    std::lock_guard<std::mutex> l(streamLock_);    for (auto it : streamMap_) {      it.second->StopStream();// 如果流被支持，但需要内部重启，这里先停流    }  }  {    std::lock_guard<std::mutex> l(streamLock_);    for (auto it : streamMap_) {      if (it.second->CommitStream() != RC_OK) { // 真正的 CommitStream，下面再细说        CAMERA_LOGE("commit stream [id = %{public}d] failed.", it.first);        return DEVICE_ERROR;      }    }  }  RetCode rc = streamPipeline_->PreConfig(modeSetting); // 把模式传入进行预配置  if (rc != RC_OK) {    CAMERA_LOGE("prepare mode settings failed");    return DEVICE_ERROR;  }  rc = streamPipeline_->CreatePipeline(mode);// 创建pipeline  if (rc != RC_OK) {    CAMERA_LOGE("create pipeline failed.");    return INVALID_ARGUMENT;  }
  DFX_LOCAL_HITRACE_END;  return NO_ERROR;}

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C++RetCode StreamBase::CommitStream(){// ...  hostStreamMgr_ = pipelineCore_->GetHostStreamMgr(); //从pipelinecore获取hoststreamanager  CHECK_IF_PTR_NULL_RETURN_VALUE(hostStreamMgr_, RC_ERROR);// ...    info.bufferPoolId_ = poolId_;    info.bufferCount_ = GetBufferCount();  // 初始化 bufferpool    RetCode rc = bufferPool_->Init(streamConfig_.width, streamConfig_.height, streamConfig_.usage,                    streamConfig_.format, GetBufferCount(), CAMERA_BUFFER_SOURCE_TYPE_EXTERNAL);    if (rc != RC_OK) {      CAMERA_LOGE("stream [id:%{public}d] initialize buffer pool failed.", streamId_);      return RC_ERROR;    }  }// stream传递到pipelinecore 并进行绑定  RetCode rc = hostStreamMgr_->CreateHostStream(info, [this](std::shared_ptr buffer) {    HandleResult(buffer);    return;  });// ....  return RC_OK;}

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CreateStream 和CommitStream结束之后便是Capture，这里包含了起流的动作，关键实现如下

C++CamRetCode StreamOperator::Capture(int captureId, const std::shared_ptr& captureInfo, bool isStreaming){// ...//  captureId 捕获请求的id; captureInfo 预览/拍照/录像的参数；isStreaming 连续捕获还是单次捕获（拍照）  CaptureSetting setting = captureInfo->captureSetting_;  auto request =    std::make_shared(captureId, captureInfo->streamIds_.size(), setting,                     captureInfo->enableShutterCallback_, isStreaming);  for (auto id : captureInfo->streamIds_) {    // 创建捕获请求，并传递给前文创建的流    RetCode rc = streamMap_[id]->AddRequest(request);    if (rc != RC_OK) {      return DEVICE_ERROR;    }  }// ...}

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从上面的代码可知预览、拍照、录像都是通过捕获请求触发，单次拍照则为单次捕获请求，预览和录像则是连续捕获请求。

C++RetCode StreamBase::AddRequest(std::shared_ptr& request){  CHECK_IF_PTR_NULL_RETURN_VALUE(request, RC_ERROR);  request->AddOwner(shared_from_this());
  request->SetFirstRequest(false);  if (isFirstRequest) {    RetCode rc = StartStream(); // 起流    if (rc != RC_OK) {      CAMERA_LOGE("start stream [id:%{public}d] failed", streamId_);      return RC_ERROR;    }    request->SetFirstRequest(true);    isFirstRequest = false;  }  {    std::unique_lock<std::mutex> l(wtLock_);    waitingList_.emplace_back(request); // 捕获请求添加到waitingList    cv_.notify_one();  }  return RC_OK;}

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看看StreamStream是怎么实现的吧

C++RetCode StreamBase::StartStream(){// ...  RetCode rc = pipeline_->Prepare({streamId_}); // pipeline先完成一些准备工作// ...
  state_ = STREAM_STATE_BUSY;  std::string threadName =    g_availableStreamType[static_cast(streamType_)] + "#" + std::to_string(streamId_);  handler_ = std::make_unique<std::thread>([this, &threadName] {// 创建轮转线程    prctl(PR_SET_NAME, threadName.c_str());    while (state_ == STREAM_STATE_BUSY) {      HandleRequest(); // 处理捕获请求    }  });// ...  rc = pipeline_->Start({streamId_}); // 通知pipeline和底层硬件可以开始出帧了// ...  return RC_OK;}

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C++void StreamBase::HandleRequest(){  // 如果有 捕获请求下发，则退出等待状态  if (waitingList_.empty()) {    std::unique_lock<std::mutex> l(wtLock_);    if (waitingList_.empty()) {      cv_.wait(l, [this] { return !(state_ == STREAM_STATE_BUSY && waitingList_.empty()); });    }  }// ...    request = waitingList_.front();    CHECK_IF_PTR_NULL_RETURN_VOID(request);    if (!request->IsContinous()) { // 如果是连续捕获，则保留一份拷贝在waitinglist      waitingList_.pop_front();    }  }// 处理捕获请求  request->Process(streamId_);// 最终调用下面的Capture接口  return;}

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C++RetCode StreamBase::Capture(const std::shared_ptr& request){  CHECK_IF_PTR_NULL_RETURN_VALUE(request, RC_ERROR);  CHECK_IF_PTR_NULL_RETURN_VALUE(pipeline_, RC_ERROR);
  RetCode rc = RC_ERROR;  if (request->IsFirstOne() && !request->IsContinous()) {    uint32_t n = GetBufferCount();    for (uint32_t i = 0; i < n; i++) {      DeliverBuffer();// 单次捕获一次性下发所有的buffer    }  } else {    do {      rc = DeliverBuffer();// 连续捕获每次下发一个buffer    } while (rc != RC_OK && state_ == STREAM_STATE_BUSY);  }
  if (request->NeedCancel()) {// 被取消的捕获则退出    CAMERA_LOGE("StreamBase::Capture stream [id:%{public}d] request->NeedCancel", streamId_);    return RC_OK;  }
  rc = pipeline_->Config({streamId_}, request->GetCaptureSetting());// 通知pipeline配置  if (rc != RC_OK) {    CAMERA_LOGE("stream [id:%{public}d] config pipeline failed.", streamId_);    return RC_ERROR;  }
  rc = pipeline_->Capture({streamId_}, request->GetCaptureId());// 这里的capture指的是pipeline中的source node开始回buffer
  {    std::unique_lock<std::mutex> l(tsLock_);    inTransitList_.emplace_back(request);// 处理过的捕获请求存放在inTransitList  }  return RC_OK;}

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到这起流的流程就结束了，pipeline回上来的帧通过OnFrame接口处理

C++RetCode StreamBase::OnFrame(const std::shared_ptr& request){// ...  bool isEnded = false;  if (!request->IsContinous()) {    isEnded = true;  } else if (request->NeedCancel()) {    isEnded = true;  }  {    // inTransitList_ may has multiple copies of continious-capture request, we just need erase one of them.    std::unique_lock<std::mutex> l(tsLock_);    for (auto it = inTransitList_.begin(); it != inTransitList_.end(); it++) {      if ((*it) == request) {        inTransitList_.erase(it);// 已经回帧的请求，从inTransitList删除        break;      }    }    if (isEnded) {      // if this is the last request of capture, send CaptureEndedMessage.      auto it = std::find(inTransitList_.begin(), inTransitList_.end(), request);      if (it == inTransitList_.end()) {        std::shared_ptr endMessage =          std::make_shared(streamId_, request->GetCaptureId(), request->GetEndTime(),                             request->GetOwnerCount(), tunnel_->GetFrameCount());        CAMERA_LOGV("end of stream [%d], ready to send end message, capture id = %d",          streamId_, request->GetCaptureId());        messenger_->SendMessage(endMessage);        pipeline_->CancelCapture({streamId_});// 如果此次捕获结束，则取消捕获      }    }  }  ReceiveBuffer(buffer);// 底层返回的buffer送还到生产端，最终帧数据送到消费端  return RC_OK;}

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附录：

• linux和Android的关系 - 知乎 (zhihu.com)

• HAL Subsystem | Android Open Source Project (google.cn)

• zh-cn/release-notes/OpenHarmony-v3.1-release.md · OpenHarmony/docs - Gitee.com

• OpenHarmony HDF 驱动框架介绍和驱动加载过程分析-OpenHarmony技术社区

• OpenHarmony HDF HDI基础能力分析与使用

原文标题：OpenHarmony 相机用户态驱动框架

文章出处：【微信公众号：HarmonyOS官方合作社区】欢迎添加关注！文章转载请注明出处。

审核编辑：汤梓红