OpenHarmony相机用户态驱动框架 原创 精华

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

Shell
drivers/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

•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);

}

先获取stream operator实例

C++
void testdisplay::achievestreamoperator()

{

    // create and get streamoperator information

    std::shared_ptr<ohos::camera::istreamoperatorcallback> streamoperatorcallback =

        std::make_shared<ohos::camera::istreamoperatorcallback>();

    rc = cameradevice->getstreamoperator(streamoperatorcallback, streamoperator);

					// ........

}

通过前文的streamOperator创建流

C++
void TestDisplay::StartStream(std::vector<OHOS::Camera::StreamIntent> intents)

{

    // ..............................

    for (auto& intent : intents) {

        if (intent == 0) {

            std::shared_ptr<IBufferProducer> 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<SurfaceBuffer> 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

    // .................................

}

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<StreamInfo>>& streamInfos)

{

 // .....

    for (auto it : streamInfos) {

//....

        std::shared_ptr<IStream> 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<PixelFormat>(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<StreamTunnel>();

            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

        }

// ...

}

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<StreamTunnel>& 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;

}

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<CameraStandard::CameraMetadata>& modeSetting)

{

// ......

    std::vector<StreamConfiguration> 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;

}

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<IBuffer> buffer) {

        HandleResult(buffer);

        return;

    });

// ....

    return RC_OK;

}

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>& 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<CaptureRequest>(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;

        }

    }

// ...

}

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<CaptureRequest>& 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;

}

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<StreamIntent>(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;

}

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;

}

C++
RetCode StreamBase::Capture(const std::shared_ptr<CaptureRequest>& 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;

}

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<CaptureRequest>& 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<ICaptureMessage> endMessage =

                    std::make_shared<CaptureEndedMessage>(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;

}

::: hljs-center

附录

:::

[^1]: linux和Android的关系 - 知乎 (zhihu.com)

[^2]: HAL Subsystem | Android Open Source Project (google.cn)

[^3]: zh-cn/release-notes/OpenHarmony-v3.1-release.md · OpenHarmony/docs - Gitee.com

[^4]: OpenHarmony HDF 驱动框架介绍和驱动加载过程分析-OpenHarmony技术社区-51CTO.COM

[^5]: OpenHarmony HDF HDI基础能力分析与使用-51CTO.COM