# 视频编码

此示例展示了如何使用 [Video Encoder](https://docs.luxonis.com/software-v3/depthai/depthai-components/nodes/video_encoder.md)
节点，该节点可以在设备上将视频帧编码为 MJPEG、H264 或 H265 视频编解码格式。 它创建了一个名为 VideoSaver 的自定义
[主机节点](https://docs.luxonis.com/software-v3/depthai/depthai-components/host_nodes.md)，该节点从 Video Encoder
节点接收编码后的视频帧并将其保存到宿主计算机上的文件中。

录制结束后，用户必须使用 ffmpeg 将原始编码流转换为可播放的视频文件。可以扩展 VideoSaver 节点以直接保存到容器中，就像 [将编码视频流保存到 mp4
容器](https://github.com/luxonis/oak-examples/tree/master/gen2-container-encoding#save-encoded-video-stream-into-mp4-container)
实验中那样。

## 演示输出

```bash
python3 video_encode.py
Started to save video to video.encoded
Press Ctrl+C to stop
To view the encoded data, convert the stream file (.encoded) into a video file (.mp4) using a command below:
ffmpeg -framerate 30 -i video.encoded -c copy video.mp4
```

运行 ffmpeg 命令后，应使用 VLC 播放器查看视频文件，特别是对于 H265 格式，因为并非所有视频播放器都支持（例如 macOS 上的 QuickTime）。

这个示例需要DepthAI v3 API，参见[安装说明](https://docs.luxonis.com/software-v3/depthai.md)。

## 流水线

### examples/video_encode.pipeline.json

```json
{"pipeline": {"connections": [{"node1Id": 1, "node1Output": "out", "node1OutputGroup": "", "node2Id": 4, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 0, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 6, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 0, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 1, "node2Input": "in", "node2InputGroup": ""}], "globalProperties": {"calibData": null, "cameraTuningBlobSize": null, "cameraTuningBlobUri": "", "leonCssFrequencyHz": 700000000.0, "leonMssFrequencyHz": 700000000.0, "pipelineName": null, "pipelineVersion": null, "sippBufferSize": 18432, "sippDmaBufferSize": 16384, "xlinkChunkSize": -1}, "nodes": [[6, {"alias": "", "id": 6, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 8, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_0_0"}}], [4, {"alias": "", "id": 4, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 7, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_1__out"}}], [1, {"alias": "", "id": 1, "ioInfo": [[["", "out"], {"blocking": false, "group": "", "id": 6, "name": "out", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "bitstream"], {"blocking": false, "group": "", "id": 5, "name": "bitstream", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "in"], {"blocking": true, "group": "", "id": 4, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "VideoEncoder", "parentId": -1, "properties": {"bitrate": 0, "frameRate": 30.0, "keyframeFrequency": 30, "lossless": false, "maxBitrate": 0, "numBFrames": 0, "numFramesPool": 0, "outputFrameSize": 0, "profile": 4, "quality": 80, "rateCtrlMode": 0}}], [0, {"alias": "", "id": 0, "ioInfo": [[["dynamicOutputs", "0"], {"blocking": false, "group": "dynamicOutputs", "id": 3, "name": "0", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "raw"], {"blocking": false, "group": "", "id": 2, "name": "raw", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "mockIsp"], {"blocking": true, "group": "", "id": 1, "name": "mockIsp", "queueSize": 8, "type": 3, "waitForMessage": false}], [["", "inputControl"], {"blocking": true, "group": "", "id": 0, "name": "inputControl", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "Camera", "parentId": -1, "properties": {"boardSocket": 0, "cameraName": "", "fps": -1.0, "imageOrientation": -1, "initialControl": {"aeLockMode": false, "aeMaxExposureTimeUs": 0, "aeRegion": {"height": 0, "priority": 0, "width": 0, "x": 0, "y": 0}, "afRegion": {"height": 0, "priority": 0, "width": 0, "x": 0, "y": 0}, "antiBandingMode": 0, "autoFocusMode": 3, "awbLockMode": false, "awbMode": 0, "brightness": 0, "captureIntent": 0, "chromaDenoise": 0, "cmdMask": 0, "contrast": 0, "controlMode": 0, "effectMode": 0, "enableHdr": false, "expCompensation": 0, "expManual": {"exposureTimeUs": 0, "frameDurationUs": 0, "sensitivityIso": 0}, "frameSyncMode": 0, "lensPosAutoInfinity": 0, "lensPosAutoMacro": 0, "lensPosition": 0, "lensPositionRaw": 0.0, "lowPowerNumFramesBurst": 0, "lowPowerNumFramesDiscard": 0, "lumaDenoise": 0, "miscControls": [], "saturation": 0, "sceneMode": 0, "sharpness": 0, "strobeConfig": {"activeLevel": 0, "enable": 0, "gpioNumber": 0}, "strobeTimings": {"durationUs": 0, "exposureBeginOffsetUs": 0, "exposureEndOffsetUs": 0}, "wbColorTemp": 0}, "isp3aFps": 0, "mockIspHeight": -1, "mockIspWidth": -1, "numFramesPoolIsp": 3, "numFramesPoolPreview": 4, "numFramesPoolRaw": 3, "numFramesPoolStill": 4, "numFramesPoolVideo": 4, "outputRequests": [{"enableUndistortion": null, "fps": {"value": null}, "resizeMode": 0, "size": {"value": {"index": 0, "value": [1920, 1440]}}, "type": 22}], "resolutionHeight": -1, "resolutionWidth": -1}}]]}}
```

## 源代码

#### Python

```python
import depthai as dai

# Capture Ctrl+C and set a flag to stop the loop
import time
import cv2
import threading
import signal

PROFILE = dai.VideoEncoderProperties.Profile.MJPEG # or H265_MAIN, H264_MAIN

quitEvent = threading.Event()
signal.signal(signal.SIGTERM, lambda *_args: quitEvent.set())
signal.signal(signal.SIGINT, lambda *_args: quitEvent.set())

class VideoSaver(dai.node.HostNode):
    def __init__(self, *args, **kwargs):
        dai.node.HostNode.__init__(self, *args, **kwargs)
        self.file_handle = open('video.encoded', 'wb')

    def build(self, *args):
        self.link_args(*args)
        return self

    def process(self, frame):
        frame.getData().tofile(self.file_handle)

with dai.Pipeline() as pipeline:
    camRgb = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_A)
    output = camRgb.requestOutput((1920, 1440), type=dai.ImgFrame.Type.NV12)
    outputQueue = output.createOutputQueue()
    encoded = pipeline.create(dai.node.VideoEncoder).build(output,
            frameRate = 30,
            profile = PROFILE)
    saver = pipeline.create(VideoSaver).build(encoded.out)

    pipeline.start()
    print("Started to save video to video.encoded")
    print("Press Ctrl+C to stop")
    timeStart = time.monotonic()
    while pipeline.isRunning() and not quitEvent.is_set():
        frame = outputQueue.get()
        assert isinstance(frame, dai.ImgFrame)
        cv2.imshow("video", frame.getCvFrame())
        key = cv2.waitKey(1)
        if key == ord('q'):
            break
    pipeline.stop()
    pipeline.wait()
    saver.file_handle.close()

print("To view the encoded data, convert the stream file (.encoded) into a video file (.mp4) using a command below:")
print("ffmpeg -framerate 30 -i video.encoded -c copy video.mp4")
```

#### C++

```cpp
#include <atomic>
#include <csignal>
#include <fstream>
#include <iostream>
#include <memory>
#include <opencv2/opencv.hpp>
#include <thread>

#include "depthai/depthai.hpp"
#include "depthai/pipeline/datatype/MessageGroup.hpp"

// Global flag for graceful shutdown
std::atomic<bool> quitEvent(false);

// Signal handler
void signalHandler(int signum) {
    quitEvent = true;
}

// Custom host node for saving video data
class VideoSaver : public dai::node::CustomNode<VideoSaver> {
   public:
    VideoSaver() : fileHandle("video.encoded", std::ios::binary) {
        if(!fileHandle.is_open()) {
            throw std::runtime_error("Could not open video.encoded for writing");
        }
    }

    ~VideoSaver() {
        if(fileHandle.is_open()) {
            fileHandle.close();
        }
    }

    std::shared_ptr<dai::Buffer> processGroup(std::shared_ptr<dai::MessageGroup> message) override {
        if(!fileHandle.is_open()) return nullptr;

        // Get raw data and write to file
        auto frame = message->get<dai::EncodedFrame>("data");
        unsigned char* frameData = frame->getData().data();
        size_t frameSize = frame->getData().size();
        std::cout << "Storing frame of size: " << frameSize << std::endl;
        fileHandle.write(reinterpret_cast<const char*>(frameData), frameSize);

        // Don't send anything back
        return nullptr;
    }

   private:
    std::ofstream fileHandle;
};

int main() {
    // Set up signal handlers
    signal(SIGTERM, signalHandler);
    signal(SIGINT, signalHandler);

    // Create device
    std::shared_ptr<dai::Device> device = std::make_shared<dai::Device>();

    // Create pipeline
    dai::Pipeline pipeline(device);

    // Create nodes
    auto camRgb = pipeline.create<dai::node::Camera>()->build(dai::CameraBoardSocket::CAM_A);
    auto output = camRgb->requestOutput(std::make_pair(1920, 1440), dai::ImgFrame::Type::NV12);
    auto outputQueue = output->createOutputQueue();

    // Create video encoder node
    auto encoded = pipeline.create<dai::node::VideoEncoder>();
    encoded->setDefaultProfilePreset(30, dai::VideoEncoderProperties::Profile::MJPEG);
    output->link(encoded->input);

    // Create video saver node
    auto saver = pipeline.create<VideoSaver>();
    encoded->out.link(saver->inputs["data"]);

    // Start pipeline
    pipeline.start();
    std::cout << "Started to save video to video.encoded" << std::endl;
    std::cout << "Press Ctrl+C to stop" << std::endl;

    auto timeStart = std::chrono::steady_clock::now();

    while(pipeline.isRunning() && !quitEvent) {
        auto frame = outputQueue->get<dai::ImgFrame>();
        if(frame == nullptr) continue;

        cv::imshow("video", frame->getCvFrame());

        int key = cv::waitKey(1);
        if(key == 'q') {
            break;
        }
    }

    // Cleanup
    pipeline.stop();
    pipeline.wait();

    std::cout << "To view the encoded data, convert the stream file (.encoded) into a video file (.mp4) using a command below:" << std::endl;
    std::cout << "ffmpeg -framerate 30 -i video.encoded -c copy video.mp4" << std::endl;

    return 0;
}
```

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