# Holistic Replay

This example demonstrates how to replay previously recorded holistic data, feeding multiple synchronized streams such as video and
IMU back into a DepthAI pipeline for testing and development.

This example requires the DepthAI v3 API, see [installation instructions](https://docs.luxonis.com/software-v3/depthai.md).

## Pipeline

### examples/holistic_replay.pipeline.json

```json
{"pipeline": {"connections": [{"node1Id": 1, "node1Output": "out", "node1OutputGroup": "", "node2Id": 4, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 0, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 2, "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": [[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"}}], [2, {"alias": "", "id": 2, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 6, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_0_0"}}], [1, {"alias": "", "id": 1, "ioInfo": [[["", "out"], {"blocking": false, "group": "", "id": 5, "name": "out", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "mockIn"], {"blocking": true, "group": "", "id": 4, "name": "mockIn", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "IMU", "parentId": -1, "properties": {"batchReportThreshold": 100, "enableFirmwareUpdate": false, "imuSensors": [{"changeSensitivity": 0, "reportRate": 500, "sensitivityEnabled": false, "sensitivityRelative": false, "sensorId": 20}, {"changeSensitivity": 0, "reportRate": 400, "sensitivityEnabled": false, "sensitivityRelative": false, "sensorId": 21}], "maxBatchReports": 5}}], [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": {"index": 0, "value": 30.0}}, "resizeMode": 0, "size": {"value": {"index": 0, "value": [1920, 1080]}}, "type": null}], "resolutionHeight": -1, "resolutionWidth": -1}}]]}}
```

## Source code

#### Python

```python
#!/usr/bin/env python3

import cv2
import depthai as dai
import argparse

parser = argparse.ArgumentParser()
parser.add_argument("-s", "--source", default="recordings/recording.tar", help="Recording path")
args = parser.parse_args()

# Create pipeline
with dai.Pipeline(True) as pipeline:
    pipeline.enableHolisticReplay(args.source)

    # Define source and output
    camRgb = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_A)
    camRgbOut = camRgb.requestOutput((600, 400), fps = 30)

    imu = pipeline.create(dai.node.IMU)
    imu.enableIMUSensor(dai.IMUSensor.ACCELEROMETER_RAW, 500);
    imu.enableIMUSensor(dai.IMUSensor.GYROSCOPE_RAW, 400);
    imu.setBatchReportThreshold(100)

    videoQueue = camRgbOut.createOutputQueue()
    imuQueue = imu.out.createOutputQueue()

    # Connect to device and start pipeline
    pipeline.start()
    while pipeline.isRunning():
        videoIn : dai.ImgFrame = videoQueue.get()
        imuData : dai.IMUData = imuQueue.get()

        # Get BGR frame from NV12 encoded video frame to show with opencv
        # Visualizing the frame on slower hosts might have overhead
        cv2.imshow("video", videoIn.getCvFrame())

        for packet in imuData.packets:
            print(f"IMU Accelerometer: {packet.acceleroMeter}")
            print(f"IMU Gyroscope: {packet.gyroscope}")

        if cv2.waitKey(1) == ord('q'):
            break
```

#### C++

```cpp
#include <opencv2/highgui.hpp>

#include "depthai/depthai.hpp"

#ifndef DEPTHAI_MERGED_TARGET
    #error This example needs OpenCV support, which is not available on your system
#endif

int main(int argc, char** argv) {
    dai::Pipeline pipeline;

    pipeline.enableHolisticReplay(argc > 1 ? std::string(argv[1]) : "recording.tar");

    auto camRgb = pipeline.create<dai::node::Camera>()->build(dai::CameraBoardSocket::CAM_A);
    auto* camOut = camRgb->requestOutput({600, 400});

    auto imu = pipeline.create<dai::node::IMU>();

    // enable ACCELEROMETER_RAW at 500 hz rate
    imu->enableIMUSensor(dai::IMUSensor::ACCELEROMETER_RAW, 500);
    // enable GYROSCOPE_RAW at 400 hz rate
    imu->enableIMUSensor(dai::IMUSensor::GYROSCOPE_RAW, 400);
    imu->setBatchReportThreshold(100);

    auto videoQueue = camOut->createOutputQueue();
    auto q = imu->out.createOutputQueue();

    pipeline.start();

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

    while(pipeline.isRunning()) {
        auto videoIn = videoQueue->get<dai::ImgFrame>();
        auto imuData = q->get<dai::IMUData>();

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

        for(auto& imuPacket : imuData->packets) {
            auto& acceleroValues = imuPacket.acceleroMeter;
            auto& gyroValues = imuPacket.gyroscope;

            printf("Accelerometer [m/s^2]: x: %.3f y: %.3f z: %.3f \n", acceleroValues.x, acceleroValues.y, acceleroValues.z);
            printf("Gyroscope [rad/s]: x: %.3f y: %.3f z: %.3f \n", gyroValues.x, gyroValues.y, gyroValues.z);
        }

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

    pipeline.stop();
}
```

### Need assistance?

Head over to [Discussion Forum](https://discuss.luxonis.com/) for technical support or any other questions you might have.