# Detection network Remap

This example demonstrates running YOLOv6 object detection on an RGB stream while simultaneously processing stereo depth data,
displaying bounding boxes on both the RGB and colorized depth frames.

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

## Pipeline

### examples/detection_network_remap.pipeline.json

```json
{"pipeline": {"connections": [{"node1Id": 6, "node1Output": "disparity", "node1OutputGroup": "", "node2Id": 11, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 5, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 6, "node2Input": "right", "node2InputGroup": ""}, {"node1Id": 4, "node1Output": "0", "node1OutputGroup": "dynamicOutputs", "node2Id": 6, "node2Input": "left", "node2InputGroup": ""}, {"node1Id": 2, "node1Output": "passthrough", "node1OutputGroup": "", "node2Id": 7, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 2, "node1Output": "passthrough", "node1OutputGroup": "", "node2Id": 3, "node2Input": "imageIn", "node2InputGroup": ""}, {"node1Id": 2, "node1Output": "out", "node1OutputGroup": "", "node2Id": 3, "node2Input": "in", "node2InputGroup": ""}, {"node1Id": 3, "node1Output": "out", "node1OutputGroup": "", "node2Id": 9, "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": [[11, {"alias": "", "id": 11, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 37, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_6_disparity"}}], [9, {"alias": "", "id": 9, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 36, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_3_out"}}], [7, {"alias": "", "id": 7, "ioInfo": [[["", "in"], {"blocking": true, "group": "", "id": 35, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "XLinkOut", "parentId": -1, "properties": {"maxFpsLimit": -1.0, "metadataOnly": false, "streamName": "__x_2_passthrough"}}], [6, {"alias": "", "id": 6, "ioInfo": [[["", "confidenceMap"], {"blocking": false, "group": "", "id": 34, "name": "confidenceMap", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "debugDispCostDump"], {"blocking": false, "group": "", "id": 33, "name": "debugDispCostDump", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "debugExtDispLrCheckIt2"], {"blocking": false, "group": "", "id": 32, "name": "debugExtDispLrCheckIt2", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "debugDispLrCheckIt2"], {"blocking": false, "group": "", "id": 30, "name": "debugDispLrCheckIt2", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "debugExtDispLrCheckIt1"], {"blocking": false, "group": "", "id": 31, "name": "debugExtDispLrCheckIt1", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "debugDispLrCheckIt1"], {"blocking": false, "group": "", "id": 29, "name": "debugDispLrCheckIt1", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "outConfig"], {"blocking": false, "group": "", "id": 28, "name": "outConfig", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "rectifiedRight"], {"blocking": false, "group": "", "id": 27, "name": "rectifiedRight", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "rectifiedLeft"], {"blocking": false, "group": "", "id": 26, "name": "rectifiedLeft", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "depth"], {"blocking": false, "group": "", "id": 22, "name": "depth", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "right"], {"blocking": true, "group": "", "id": 21, "name": "right", "queueSize": 3, "type": 3, "waitForMessage": false}], [["", "left"], {"blocking": true, "group": "", "id": 20, "name": "left", "queueSize": 3, "type": 3, "waitForMessage": false}], [["", "syncedRight"], {"blocking": false, "group": "", "id": 25, "name": "syncedRight", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "syncedLeft"], {"blocking": false, "group": "", "id": 24, "name": "syncedLeft", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "inputAlignTo"], {"blocking": false, "group": "", "id": 19, "name": "inputAlignTo", "queueSize": 1, "type": 3, "waitForMessage": true}], [["", "disparity"], {"blocking": false, "group": "", "id": 23, "name": "disparity", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "inputConfig"], {"blocking": true, "group": "", "id": 18, "name": "inputConfig", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "StereoDepth", "parentId": -1, "properties": {"alphaScaling": null, "baseline": null, "depthAlignCamera": -1, "depthAlignmentUseSpecTranslation": null, "disparityToDepthUseSpecTranslation": null, "enableFrameSync": true, "enableRectification": true, "enableRuntimeStereoModeSwitch": false, "focalLength": null, "focalLengthFromCalibration": true, "height": null, "initialConfig": {"algorithmControl": {"centerAlignmentShiftFactor": null, "customDepthUnitMultiplier": 1000.0, "depthAlign": 1, "depthUnit": 2, "disparityShift": 0, "enableExtended": true, "enableLeftRightCheck": true, "enableSubpixel": true, "enableSwLeftRightCheck": false, "leftRightCheckThreshold": 10, "numInvalidateEdgePixels": 0, "subpixelFractionalBits": 5}, "censusTransform": {"enableMeanMode": true, "kernelMask": 0, "kernelSize": -1, "noiseThresholdOffset": 1, "noiseThresholdScale": 1, "threshold": 0}, "confidenceMetrics": {"flatnessConfidenceThreshold": 2, "flatnessConfidenceWeight": 8, "flatnessOverride": false, "motionVectorConfidenceThreshold": 1, "motionVectorConfidenceWeight": 4, "occlusionConfidenceWeight": 20}, "costAggregation": {"divisionFactor": 1, "horizontalPenaltyCostP1": 250, "horizontalPenaltyCostP2": 500, "p1Config": {"defaultValue": 11, "edgeThreshold": 15, "edgeValue": 10, "enableAdaptive": true, "smoothThreshold": 5, "smoothValue": 22}, "p2Config": {"defaultValue": 33, "edgeValue": 22, "enableAdaptive": true, "smoothValue": 63}, "verticalPenaltyCostP1": 250, "verticalPenaltyCostP2": 500}, "costMatching": {"confidenceThreshold": 55, "disparityWidth": 1, "enableCompanding": false, "enableSwConfidenceThresholding": false, "invalidDisparityValue": 0, "linearEquationParameters": {"alpha": 0, "beta": 2, "threshold": 127}}, "filtersBackend": 2, "postProcessing": {"adaptiveMedianFilter": {"confidenceThreshold": 200, "enable": true}, "bilateralSigmaValue": 0, "brightnessFilter": {"maxBrightness": 256, "minBrightness": 0}, "decimationFilter": {"decimationFactor": 1, "decimationMode": 0}, "filteringOrder": [3, 1, 2, 4, 5], "holeFilling": {"enable": true, "fillConfidenceThreshold": 200, "highConfidenceThreshold": 210, "invalidateDisparities": true, "minValidDisparity": 1}, "median": 0, "spatialFilter": {"alpha": 0.5, "delta": 0, "enable": false, "holeFillingRadius": 2, "numIterations": 1}, "speckleFilter": {"differenceThreshold": 2, "enable": false, "speckleRange": 50}, "temporalFilter": {"alpha": 0.4000000059604645, "delta": 0, "enable": false, "persistencyMode": 3}, "thresholdFilter": {"maxRange": 65535, "minRange": 0}}}, "mesh": {"meshLeftUri": "", "meshRightUri": "", "meshSize": null, "stepHeight": 16, "stepWidth": 16}, "numFramesPool": 3, "numPostProcessingMemorySlices": -1, "numPostProcessingShaves": -1, "outHeight": null, "outKeepAspectRatio": true, "outWidth": null, "rectificationUseSpecTranslation": null, "rectifyEdgeFillColor": 0, "useHomographyRectification": null, "width": null}}], [5, {"alias": "", "id": 5, "ioInfo": [[["dynamicOutputs", "0"], {"blocking": false, "group": "dynamicOutputs", "id": 17, "name": "0", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "raw"], {"blocking": false, "group": "", "id": 16, "name": "raw", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "mockIsp"], {"blocking": true, "group": "", "id": 15, "name": "mockIsp", "queueSize": 8, "type": 3, "waitForMessage": false}], [["", "inputControl"], {"blocking": true, "group": "", "id": 14, "name": "inputControl", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "Camera", "parentId": -1, "properties": {"boardSocket": 2, "cameraName": "", "fps": -1.0, "imageOrientation": -1, "initialControl": {"aeLockMode": false, "aeMaxExposureTimeUs": 48, "aeRegion": {"height": 49249, "priority": 3611420857, "width": 26231, "x": 50422, "y": 17299}, "afRegion": {"height": 44658, "priority": 3128807845, "width": 19054, "x": 30871, "y": 864}, "antiBandingMode": 134, "autoFocusMode": 3, "awbLockMode": false, "awbMode": 16, "brightness": 0, "captureIntent": 108, "chromaDenoise": 87, "cmdMask": 0, "contrast": 10, "controlMode": 27, "effectMode": 138, "enableHdr": false, "expCompensation": 0, "expManual": {"exposureTimeUs": 3098448084, "frameDurationUs": 2264028624, "sensitivityIso": 3256143576}, "frameSyncMode": 185, "lensPosAutoInfinity": 169, "lensPosAutoMacro": 93, "lensPosition": 0, "lensPositionRaw": 0.0, "lowPowerNumFramesBurst": 0, "lowPowerNumFramesDiscard": 0, "lumaDenoise": 202, "miscControls": [], "saturation": -35, "sceneMode": 158, "sharpness": 101, "strobeConfig": {"activeLevel": 51, "enable": 89, "gpioNumber": -8}, "strobeTimings": {"durationUs": 0, "exposureBeginOffsetUs": -1175339376, "exposureEndOffsetUs": 272}, "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": [1280, 720]}}, "type": 22}], "resolutionHeight": -1, "resolutionWidth": -1}}], [4, {"alias": "", "id": 4, "ioInfo": [[["dynamicOutputs", "0"], {"blocking": false, "group": "dynamicOutputs", "id": 13, "name": "0", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "raw"], {"blocking": false, "group": "", "id": 12, "name": "raw", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "mockIsp"], {"blocking": true, "group": "", "id": 11, "name": "mockIsp", "queueSize": 8, "type": 3, "waitForMessage": false}], [["", "inputControl"], {"blocking": true, "group": "", "id": 10, "name": "inputControl", "queueSize": 3, "type": 3, "waitForMessage": false}]], "logLevel": 3, "name": "Camera", "parentId": -1, "properties": {"boardSocket": 1, "cameraName": "", "fps": -1.0, "imageOrientation": -1, "initialControl": {"aeLockMode": false, "aeMaxExposureTimeUs": 740438574, "aeRegion": {"height": 8202, "priority": 2099257376, "width": 23840, "x": 8224, "y": 8224}, "afRegion": {"height": 27938, "priority": 1818584175, "width": 8224, "x": 2604, "y": 8224}, "antiBandingMode": 110, "autoFocusMode": 3, "awbLockMode": false, "awbMode": 99, "brightness": 32, "captureIntent": 118, "chromaDenoise": 100, "cmdMask": 0, "contrast": 32, "controlMode": 101, "effectMode": 114, "enableHdr": false, "expCompensation": 32, "expManual": {"exposureTimeUs": 1663986026, "frameDurationUs": 538976266, "sensitivityIso": 577138287}, "frameSyncMode": 116, "lensPosAutoInfinity": 100, "lensPosAutoMacro": 110, "lensPosition": 0, "lensPositionRaw": 0.0, "lowPowerNumFramesBurst": 111, "lowPowerNumFramesDiscard": 112, "lumaDenoise": 111, "miscControls": [], "saturation": 34, "sceneMode": 111, "sharpness": 109, "strobeConfig": {"activeLevel": 114, "enable": 101, "gpioNumber": 95}, "strobeTimings": {"durationUs": 825110562, "exposureBeginOffsetUs": 1869181810, "exposureEndOffsetUs": 540680814}, "wbColorTemp": 24428}, "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": [1280, 720]}}, "type": 22}], "resolutionHeight": -1, "resolutionWidth": -1}}], [3, {"alias": "detectionParser", "id": 3, "ioInfo": [[["", "out"], {"blocking": false, "group": "", "id": 9, "name": "out", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "imageIn"], {"blocking": false, "group": "", "id": 8, "name": "imageIn", "queueSize": 1, "type": 3, "waitForMessage": true}], [["", "in"], {"blocking": true, "group": "", "id": 7, "name": "in", "queueSize": 1, "type": 3, "waitForMessage": true}]], "logLevel": 3, "name": "DetectionParser", "parentId": 1, "properties": {"networkInputs": {"images": {"dataType": 1, "dims": [416, 416, 3, 1], "name": "images", "numDimensions": 4, "offset": 0, "order": 17185, "qpScale": 1.0, "qpZp": 0.0, "quantization": false, "strides": []}}, "numFramesPool": 8, "parser": {"anchorMasks": {}, "anchors": [], "anchorsV2": [], "classNames": ["person", "bicycle", "car", "motorcycle", "airplane", "bus", "train", "truck", "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake", "chair", "couch", "potted plant", "bed", "dining table", "toilet", "tv", "laptop", "mouse", "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"], "classes": 80, "confidenceThreshold": 0.5, "coordinates": 4, "iouThreshold": 0.5, "nnFamily": 0, "subtype": "yolov6"}}}], [2, {"alias": "neuralNetwork", "id": 2, "ioInfo": [[["", "passthrough"], {"blocking": false, "group": "", "id": 6, "name": "passthrough", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "out"], {"blocking": false, "group": "", "id": 5, "name": "out", "queueSize": 8, "type": 0, "waitForMessage": false}], [["", "in"], {"blocking": true, "group": "", "id": 4, "name": "in", "queueSize": 3, "type": 3, "waitForMessage": true}]], "logLevel": 3, "name": "NeuralNetwork", "parentId": 1, "properties": {"backend": "", "backendProperties": {}, "blobSize": 8689834, "blobUri": "asset:__blob", "modelSource": 0, "modelUri": "", "numFrames": 8, "numNCEPerThread": 0, "numShavesPerThread": 0, "numThreads": 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": 65544, "aeRegion": {"height": 0, "priority": 0, "width": 0, "x": 0, "y": 0}, "afRegion": {"height": 43, "priority": 131077, "width": 12, "x": 0, "y": 0}, "antiBandingMode": 0, "autoFocusMode": 3, "awbLockMode": false, "awbMode": 0, "brightness": 0, "captureIntent": 0, "chromaDenoise": 136, "cmdMask": 0, "contrast": -116, "controlMode": 12, "effectMode": 0, "enableHdr": false, "expCompensation": 0, "expManual": {"exposureTimeUs": 0, "frameDurationUs": 0, "sensitivityIso": 0}, "frameSyncMode": 6, "lensPosAutoInfinity": 0, "lensPosAutoMacro": 0, "lensPosition": 0, "lensPositionRaw": 0.0, "lowPowerNumFramesBurst": 1, "lowPowerNumFramesDiscard": 0, "lumaDenoise": 0, "miscControls": [], "saturation": 0, "sceneMode": 0, "sharpness": 2, "strobeConfig": {"activeLevel": 110, "enable": 0, "gpioNumber": 111}, "strobeTimings": {"durationUs": 2949132, "exposureBeginOffsetUs": 6649189, "exposureEndOffsetUs": 1704760}, "wbColorTemp": 1}, "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": [416, 416]}}, "type": 8}], "resolutionHeight": -1, "resolutionWidth": -1}}]]}}
```

## Source code

#### Python

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

import cv2
import depthai as dai
import numpy as np

def colorizeDepth(frameDepth):
    invalidMask = frameDepth == 0
    # Log the depth, minDepth and maxDepth
    try:
        minDepth = np.percentile(frameDepth[frameDepth != 0], 3)
        maxDepth = np.percentile(frameDepth[frameDepth != 0], 95)
        logDepth = np.log(frameDepth, where=frameDepth != 0)
        logMinDepth = np.log(minDepth)
        logMaxDepth = np.log(maxDepth)
        np.nan_to_num(logDepth, copy=False, nan=logMinDepth)
        # Clip the values to be in the 0-255 range
        logDepth = np.clip(logDepth, logMinDepth, logMaxDepth)

        # Interpolate only valid logDepth values, setting the rest based on the mask
        depthFrameColor = np.interp(logDepth, (logMinDepth, logMaxDepth), (0, 255))
        depthFrameColor = np.nan_to_num(depthFrameColor)
        depthFrameColor = depthFrameColor.astype(np.uint8)
        depthFrameColor = cv2.applyColorMap(depthFrameColor, cv2.COLORMAP_JET)
        # Set invalid depth pixels to black
        depthFrameColor[invalidMask] = 0
    except IndexError:
        # Frame is likely empty
        depthFrameColor = np.zeros((frameDepth.shape[0], frameDepth.shape[1], 3), dtype=np.uint8)
    except Exception as e:
        raise e
    return depthFrameColor

# Create pipeline
with dai.Pipeline() as pipeline:
    cameraNode = pipeline.create(dai.node.Camera).build()
    detectionNetwork = pipeline.create(dai.node.DetectionNetwork).build(cameraNode, dai.NNModelDescription("yolov6-nano"))
    labelMap = detectionNetwork.getClasses()
    monoLeft = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_B)
    monoRight = pipeline.create(dai.node.Camera).build(dai.CameraBoardSocket.CAM_C)
    stereo = pipeline.create(dai.node.StereoDepth)

    # Linking
    monoLeftOut = monoLeft.requestOutput((1280, 720))
    monoRightOut = monoRight.requestOutput((1280, 720))
    monoLeftOut.link(stereo.left)
    monoRightOut.link(stereo.right)

    stereo.setRectification(True)
    stereo.setExtendedDisparity(True)
    stereo.setLeftRightCheck(True)
    stereo.setSubpixel(True)

    qRgb = detectionNetwork.passthrough.createOutputQueue()
    qDet = detectionNetwork.out.createOutputQueue()
    qDepth = stereo.disparity.createOutputQueue()

    pipeline.start()

    def displayFrame(name: str, frame: dai.ImgFrame, imgDetections: dai.ImgDetections):
        color = (0, 255, 0)
        assert imgDetections.getTransformation() is not None
        cvFrame = frame.getFrame() if frame.getType() == dai.ImgFrame.Type.RAW16 else frame.getCvFrame()
        if(frame.getType() == dai.ImgFrame.Type.RAW16):
            cvFrame = colorizeDepth(cvFrame)
        for detection in imgDetections.detections:
            # Get the shape of the frame from which the detections originated for denormalization
            normShape = imgDetections.getTransformation().getSize()

            # Create rotated rectangle to remap
            # Here we use an intermediate dai.Rect to create a dai.RotatedRect to simplify construction and denormalization
            rotRect = dai.RotatedRect(dai.Rect(dai.Point2f(detection.xmin, detection.ymin), dai.Point2f(detection.xmax, detection.ymax)).denormalize(normShape[0], normShape[1]), 0)
            # Remap the detection rectangle to target frame
            remapped = imgDetections.getTransformation().remapRectTo(frame.getTransformation(), rotRect)
            # Remapped rectangle could be rotated, so we get the bounding box
            bbox = [int(l) for l in remapped.getOuterRect()]
            cv2.putText(
                cvFrame,
                labelMap[detection.label],
                (bbox[0] + 10, bbox[1] + 20),
                cv2.FONT_HERSHEY_TRIPLEX,
                0.5,
                255,
            )
            cv2.putText(
                cvFrame,
                f"{int(detection.confidence * 100)}%",
                (bbox[0] + 10, bbox[1] + 40),
                cv2.FONT_HERSHEY_TRIPLEX,
                0.5,
                255,
            )
            cv2.rectangle(cvFrame, (bbox[0], bbox[1]), (bbox[2], bbox[3]), color, 2)
        # Show the frame
        cv2.imshow(name, cvFrame)

    while pipeline.isRunning():
        inRgb: dai.ImgFrame = qRgb.get()
        inDet: dai.ImgDetections = qDet.get()
        inDepth: dai.ImgFrame = qDepth.get()
        hasRgb = inRgb is not None
        hasDepth = inDepth is not None
        hasDet = inDet is not None
        if hasRgb:
            displayFrame("rgb", inRgb, inDet)
        if hasDepth:
            displayFrame("depth", inDepth, inDet)
        if cv2.waitKey(1) == ord("q"):
            pipeline.stop()
            break
```

#### C++

```cpp
#include <algorithm>  // Required for std::sort and std::unique
#include <cmath>      // Required for std::log, std::isnan, std::isinf
#include <iostream>
#include <opencv2/opencv.hpp>
#include <string>
#include <vector>

#include "depthai/depthai.hpp"
#include "xtensor/containers/xadapt.hpp"
#include "xtensor/core/xmath.hpp"

cv::Mat colorizeDepth(cv::Mat frameDepth) {
    cv::Mat invalidMask = frameDepth == 0;
    cv::Mat depthFrameColor;

    try {
        cv::Mat frameDepthFloat;
        frameDepth.convertTo(frameDepthFloat, CV_32F);
        xt::xtensor<float, 2> depth =
            xt::adapt((float*)frameDepthFloat.data, {static_cast<size_t>(frameDepthFloat.rows), static_cast<size_t>(frameDepthFloat.cols)});

        // Get valid depth values (non-zero)
        std::vector<float> validDepth;
        validDepth.reserve(depth.size());
        std::copy_if(depth.begin(), depth.end(), std::back_inserter(validDepth), [](float x) { return x != 0; });

        if(validDepth.size() == 0) {
            return cv::Mat::zeros(frameDepth.rows, frameDepth.cols, CV_8UC3);
        }

        // Calculate percentiles
        std::sort(validDepth.begin(), validDepth.end());
        float minDepth = validDepth[static_cast<size_t>(validDepth.size() * 0.03)];
        float maxDepth = validDepth[static_cast<size_t>(validDepth.size() * 0.95)];

        // Take log of depth values
        auto logDepth = xt::eval(xt::log(depth));
        float logMinDepth = std::log(minDepth);
        float logMaxDepth = std::log(maxDepth);

        // Replace invalid values with logMinDepth using a naive implementation
        auto logDepthData = logDepth.data();
        auto depthData = depth.data();
        const size_t size = depth.size();
        for(size_t i = 0; i < size; i++) {
            if(std::isnan(logDepthData[i]) || std::isinf(logDepthData[i]) || depthData[i] == 0.0f) {
                logDepthData[i] = logMinDepth;
            }
        }

        // Clip values
        logDepth = xt::clip(logDepth, logMinDepth, logMaxDepth);

        // Normalize to 0-255 range
        auto normalizedDepth = (logDepth - logMinDepth) / (logMaxDepth - logMinDepth) * 255.0f;

        // Convert to CV_8UC1
        cv::Mat depthMat(frameDepth.rows, frameDepth.cols, CV_8UC1);
        std::transform(normalizedDepth.begin(), normalizedDepth.end(), depthMat.data, [](float x) { return static_cast<uchar>(x); });

        // Apply colormap
        cv::applyColorMap(depthMat, depthFrameColor, cv::COLORMAP_JET);

        // Set invalid pixels to black
        depthFrameColor.setTo(cv::Scalar(0, 0, 0), invalidMask);

    } catch(const std::exception& e) {
        std::cerr << "Error in colorizeDepth: " << e.what() << std::endl;
        return cv::Mat::zeros(frameDepth.rows, frameDepth.cols, CV_8UC3);
    }

    return depthFrameColor;
}

// Helper function to display frames with detections
void displayFrame(const std::string& name,
                  std::shared_ptr<dai::ImgFrame> frame,
                  std::shared_ptr<dai::ImgDetections> imgDetections,
                  const std::vector<std::string>& labelMap) {
    cv::Scalar color(0, 255, 0);
    cv::Mat cvFrame;

    if(frame->getType() == dai::ImgFrame::Type::RAW16) {
        cvFrame = colorizeDepth(frame->getFrame());
    } else {
        cvFrame = frame->getCvFrame();
    }

    if(!imgDetections || !imgDetections->transformation.has_value()) {
        // std::cout << "No detections or transformation data for " << name << std::endl;
        cv::imshow(name, cvFrame);
        return;
    }

    const auto& sourceTransform = *(imgDetections->transformation);
    const auto& targetTransform = frame->transformation;

    for(const auto& detection : imgDetections->detections) {
        auto normShape = sourceTransform.getSize();

        dai::Rect rect(dai::Point2f(detection.xmin, detection.ymin), dai::Point2f(detection.xmax, detection.ymax));
        rect = rect.denormalize(static_cast<float>(normShape.first), static_cast<float>(normShape.second));
        dai::RotatedRect rotRect(rect, 0);

        auto remapped = sourceTransform.remapRectTo(targetTransform, rotRect);
        auto bbox = remapped.getOuterRect();

        cv::putText(cvFrame,
                    labelMap[detection.label],
                    cv::Point(static_cast<int>(bbox[0]) + 10, static_cast<int>(bbox[1]) + 20),
                    cv::FONT_HERSHEY_TRIPLEX,
                    0.5,
                    cv::Scalar(255, 255, 255));
        cv::putText(cvFrame,
                    std::to_string(static_cast<int>(detection.confidence * 100)) + "%",
                    cv::Point(static_cast<int>(bbox[0]) + 10, static_cast<int>(bbox[1]) + 40),
                    cv::FONT_HERSHEY_TRIPLEX,
                    0.5,
                    cv::Scalar(255, 255, 255));
        cv::rectangle(cvFrame,
                      cv::Point(static_cast<int>(bbox[0]), static_cast<int>(bbox[1])),
                      cv::Point(static_cast<int>(bbox[2]), static_cast<int>(bbox[3])),
                      color,
                      2);
    }
    cv::imshow(name, cvFrame);
}

int main() {
    dai::Pipeline pipeline;

    auto cameraNode = pipeline.create<dai::node::Camera>();
    cameraNode->build();

    auto detectionNetwork = pipeline.create<dai::node::DetectionNetwork>();
    dai::NNModelDescription modelDescription;
    modelDescription.model = "yolov6-nano";
    detectionNetwork->build(cameraNode, modelDescription);
    auto labelMap = detectionNetwork->getClasses().value_or(std::vector<std::string>{});

    auto monoLeft = pipeline.create<dai::node::Camera>();
    monoLeft->build(dai::CameraBoardSocket::CAM_B);
    auto monoRight = pipeline.create<dai::node::Camera>();
    monoRight->build(dai::CameraBoardSocket::CAM_C);
    auto stereo = pipeline.create<dai::node::StereoDepth>();

    // Linking
    auto monoLeftOut = monoLeft->requestOutput(std::make_pair(1280, 720));
    auto monoRightOut = monoRight->requestOutput(std::make_pair(1280, 720));
    monoLeftOut->link(stereo->left);
    monoRightOut->link(stereo->right);

    stereo->setRectification(true);
    stereo->setExtendedDisparity(true);
    stereo->setLeftRightCheck(true);
    stereo->setSubpixel(true);

    auto qRgb = detectionNetwork->passthrough.createOutputQueue();
    auto qDet = detectionNetwork->out.createOutputQueue();
    auto qDepth = stereo->disparity.createOutputQueue();

    pipeline.start();

    while(pipeline.isRunning()) {
        auto inRgb = qRgb->tryGet<dai::ImgFrame>();
        auto inDet = qDet->tryGet<dai::ImgDetections>();
        auto inDepth = qDepth->tryGet<dai::ImgFrame>();

        bool hasRgb = inRgb != nullptr;
        bool hasDepth = inDepth != nullptr;
        bool hasDet = inDet != nullptr;

        if(hasRgb && hasDet) {
            displayFrame("rgb", inRgb, inDet, labelMap);
        }
        if(hasDepth && hasDet) {
            displayFrame("depth", inDepth, inDet, labelMap);
        }

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

    return 0;
}
```

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