I've test OAK-D Pro PoE with tirandazi/depthai-yolov8-segment code.
I created a separate model that learns only two classes from the basic YOLOv8s_seg model, created onnx and blob files, and ran this model after modifying some shape and class information using the github code mentioned above, but the following error occurred.

```

PS C:\Users\great\OneDrive\Documents\ITman\OAK_D\depthai-yolov8-segment-main>
& C:/Users/great/anaconda3/envs/py310/python.exe c:/Users/great/OneDrive/Documents/ITman/OAK_D/depthai-yolov8-segment-main/main.py

Color cam resolution:  (1280, 800)
Left cam resolution:  (1280, 800)
Right cam resolution:  (1280, 800)
[18443010E103F7F400] [192.168.0.102] [6.110] [ColorCamera(4)] [warning] Unsupported resolution set for detected camera IMX378/214, needs 1080_P / 4_K / 12_MP. Defaulting to 1080_P
[18443010E103F7F400] [192.168.0.102] [6.161] [NeuralNetwork(3)] [warning] Network compiled for 6 shaves, maximum available 10, compiling for 5 shaves likely will yield in better performance
[18443010E103F7F400] [192.168.0.102] [6.670] [StereoDepth(5)] [error] Stereo rectification error: 1, trying to recover.
[18443010E103F7F400] [192.168.0.102] [6.670] [StereoDepth(5)] [error] Stereo alignment error: 1, trying to recover.
[18443010E103F7F400] [192.168.0.102] [1732086905.791] [host] [warning] Monitor thread (device: 18443010E103F7F400 [192.168.0.102]) - ping was missed, closing the device connection
[2024-11-20 16:17:22.877] [depthai] [error] Device with id 18443010E103F7F400 has crashed. Crash dump logs are stored in: C:\Users\great\OneDrive\Documents\ITman\OAK_D\depthai-yolov8-segment-main\.cache\depthai\crashdumps\b4f6dd7b65d6361d04e08fb19ae9f6f2814ae31d\crash_dump.json - please report to developers.

So I use OAK-D Pro with usb-c type interface for comparison and I don't find any problem log at all.

I need to use PoE, how should I do it?

    OseongKwon

    • Your USB OAK-D Pro might have OV9782 which supports 800p, whereas POE version has IMX378 which doesn't. Set resolution from 1080p to 800p via setIspScale or setPreviewSize().

    • Calibration might be wrong as well, do examples like depth_video work well?

    Thanks,
    Jaka

      PoE, USB all cameras are same with

      d.getCameraSensorNames()
      {<CameraBoardSocket.CAM_C: 2>: 'OV9282',
      <CameraBoardSocket.CAM_A: 0>: 'IMX378',
      <CameraBoardSocket.CAM_B: 1>: 'OV9282'}

        Is EEPROM available: True

        User calibration: {

        "batchName": "",

        "batchTime": 1710401925,

        "boardConf": "IR-C00M00-00",

        "boardCustom": "",

        "boardName": "NG9097",

        "boardOptions": 7,

        "boardRev": "R4M2E4",

        "cameraData": [

        [

  1,

  {

    "cameraType": 0,

    "distortionCoeff": [

      20\.86638641357422,

      -32.677059173583984,

      -0.0002762333897408098,

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      15\.335541725158691,

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      -31.194011688232422,

      14\.251194953918457,

      0\.0,

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    ],

    "extrinsics": {

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      ],

      "specTranslation": {

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        "y": 0.0,

        "z": 0.0

      },

      "toCameraSocket": 2,

      "translation": {

        "x": -7.534882545471191,

        "y": -0.013073663227260113,

        "z": -0.05111880972981453

      }

    },

    "height": 800,

    "intrinsicMatrix": [

      [

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      [

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    ],

    "lensPosition": 0,

    "specHfovDeg": 71.86000061035156,

    "width": 1280

  }

],

[

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      },

      "toCameraSocket": -1,

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    "height": 2160,

    "intrinsicMatrix": [

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    "lensPosition": 0,

    "specHfovDeg": 68.7938003540039,

    "width": 3840

  }

],

[

  2,

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      "toCameraSocket": 0,

      "translation": {

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        "y": 0.072788767516613,

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    },

    "height": 800,

    "intrinsicMatrix": [

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    "lensPosition": 0,

    "specHfovDeg": 71.86000061035156,

    "width": 1280

  }

]

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        "deviceName": "",

        "hardwareConf": "F1-FV00-BC001",

        "housingExtrinsics": {

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"specTranslation": {

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},

"toCameraSocket": -1,

"translation": {

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}

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"specTranslation": {

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},

"toCameraSocket": -1,

"translation": {

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}

        },

        "miscellaneousData": [],

        "productName": "OAK-D-PRO-POE-FF",

        "stereoEnableDistortionCorrection": true,

        "stereoRectificationData": {

        "leftCameraSocket": 1,

"rectifiedRotationLeft": [

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],

"rightCameraSocket": 2

        },

        "stereoUseSpecTranslation": false,

        "version": 7,

        "verticalCameraSocket": -1

        }

        Factory calibration: {

        "batchName": "",

        "batchTime": 1710401925,

        "boardConf": "IR-C00M00-00",

        "boardCustom": "",

        "boardName": "NG9097",

        "boardOptions": 7,

        "boardRev": "R4M2E4",

        "cameraData": [

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],

[

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          I have an additional question.

          The default ColorOrder of the ColorCamera node is BGR, and the default color order when training the YOLO model is RGB.

          Therefore, when running the NN model on OAK-D, this color conversion needs to be performed. To do this,

          - Add the --reverse option when converting the blob,

          - Add cam.setColorOrder(dai.ColorCameraProperties.ColorOrder.RGB)

          in the ColorCamera node.

          If you look at the example luxonis/depthai-experimentsblob/master/gen2-yolo/yolo-segmentation,

          there is no typical guidance on this. Is this also a problem with the example?

            OseongKwon
            stereoDepth node memory issue is the suspected cause of this.
            Try:

            • compiling the model for 5 or 4 shaves and check if that makes a difference
            • lowering the mono and color resolution

            OseongKwon - Add the --reverse option when converting the blob,

            • Add cam.setColorOrder(dai.ColorCameraProperties.ColorOrder.RGB)

            You probably don't need both. If your model expects RGB, setting color order to RGB should be enough. When you set it on both sides, it think you might actually just reverse both for no good reason. Haven't tested this though.

            Thanks
            Jaka

                  when running the NN model on OAK-D, this color conversion needs to be performed. To do this,

                  - Add the --reverse option when converting the blob,

                  - Or add cam.setColorOrder(dai.ColorCameraProperties.ColorOrder.RGB)

                  in the ColorCamera node.

                  If you look at the example luxonis/depthai-experimentsblob/master/gen2-yolo/yolo-segmentation,

                  there is no typical guidance on this. this is also a problem with the example.

                  jakaskerl
                  1. The same problem is observed at 4~5 shaves.
                  2. The detection capability decreases when the resolution is lowered.
                  current resolution is 640x480.

                      OseongKwon
                      Ok, thanks. This is a FW issue which we need to debug. I will notify you when a solution is found. I suggest you use lower resolution in the meantime.

                      Thanks,
                      Jaka

                          OseongKwon
                          There was another suggestion to further lower the shave count for NN to 3. This will lower the FPS, but it might help us gain better understanding of what is going on.

                          Thanks,
                          Jaka