# Multi-Input Frame Concatenation

Example concatenates all 3 inputs with a simple custom model created with PyTorch ([link
here](https://github.com/luxonis/oak-examples/blob/master/gen2-custom-models/generate_model/pytorch_concat.py), [tutorial
here](https://docs.luxonis.com/software/depthai/on-device-programming.md)). It uses
[NeuralNetwork](https://docs.luxonis.com/software/depthai-components/nodes/neural_network.md)'s multiple input feature and links
all 3 camera streams directly to the NeuralNetwork node.

## Demo

## Setup

Please run the [install script](https://github.com/luxonis/depthai-python/blob/main/examples/install_requirements.py) to download
all required dependencies. Please note that this script must be ran from git context, so you have to download the
[depthai-python](https://github.com/luxonis/depthai-python) repository first and then run the script

```bash
git clone https://github.com/luxonis/depthai-python.git
cd depthai-python/examples
python3 install_requirements.py
```

For additional information, please follow the [installation guide](https://docs.luxonis.com/software/depthai/manual-install.md).

## Source code

#### Python

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

from pathlib import Path
import sys
import numpy as np
import cv2
import depthai as dai
SHAPE = 300

# Get argument first
nnPath = str((Path(__file__).parent / Path('../models/concat_openvino_2021.4_6shave.blob')).resolve().absolute())
if len(sys.argv) > 1:
    nnPath = sys.argv[1]

if not Path(nnPath).exists():
    import sys
    raise FileNotFoundError(f'Required file/s not found, please run "{sys.executable} install_requirements.py"')

p = dai.Pipeline()
p.setOpenVINOVersion(dai.OpenVINO.VERSION_2021_4)

camRgb = p.createColorCamera()
camRgb.setPreviewSize(SHAPE, SHAPE)
camRgb.setInterleaved(False)
camRgb.setColorOrder(dai.ColorCameraProperties.ColorOrder.BGR)

def create_mono(p, socket):
    mono = p.create(dai.node.MonoCamera)
    mono.setBoardSocket(socket)
    mono.setResolution(dai.MonoCameraProperties.SensorResolution.THE_400_P)

    # ImageManip for cropping (face detection NN requires input image of 300x300) and to change frame type
    manip = p.create(dai.node.ImageManip)
    manip.initialConfig.setResize(300, 300)
    manip.initialConfig.setFrameType(dai.RawImgFrame.Type.BGR888p)
    mono.out.link(manip.inputImage)
    return manip.out

# NN that detects faces in the image
nn = p.createNeuralNetwork()
nn.setBlobPath(nnPath)
nn.setNumInferenceThreads(2)

camRgb.preview.link(nn.inputs['img2'])
create_mono(p, dai.CameraBoardSocket.CAM_B).link(nn.inputs['img1'])
create_mono(p, dai.CameraBoardSocket.CAM_C).link(nn.inputs['img3'])

# Send bouding box from the NN to the host via XLink
nn_xout = p.createXLinkOut()
nn_xout.setStreamName("nn")
nn.out.link(nn_xout.input)

# Pipeline is defined, now we can connect to the device
with dai.Device(p) as device:
    qNn = device.getOutputQueue(name="nn", maxSize=4, blocking=False)
    shape = (3, SHAPE, SHAPE * 3)

    while True:
        inNn = np.array(qNn.get().getFirstLayerFp16())
        # Planar INT8 frame
        frame = inNn.reshape(shape).astype(np.uint8).transpose(1, 2, 0)

        cv2.imshow("Concat", frame)

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

#### C++

```cpp
#include <chrono>
#include <cstdio>
#include <iostream>

// Inludes common necessary includes for development using depthai library
#include "depthai/depthai.hpp"
#include "utility.hpp"

int main(int argc, char** argv) {
    using namespace std;
    // Default blob path provided by Hunter private data download
    // Applicable for easier example usage only
    std::string nnPath(BLOB_PATH);

    // If path to blob specified, use that
    if(argc > 1) {
        nnPath = std::string(argv[1]);
    }

    // Print which blob we are using
    printf("Using blob at path: %s\n", nnPath.c_str());

    // Create pipeline
    dai::Pipeline pipeline;
    pipeline.setOpenVINOVersion(dai::OpenVINO::Version::VERSION_2021_4);

    // Define sources and outputs
    auto camRgb = pipeline.create<dai::node::ColorCamera>();
    camRgb->setPreviewSize(300, 300);  // NN input
    camRgb->setInterleaved(false);
    camRgb->setColorOrder(dai::ColorCameraProperties::ColorOrder::BGR);

    auto right = pipeline.create<dai::node::MonoCamera>();
    right->setCamera("right");
    right->setResolution(dai::MonoCameraProperties::SensorResolution::THE_400_P);

    auto manipRight = pipeline.create<dai::node::ImageManip>();
    manipRight->initialConfig.setResize(300, 300);
    manipRight->initialConfig.setFrameType(dai::ImgFrame::Type::BGR888p);
    right->out.link(manipRight->inputImage);

    auto left = pipeline.create<dai::node::MonoCamera>();
    left->setCamera("left");
    left->setResolution(dai::MonoCameraProperties::SensorResolution::THE_400_P);

    auto manipLeft = pipeline.create<dai::node::ImageManip>();
    manipLeft->initialConfig.setResize(300, 300);
    manipLeft->initialConfig.setFrameType(dai::ImgFrame::Type::BGR888p);
    left->out.link(manipLeft->inputImage);

    auto nn = pipeline.create<dai::node::NeuralNetwork>();
    nn->setBlobPath(nnPath);
    nn->setNumInferenceThreads(2);

    manipLeft->out.link(nn->inputs["img1"]);
    camRgb->preview.link(nn->inputs["img2"]);
    manipRight->out.link(nn->inputs["img3"]);

    auto xout = pipeline.create<dai::node::XLinkOut>();
    xout->setStreamName("nn");
    nn->out.link(xout->input);

    // Connect to device and start pipeline
    dai::Device device(pipeline);

    // Output queues will be used to get the rgb frames and nn data from the outputs defined above
    auto qNn = device.getOutputQueue("nn", 4, false);

    while(true) {
        auto inNn = qNn->get<dai::NNData>();
        cv::imshow("Concat", fromPlanarFp16(inNn->getFirstLayerFp16(), 900, 300));

        int key = cv::waitKey(1);
        if(key == 'q' || key == 'Q') {
            return 0;
        }
    }
    return 0;
}
```

## Pipeline

### examples/concat_multi_input.pipeline.json

```json
{
  "pipeline": {
    "connections": [
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        "node1Output": "out",
        "node1OutputGroup": "",
        "node2Id": 1,
        "node2Input": "img3",
        "node2InputGroup": "inputs"
      },
      {
        "node1Id": 3,
        "node1Output": "out",
        "node1OutputGroup": "",
        "node2Id": 1,
        "node2Input": "img1",
        "node2InputGroup": "inputs"
      },
      {
        "node1Id": 0,
        "node1Output": "preview",
        "node1OutputGroup": "",
        "node2Id": 1,
        "node2Input": "img2",
        "node2InputGroup": "inputs"
      },
      {
        "node1Id": 2,
        "node1Output": "out",
        "node1OutputGroup": "",
        "node2Id": 3,
        "node2Input": "inputImage",
        "node2InputGroup": ""
      },
      {
        "node1Id": 4,
        "node1Output": "out",
        "node1OutputGroup": "",
        "node2Id": 5,
        "node2Input": "inputImage",
        "node2InputGroup": ""
      },
      {
        "node1Id": 1,
        "node1Output": "out",
        "node1OutputGroup": "",
        "node2Id": 6,
        "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": [
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                "name": "video",
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            [
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              {
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                "name": "isp",
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                "type": 0,
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            ],
            [
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              ],
              {
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                "name": "preview",
                "queueSize": 8,
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            [
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              ],
              {
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                "name": "frameEvent",
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          "name": "ColorCamera",
          "properties": {
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            "colorOrder": 0,
            "fp16": false,
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            "initialControl": {
              "aeLockMode": false,
              "aeMaxExposureTimeUs": 0,
              "aeRegion": {
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                "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,
              "expCompensation": 0,
              "expManual": {
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                "frameDurationUs": 0,
                "sensitivityIso": 0
              },
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              "lensPosAutoInfinity": 0,
              "lensPosAutoMacro": 0,
              "lensPosition": 0,
              "lensPositionRaw": 0.0,
              "lowPowerNumFramesBurst": 0,
              "lowPowerNumFramesDiscard": 0,
              "lumaDenoise": 0,
              "saturation": 0,
              "sceneMode": 0,
              "sharpness": 0,
              "strobeConfig": {
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            "rawPacked": null,
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          }
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              {
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              {
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            ],
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              ],
              {
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                "name": "img3",
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            ],
            [
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              {
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                "name": "passthrough",
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                "type": 0,
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            ]
          ],
          "name": "NeuralNetwork",
          "properties": {
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            "blobUri": "asset:__blob",
            "numFrames": 8,
            "numNCEPerThread": 0,
            "numThreads": 2
          }
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      ],
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          "ioInfo": [
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              {
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              }
            ],
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              {
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                "group": "",
                "id": 16,
                "name": "out",
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            ],
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              {
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                "name": "raw",
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          ],
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        }
      ],
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            ]
          ],
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          "properties": {
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                "cropRect": {
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                },
                "cropRotatedRect": {
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              },
              "enableCrop": false,
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              "enableResize": true,
              "formatConfig": {
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                "colormapMax": 255,
                "colormapMin": 0,
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                "type": 8
              },
              "interpolation": -1,
              "resizeConfig": {
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                "bgGreen": 0,
                "bgRed": 0,
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                "enableWarpMatrix": false,
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                "lockAspectRatioFill": false,
                "normalizedCoords": true,
                "rotationAngleDeg": 0.0,
                "warpBorderReplicate": false,
                "warpFourPoints": [],
                "warpMatrix3x3": [],
                "width": 300
              },
              "reusePreviousImage": false,
              "skipCurrentImage": false
            },
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            "meshUri": "",
            "meshWidth": 0,
            "numFramesPool": 4,
            "outputFrameSize": 1048576
          }
        }
      ],
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            ],
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                "name": "out",
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            ],
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                "name": "frameEvent",
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              }
            ]
          ],
          "name": "MonoCamera",
          "properties": {
            "boardSocket": 2,
            "cameraName": "",
            "fps": 30.0,
            "imageOrientation": -1,
            "initialControl": {
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                "y": 0
              },
              "afRegion": {
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                "priority": 0,
                "width": 0,
                "x": 0,
                "y": 0
              },
              "antiBandingMode": 0,
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              "awbLockMode": false,
              "awbMode": 0,
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              "captureIntent": 0,
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              "contrast": 0,
              "controlMode": 0,
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                "sensitivityIso": 0
              },
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              "lensPosAutoMacro": 0,
              "lensPosition": 0,
              "lensPositionRaw": 0.0,
              "lowPowerNumFramesBurst": 0,
              "lowPowerNumFramesDiscard": 0,
              "lumaDenoise": 0,
              "saturation": 0,
              "sceneMode": 0,
              "sharpness": 0,
              "strobeConfig": {
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                "enable": 0,
                "gpioNumber": 0
              },
              "strobeTimings": {
                "durationUs": 0,
                "exposureBeginOffsetUs": 0,
                "exposureEndOffsetUs": 0
              },
              "wbColorTemp": 0
            },
            "isp3aFps": 0,
            "numFramesPool": 3,
            "numFramesPoolRaw": 3,
            "rawPacked": null,
            "resolution": 2
          }
        }
      ],
      [
        5,
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          "id": 5,
          "ioInfo": [
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              [
                "",
                "inputConfig"
              ],
              {
                "blocking": true,
                "group": "",
                "id": 26,
                "name": "inputConfig",
                "queueSize": 8,
                "type": 3,
                "waitForMessage": false
              }
            ],
            [
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                "",
                "inputImage"
              ],
              {
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                },
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                "warpBorderReplicate": false,
                "warpFourPoints": [],
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              "reusePreviousImage": false,
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            },
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            ]
          ],
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          "properties": {
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        }
      ]
    ]
  }
}
```

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