MobileNetSpatialDetectionNetwork

Spatial detection for the MobileNet NN. It is similar to a combination of the MobileNetDetectionNetwork and SpatialLocationCalculator.

How to place it

Python

C++

pipeline = dai.Pipeline()
mobilenetSpatial = pipeline.create(dai.node.MobileNetSpatialDetectionNetwork)

dai::Pipeline pipeline;
auto mobilenetSpatial = pipeline.create<dai::node::MobileNetSpatialDetectionNetwork>();

Inputs and Outputs

               ┌───────────────────┐
input          │                   │       passthrough
──────────────►│-------------------├─────────────────►
               │     MobileNet     │               out
               │     Spatial       ├─────────────────►
               │     Detection     │boundingBoxMapping
               │     Network       ├─────────────────►
inputDepth     │                   │  passthroughDepth
──────────────►│-------------------├─────────────────►
               └───────────────────┘

Message types

• input - ImgFrame

• inputDepth - ImgFrame

• passthrough - ImgFrame

• out - SpatialImgDetections

• boundingBoxMapping - SpatialLocationCalculatorConfig

• passthroughDepth - ImgFrame

Usage

Python

C++

pipeline = dai.Pipeline()
mobilenetSpatial = pipeline.create(dai.node.MobileNetSpatialDetectionNetwork)

mobilenetSpatial.setBlobPath(nnBlobPath)
# Will ingore all detections whose confidence is below 50%
mobilenetSpatial.setConfidenceThreshold(0.5)
mobilenetSpatial.input.setBlocking(False)
# How big the ROI will be (smaller value can provide a more stable reading)
mobilenetSpatial.setBoundingBoxScaleFactor(0.5)
# Min/Max threshold. Values out of range will be set to 0 (invalid)
mobilenetSpatial.setDepthLowerThreshold(100)
mobilenetSpatial.setDepthUpperThreshold(5000)

# Link depth from the StereoDepth node
stereo.depth.link(mobilenetSpatial.inputDepth)

dai::Pipeline pipeline;
auto mobilenetSpatial = pipeline.create<dai::node::MobileNetSpatialDetectionNetwork>();

mobilenetSpatial->setBlobPath(nnBlobPath);
// Will ingore all detections whose confidence is below 50%
mobilenetSpatial->setConfidenceThreshold(0.5f);
mobilenetSpatial->input.setBlocking(false);
// How big the ROI will be (smaller value can provide a more stable reading)
mobilenetSpatial->setBoundingBoxScaleFactor(0.5f);
// Min/Max threshold. Values out of range will be set to 0 (invalid)
mobilenetSpatial->setDepthLowerThreshold(100);
mobilenetSpatial->setDepthUpperThreshold(5000);

// Link depth from the StereoDepth node
stereo->depth.link(mobilenetSpatial->inputDepth);

Examples of functionality

• RGB & MobilenetSSD with spatial data

• Mono & MobilenetSSD with spatial data

Spatial coordinate system

OAK camera uses left-handed (Cartesian) coordinate system for all spatial coordiantes.

Middle of the frame is 0,0 in terms of X,Y coordinates. If you go up, Y will increase, and if you go right, X will increase.

Reference

Python

C++

class depthai.node.MobileNetSpatialDetectionNetwork

class Id

Node identificator. Unique for every node on a single Pipeline

getAssetManager(*args, **kwargs)

Overloaded function.

1. getAssetManager(self: depthai.Node) -> depthai.AssetManager

2. getAssetManager(self: depthai.Node) -> depthai.AssetManager

getConfidenceThreshold(self: depthai.node.DetectionNetwork) → float

getInputRefs(*args, **kwargs)

Overloaded function.

1. getInputRefs(self: depthai.Node) -> list[depthai.Node.Input]

2. getInputRefs(self: depthai.Node) -> list[depthai.Node.Input]

getInputs(self: depthai.Node) → list[depthai.Node.Input]

getName(self: depthai.Node) → str

getNumInferenceThreads(self: depthai.node.NeuralNetwork) → int

getOutputRefs(*args, **kwargs)

Overloaded function.

1. getOutputRefs(self: depthai.Node) -> list[depthai.Node.Output]

2. getOutputRefs(self: depthai.Node) -> list[depthai.Node.Output]

getOutputs(self: depthai.Node) → list[depthai.Node.Output]

getParentPipeline(*args, **kwargs)

Overloaded function.

1. getParentPipeline(self: depthai.Node) -> depthai.Pipeline

2. getParentPipeline(self: depthai.Node) -> depthai.Pipeline

setBlob(*args, **kwargs)

Overloaded function.

1. setBlob(self: depthai.node.NeuralNetwork, blob: depthai.OpenVINO.Blob) -> None

2. setBlob(self: depthai.node.NeuralNetwork, path: Path) -> None

setBlobPath(self: depthai.node.NeuralNetwork, path: Path) → None

setBoundingBoxScaleFactor(self: depthai.node.SpatialDetectionNetwork, scaleFactor: float) → None

setConfidenceThreshold(self: depthai.node.DetectionNetwork, thresh: float) → None

setDepthLowerThreshold(self: depthai.node.SpatialDetectionNetwork, lowerThreshold: int) → None

setDepthUpperThreshold(self: depthai.node.SpatialDetectionNetwork, upperThreshold: int) → None

setNumInferenceThreads(self: depthai.node.NeuralNetwork, numThreads: int) → None

setNumNCEPerInferenceThread(self: depthai.node.NeuralNetwork, numNCEPerThread: int) → None

setNumPoolFrames(self: depthai.node.NeuralNetwork, numFrames: int) → None

setSpatialCalculationAlgorithm(self: depthai.node.SpatialDetectionNetwork, calculationAlgorithm: depthai.SpatialLocationCalculatorAlgorithm) → None

setSpatialCalculationStepSize(self: depthai.node.SpatialDetectionNetwork, stepSize: int) → None

class dai::node::MobileNetSpatialDetectionNetwork : public dai::NodeCRTP<SpatialDetectionNetwork, MobileNetSpatialDetectionNetwork, SpatialDetectionNetworkProperties>

MobileNetSpatialDetectionNetwork node. Mobilenet-SSD based network with spatial location data.

Public Functions

MobileNetSpatialDetectionNetwork(const std::shared_ptr<PipelineImpl> &par, int64_t nodeId)

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