Class SpatialDetectionNetwork

Inheritance Relationships

Base Type

Class Documentation

class SpatialDetectionNetwork : public dai::DeviceNodeGroup

SpatialDetectionNetwork node. Runs a neural inference on input image and calculates spatial location data.

Public Types

using Properties = SpatialDetectionNetworkProperties
using Model = NeuralNetwork::Model

Public Functions

explicit SpatialDetectionNetwork(const std::shared_ptr<Device> &device)
explicit SpatialDetectionNetwork(std::unique_ptr<Properties> props)
SpatialDetectionNetwork(std::unique_ptr<Properties> props, bool confMode)
SpatialDetectionNetwork(const std::shared_ptr<Device> &device, std::unique_ptr<Properties> props, bool confMode)
std::shared_ptr<SpatialDetectionNetwork> build(const std::shared_ptr<Camera> &inputRgb, const DepthSource &depthSource, const Model &model, std::optional<float> fps = std::nullopt, std::optional<dai::ImgResizeMode> resizeMode = std::nullopt)

Build SpatialDetectionNetwork node with specified depth source. Connect Camera and depth source outputs to this node’s inputs and configure the inference model.

Parameters:

  • inputRgb – Camera node

  • depthSource – Depth source node (StereoDepth, NeuralDepth, or ToF)

  • model – Neural network model description, NNArchive or HubAI model id string

  • fps – Desired frames per second

  • resizeMode – Resize mode for input color frames

Returns:

Shared pointer to SpatialDetectionNetwork node

std::shared_ptr<SpatialDetectionNetwork> build(const std::shared_ptr<Camera> &inputRgb, const DepthSource &depthSource, const Model &model, const ImgFrameCapability &capability)

Build SpatialDetectionNetwork node with specified depth source. Connect Camera and depth source outputs to this node’s inputs and configure the inference model.

Parameters:
Returns:

Shared pointer to SpatialDetectionNetwork node

void setNNArchive(const NNArchive &nnArchive)

Set NNArchive for this Node. If the archive’s type is SUPERBLOB, use default number of shaves.

Parameters:

nnArchive – NNArchive to set

void setFromModelZoo(NNModelDescription description, bool useCached = true)

Download model from zoo and set it for this Node.

Parameters:

  • description – Model description to download

  • useCached – Use cached model if available

void setNNArchive(const NNArchive &nnArchive, int numShaves)

Set NNArchive for this Node, throws if the archive’s type is not SUPERBLOB.

Parameters:

  • nnArchive – NNArchive to set

  • numShaves – Number of shaves to use

void setBlobPath(const std::filesystem::path &path)

Backwards compatibility interface Load network blob into assets and use once pipeline is started.

Throws:

Error – if file doesn’t exist or isn’t a valid network blob.

Parameters:

path – Path to network blob

void setBlob(OpenVINO::Blob blob)

Load network blob into assets and use once pipeline is started.

Parameters:

blob – Network blob

void setBlob(const std::filesystem::path &path)

Same functionality as the setBlobPath(). Load network blob into assets and use once pipeline is started.

Throws:

Error – if file doesn’t exist or isn’t a valid network blob.

Parameters:

path – Path to network blob

void setModelPath(const std::filesystem::path &modelPath)

Load network file into assets.

Parameters:

modelPath – Path to the model file.

void setNumPoolFrames(int numFrames)

Specifies how many frames will be available in the pool

Parameters:

numFrames – How many frames will pool have

void setNumInferenceThreads(int numThreads)

How many threads should the node use to run the network.

Parameters:

numThreads – Number of threads to dedicate to this node

void setNumNCEPerInferenceThread(int numNCEPerThread)

How many Neural Compute Engines should a single thread use for inference

Parameters:

numNCEPerThread – Number of NCE per thread

void setNumShavesPerInferenceThread(int numShavesPerThread)

How many Shaves should a single thread use for inference

Parameters:

numShavesPerThread – Number of shaves per thread

void setBackend(std::string backend)

Specifies backend to use

Parameters:

backend – String specifying backend to use

void setBackendProperties(std::map<std::string, std::string> properties)

Set backend properties

Parameters:

backendProperties – backend properties map

int getNumInferenceThreads()

How many inference threads will be used to run the network

Returns:

Number of threads, 0, 1 or 2. Zero means AUTO

void setConfidenceThreshold(float thresh)

Specifies confidence threshold at which to filter the rest of the detections.

Parameters:

thresh – Detection confidence must be greater than specified threshold to be added to the list

float getConfidenceThreshold() const

Retrieves threshold at which to filter the rest of the detections.

Returns:

Detection confidence

void setBoundingBoxScaleFactor(float scaleFactor)

Custom interface Specifies scale factor for detected bounding boxes.

Parameters:

scaleFactor – Scale factor must be in the interval (0,1].

void setDepthLowerThreshold(uint32_t lowerThreshold)

Specifies lower threshold in depth units (millimeter by default) for depth values which will used to calculate spatial data

Parameters:

lowerThreshold – LowerThreshold must be in the interval [0,upperThreshold] and less than upperThreshold.

void setDepthUpperThreshold(uint32_t upperThreshold)

Specifies upper threshold in depth units (millimeter by default) for depth values which will used to calculate spatial data

Parameters:

upperThreshold – UpperThreshold must be in the interval (lowerThreshold,65535].

void setSpatialCalculationAlgorithm(dai::SpatialLocationCalculatorAlgorithm calculationAlgorithm)

Specifies spatial location calculator algorithm: Average/Min/Max

Parameters:

calculationAlgorithm – Calculation algorithm.

void setSpatialCalculationStepSize(int stepSize)

Specifies spatial location calculator step size for depth calculation. Step size 1 means that every pixel is taken into calculation, size 2 means every second etc.

Parameters:

stepSize – Step size.

std::optional<std::vector<std::string>> getClasses() const

Get classes labels.

virtual void buildInternal() override

Function called from within the create function to build the node. This function is useful for initialization, setting up inputs and outputs = stuff that cannot be perform in the constuctor.

Public Members

Properties &properties
Subnode<NeuralNetwork> neuralNetwork = {*this, "neuralNetwork"}
Subnode<DetectionParser> detectionParser = {*this, "detectionParser"}
Subnode<SpatialLocationCalculator> spatialLocationCalculator = {*this, "spatialLocationCalculator"}
std::unique_ptr<Subnode<ImageAlign>> depthAlign
Input &input

Input message with data to be inferred upon Default queue is blocking with size 5

Output &outNetwork

Outputs unparsed inference results.

Output &passthrough

Passthrough message on which the inference was performed.

Suitable for when input queue is set to non-blocking behavior.

Input &inputDepth

Input message with depth data used to retrieve spatial information about detected object Default queue is non-blocking with size 4

Output &out

Outputs ImgDetections message that carries parsed detection results.

Output &passthroughDepth

Passthrough message for depth frame on which the spatial location calculation was performed. Suitable for when input queue is set to non-blocking behavior.

Public Static Functions

static inline std::shared_ptr<SpatialDetectionNetwork> create(const std::shared_ptr<Device> &device)

Public Static Attributes

static constexpr const char *NAME = "SpatialDetectionNetwork"