MobileNetDetectionNetwork

MobileNet detection network node is very similar to NeuralNetwork (in fact it extends it). The only difference is that this node is specifically for the MobileNet NN and it decodes the result of the NN on device. This means that out of this node is not a byte array but a ImgDetections that can easily be used in your code.

How to place it

Python

C++

pipeline = dai.Pipeline()
mobilenetDet = pipeline.create(dai.node.MobileNetDetectionNetwork)

dai::Pipeline pipeline;
auto mobilenetDet = pipeline.create<dai::node::MobileNetDetectionNetwork>();

Inputs and Outputs

            ┌───────────────────┐
            │                   │       out
            │                   ├───────────►
            │     MobileNet     │
            │     Detection     │
input       │     Network       │ passthrough
───────────►│-------------------├───────────►
            │                   │
            └───────────────────┘

Message types

• input - ImgFrame

• out - ImgDetections

• passthrough - ImgFrame

Usage

Python

C++

pipeline = dai.Pipeline()
mobilenetDet = pipeline.create(dai.node.MobileNetDetectionNetwork)

mobilenetDet.setConfidenceThreshold(0.5)
mobilenetDet.setBlobPath(nnBlobPath)
mobilenetDet.setNumInferenceThreads(2)
mobilenetDet.input.setBlocking(False)

dai::Pipeline pipeline;
auto mobilenetDet = pipeline.create<dai::node::MobileNetDetectionNetwork>();

mobilenetDet->setConfidenceThreshold(0.5f);
mobilenetDet->setBlobPath(nnBlobPath);
mobilenetDet->setNumInferenceThreads(2);
mobilenetDet->input.setBlocking(false);

Examples of functionality

• RGB & MobilenetSSD

• Mono & MobilenetSSD

• Mono & MobilenetSSD & Depth

Reference

Python

C++

class depthai.node.MobileNetDetectionNetwork

MobileNetDetectionNetwork node. Parses MobileNet results

class Connection

Connection between an Input and Output

class Id

Node identificator. Unique for every node on a single Pipeline

Properties

alias of depthai.DetectionNetworkProperties

getAssetManager(*args, **kwargs)

Overloaded function.

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

Get node AssetManager as a const reference

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

Get node AssetManager as a const reference

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

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

Returns

Detection confidence

getInputRefs(*args, **kwargs)

Overloaded function.

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

Retrieves reference to node inputs

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

Retrieves reference to node inputs

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

Retrieves all nodes inputs

getName(self: depthai.Node) → str

Retrieves nodes name

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

How many inference threads will be used to run the network

Returns

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

getOutputRefs(*args, **kwargs)

Overloaded function.

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

Retrieves reference to node outputs

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

Retrieves reference to node outputs

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

Retrieves all nodes outputs

getParentPipeline(*args, **kwargs)

Overloaded function.

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

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

property id

Id of node

property input

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

property inputs

Inputs mapped to network inputs. Useful for inferring from separate data sources Default input is non-blocking with queue size 1 and waits for messages

property out

Outputs ImgDetections message that carries parsed detection results. Overrides NeuralNetwork ‘out’ with ImgDetections output message type.

property outNetwork

Outputs unparsed inference results.

property passthrough

Passthrough message on which the inference was performed.

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

property passthroughs

Passthroughs which correspond to specified input

setBlob(*args, **kwargs)

Overloaded function.

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

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

Parameter blob:

Network blob

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

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.

Parameter path:

Path to network blob

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

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.

Parameter path:

Path to network blob

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

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

Parameter thresh:

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

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

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

Parameter numThreads:

Number of threads to dedicate to this node

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

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

Parameter numNCEPerThread:

Number of NCE per thread

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

Specifies how many frames will be available in the pool

Parameter numFrames:

How many frames will pool have

class dai::node::MobileNetDetectionNetwork : public dai::NodeCRTP<DetectionNetwork, MobileNetDetectionNetwork, DetectionNetworkProperties>

MobileNetDetectionNetwork node. Parses MobileNet results.

Public Functions

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

MobileNetDetectionNetwork(const std::shared_ptr<PipelineImpl> &par, int64_t nodeId, std::unique_ptr<Properties> props)

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