YoloSpatialDetectionNetwork¶
Spatial detection for the Yolo NN. It is similar to a combination of the YoloDetectionNetwork and SpatialLocationCalculator.
How to place it¶
pipeline = dai.Pipeline()
yoloSpatial = pipeline.create(dai.node.YoloSpatialDetectionNetwork)
dai::Pipeline pipeline;
auto yoloSpatial = pipeline.create<dai::node::YoloSpatialDetectionNetwork>();
Inputs and Outputs¶
┌───────────────────┐
input │ │ passthrough
──────────────►│-------------------├─────────────────►
│ Yolo │ out
│ Spatial ├─────────────────►
│ Detection │boundingBoxMapping
│ Network ├─────────────────►
inputDepth │ │ passthroughDepth
──────────────►│-------------------├─────────────────►
└───────────────────┘
Message types
input
- ImgFrameinputDepth
- ImgFramepassthrough
- ImgFrameout
- SpatialImgDetectionsboundingBoxMapping
- SpatialLocationCalculatorConfigpassthroughDepth
- ImgFrame
Usage¶
pipeline = dai.Pipeline()
yoloSpatial = pipeline.create(dai.node.YoloSpatialDetectionNetwork)
yoloSpatial.setBlobPath(nnBlobPath)
# Spatial detection specific parameters
yoloSpatial.setConfidenceThreshold(0.5)
yoloSpatial.input.setBlocking(False)
yoloSpatial.setBoundingBoxScaleFactor(0.5)
yoloSpatial.setDepthLowerThreshold(100) # Min 10 centimeters
yoloSpatial.setDepthUpperThreshold(5000) # Max 5 meters
# Yolo specific parameters
yoloSpatial.setNumClasses(80)
yoloSpatial.setCoordinateSize(4)
yoloSpatial.setAnchors([10,14, 23,27, 37,58, 81,82, 135,169, 344,319])
yoloSpatial.setAnchorMasks({ "side26": [1,2,3], "side13": [3,4,5] })
yoloSpatial.setIouThreshold(0.5)
dai::Pipeline pipeline;
auto yoloSpatial = pipeline.create<dai::node::YoloSpatialDetectionNetwork>();
yoloSpatial->setBlobPath(nnBlobPath);
// Spatial detection specific parameters
yoloSpatial->setConfidenceThreshold(0.5f);
yoloSpatial->input.setBlocking(false);
yoloSpatial->setBoundingBoxScaleFactor(0.5);
yoloSpatial->setDepthLowerThreshold(100); // Min 10 centimeters
yoloSpatial->setDepthUpperThreshold(5000); // Max 5 meters
// yolo specific parameters
yoloSpatial->setNumClasses(80);
yoloSpatial->setCoordinateSize(4);
yoloSpatial->setAnchors({10, 14, 23, 27, 37, 58, 81, 82, 135, 169, 344, 319});
yoloSpatial->setAnchorMasks({{"side13", {3, 4, 5}}, {"side26", {1, 2, 3}}});
yoloSpatial->setIouThreshold(0.5f);
Examples of functionality¶
Reference¶
-
class
depthai.node.
YoloSpatialDetectionNetwork
YoloSpatialDetectionNetwork node. (tiny)Yolov3/v4 based network with spatial location data.
-
class
Connection
Connection between an Input and Output
-
class
Id
Node identificator. Unique for every node on a single Pipeline
-
Properties
-
property
boundingBoxMapping
Outputs mapping of detected bounding boxes relative to depth map
Suitable for when displaying remapped bounding boxes on depth frame
-
getAnchorMasks
(self: depthai.node.YoloSpatialDetectionNetwork) → Dict[str, List[int]] Get anchor masks
-
getAnchors
(self: depthai.node.YoloSpatialDetectionNetwork) → List[float] Get anchors
-
getAssetManager
(*args, **kwargs) Overloaded function.
getAssetManager(self: depthai.Node) -> depthai.AssetManager
Get node AssetManager as a const reference
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
-
getCoordinateSize
(self: depthai.node.YoloSpatialDetectionNetwork) → int Get coordianate size
-
getInputRefs
(*args, **kwargs) Overloaded function.
getInputRefs(self: depthai.Node) -> List[depthai.Node.Input]
Retrieves reference to node inputs
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
-
getIouThreshold
(self: depthai.node.YoloSpatialDetectionNetwork) → float Get Iou threshold
-
getName
(self: depthai.Node) → str Retrieves nodes name
-
getNumClasses
(self: depthai.node.YoloSpatialDetectionNetwork) → int Get num classes
-
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.
getOutputRefs(self: depthai.Node) -> List[depthai.Node.Output]
Retrieves reference to node outputs
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.
getParentPipeline(self: depthai.Node) -> depthai.Pipeline
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
inputDepth
Input message with depth data used to retrieve spatial information about detected object Default queue is non-blocking with size 4
-
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.
-
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
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.
-
property
passthroughs
Passthroughs which correspond to specified input
-
setAnchorMasks
(self: depthai.node.YoloSpatialDetectionNetwork, anchorMasks: Dict[str, List[int]]) → None Set anchor masks
-
setAnchors
(self: depthai.node.YoloSpatialDetectionNetwork, anchors: List[float]) → None Set anchors
-
setBlob
(*args, **kwargs) Overloaded function.
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
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
-
setBoundingBoxScaleFactor
(self: depthai.node.SpatialDetectionNetwork, scaleFactor: float) → None Specifies scale factor for detected bounding boxes.
- Parameter
scaleFactor
: Scale factor must be in the interval (0,1].
- Parameter
-
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
- Parameter
-
setCoordinateSize
(self: depthai.node.YoloSpatialDetectionNetwork, coordinates: int) → None Set coordianate size
-
setDepthLowerThreshold
(self: depthai.node.SpatialDetectionNetwork, lowerThreshold: int) → None Specifies lower threshold in depth units (millimeter by default) for depth values which will used to calculate spatial data
- Parameter
lowerThreshold
: LowerThreshold must be in the interval [0,upperThreshold] and less than upperThreshold.
- Parameter
-
setDepthUpperThreshold
(self: depthai.node.SpatialDetectionNetwork, upperThreshold: int) → None Specifies upper threshold in depth units (millimeter by default) for depth values which will used to calculate spatial data
- Parameter
upperThreshold
: UpperThreshold must be in the interval (lowerThreshold,65535].
- Parameter
-
setIouThreshold
(self: depthai.node.YoloSpatialDetectionNetwork, thresh: float) → None Set Iou threshold
-
setNumClasses
(self: depthai.node.YoloSpatialDetectionNetwork, numClasses: int) → None Set num classes
-
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
- Parameter
-
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
- Parameter
-
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
- Parameter
-
setSpatialCalculationAlgorithm
(self: depthai.node.SpatialDetectionNetwork, calculationAlgorithm: depthai.SpatialLocationCalculatorAlgorithm) → None Specifies spatial location calculator algorithm: Average/Min/Max
- Parameter
calculationAlgorithm
: Calculation algorithm.
- Parameter
-
property
spatialLocationCalculatorOutput
Output of SpatialLocationCalculator node, which is used internally by SpatialDetectionNetwork. Suitable when extra information is required from SpatialLocationCalculator node, e.g. minimum, maximum distance.
-
class
-
class
dai::node
::
YoloSpatialDetectionNetwork
: public dai::NodeCRTP<SpatialDetectionNetwork, YoloSpatialDetectionNetwork, SpatialDetectionNetworkProperties>¶ YoloSpatialDetectionNetwork node. (tiny)Yolov3/v4 based network with spatial location data.
Public Functions
-
void
setNumClasses
(const int numClasses)¶ Set num classes.
-
void
setCoordinateSize
(const int coordinates)¶ Set coordianate size.
-
void
setAnchors
(std::vector<float> anchors)¶ Set anchors.
-
void
setAnchorMasks
(std::map<std::string, std::vector<int>> anchorMasks)¶ Set anchor masks.
-
void
setIouThreshold
(float thresh)¶ Set Iou threshold.
-
int
getNumClasses
() const¶ Get num classes.
-
int
getCoordinateSize
() const¶ Get coordianate size.
-
std::vector<float>
getAnchors
() const¶ Get anchors.
-
std::map<std::string, std::vector<int>>
getAnchorMasks
() const¶ Get anchor masks.
-
float
getIouThreshold
() const¶ Get Iou threshold.
-
void
Got questions?
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