DetectorDNNOpenCV¶

class DetectorDNNOpenCV(self)¶

Bases: pybind11_object

Methods

__init__
detect	Overloaded function.
dnnResultsParsingTypeFromString
dnnResultsParsingTypeToString
getAvailableDnnResultsParsingTypes
getNetConfig
parseClassNamesFile
readNet
setConfidenceThreshold
setDetectionFilterSizeRatio
setInputSize
setMean
setNMSThreshold
setNetConfig
setPreferableBackend
setPreferableTarget
setScaleFactor
setSwapRB

Inherited Methods

Operators

__doc__
__init__
__module__
__repr__

Attributes

COUNT
FASTER_RCNN
RESNET_10
SSD_MOBILENET
USER_SPECIFIED
YOLO_V3
YOLO_V4
YOLO_V5
YOLO_V7
YOLO_V8
__annotations__

__init__(self)¶

detect(*args, **kwargs)¶

Overloaded function.

1. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: visp._visp.core.ImageGray, output: list[vpDetectorDNNOpenCV::DetectedFeatures2D]) -> tuple[bool, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]

2. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: visp._visp.core.ImageGray, output: dict[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]) -> bool

3. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: visp._visp.core.ImageGray, output: list[tuple[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]]) -> tuple[bool, list[tuple[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]]]

4. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: visp._visp.core.ImageRGBa, output: list[vpDetectorDNNOpenCV::DetectedFeatures2D]) -> tuple[bool, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]

5. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: visp._visp.core.ImageRGBa, output: dict[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]) -> bool

6. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: visp._visp.core.ImageRGBa, output: list[tuple[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]]) -> tuple[bool, list[tuple[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]]]

7. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: cv::Mat, output: list[vpDetectorDNNOpenCV::DetectedFeatures2D]) -> tuple[bool, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]

8. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: cv::Mat, output: dict[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]) -> bool

9. detect(self: visp._visp.detection.DetectorDNNOpenCV, I: cv::Mat, output: list[tuple[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]]) -> tuple[bool, list[tuple[str, list[vpDetectorDNNOpenCV::DetectedFeatures2D]]]]

static dnnResultsParsingTypeFromString(name: str) → visp._visp.detection.DetectorDNNOpenCV.DNNResultsParsingType¶

static dnnResultsParsingTypeToString(type: visp._visp.detection.DetectorDNNOpenCV.DNNResultsParsingType) → str¶

static getAvailableDnnResultsParsingTypes() → str¶

getNetConfig(self) → vpDetectorDNNOpenCV::NetConfig¶

static parseClassNamesFile(filename: str) → list[str]¶

readNet(self: visp._visp.detection.DetectorDNNOpenCV, model: str, config: str =, framework: str =) → None¶

setConfidenceThreshold(self, confThreshold: float) → None¶

setDetectionFilterSizeRatio(self, sizeRatio: float) → None¶

setInputSize(self, width: int, height: int) → None¶

setMean(self, meanR: float, meanG: float, meanB: float) → None¶

setNMSThreshold(self, nmsThreshold: float) → None¶

setNetConfig(self: visp._visp.detection.DetectorDNNOpenCV, config: vpDetectorDNNOpenCV::NetConfig) → None¶

setPreferableBackend(self, backendId: int) → None¶

setPreferableTarget(self, targetId: int) → None¶

setScaleFactor(self, scaleFactor: float) → None¶

setSwapRB(self, swapRB: bool) → None¶