#include <DnnDetector_ParamsParser.h>

Inheritance diagram for DnnDetector_ParamsParser:

Classes
struct	parser_version_type

Public Member Functions
bool	parseParams (const yarp::os::Searchable &config) override

std::string	getDeviceClassName () const override

std::string	getDeviceName () const override

std::string	getDocumentationOfDeviceParams () const override

std::vector< std::string >	getListOfParams () const override

Public Attributes
const std::string	m_device_classname = {"DnnDetector"}

const std::string	m_device_name = {"DnnDetector"}

bool	m_parser_is_strict = false

const parser_version_type	m_parser_version = {}

const std::string	m_trainedModel_defaultValue = {"yolov3-tiny/yolov3-tiny.weights"}

const std::string	m_configDNNModel_defaultValue = {"yolov3-tiny/yolov3-tiny.cfg"}

const std::string	m_framework_defaultValue = {"darknet"}

const std::string	m_classesTrainedModel_defaultValue = {"coco-object-categories.txt"}

const std::string	m_backend_defaultValue = {"cuda"}

const std::string	m_target_defaultValue = {"cpu"}

const std::string	m_scale_defaultValue = {"0.00392"}

const std::string	m_mean_defaultValue = {"0.0"}

const std::string	m_confThreshold_defaultValue = {"0.1"}

const std::string	m_nmsThreshold_defaultValue = {"0.4"}

std::string	m_trainedModel = {"yolov3-tiny/yolov3-tiny.weights"}

std::string	m_configDNNModel = {"yolov3-tiny/yolov3-tiny.cfg"}

std::string	m_framework = {"darknet"}

std::string	m_classesTrainedModel = {"coco-object-categories.txt"}

std::string	m_backend = {"cuda"}

std::string	m_target = {"cpu"}

float	m_scale = {0.00392}

double	m_mean = {0.0}

float	m_confThreshold = {0.1}

float	m_nmsThreshold = {0.4}

Detailed Description

This class is the parameters parser for class DnnDetector.

These are the used parameters:

Group name	Parameter name	Type	Units	Default Value	Description	Notes
-	trainedModel	string	-	yolov3-tiny/yolov3-tiny.weights	trained model file	-
-	configDNNModel	string	-	yolov3-tiny/yolov3-tiny.cfg	configuration file	-
-	framework	string	-	darknet	framework	-
-	classesTrainedModel	string	-	coco-object-categories.txt	file with trained classes	-
-	backend	string	-	cuda	backend	default, opencv, cuda
-	target	string	-	cpu	target device	cpu, opencl, cuda
-	scale	float	-	0.00392	scale	-
-	mean	double	-	0.0	mean	-
-	confThreshold	float	-	0.1	confidence threshold	-
-	nmsThreshold	float	-	0.4	non maximum suppression threshold	-

The device can be launched by yarpdev using one of the following examples (with and without all optional parameters):

yarpdev --device DnnDetector --trainedModel yolov3-tiny/yolov3-tiny.weights --configDNNModel yolov3-tiny/yolov3-tiny.cfg --framework darknet --classesTrainedModel coco-object-categories.txt --backend cuda --target cpu --scale 0.00392 --mean 0.0 --confThreshold 0.1 --nmsThreshold 0.4

yarpdev --device DnnDetector

The documentation for this class was generated from the following files:

libraries/YarpPlugins/DnnDetector/DnnDetector_ParamsParser.h
libraries/YarpPlugins/DnnDetector/DnnDetector_ParamsParser.cpp

Classes

Public Member Functions

Public Attributes

Detailed Description