Detect salient objects and identify them using Darknet deep neural network. More...

Inheritance diagram for DarknetSaliency:

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Collaboration diagram for DarknetSaliency:

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Public Member Functions
	DarknetSaliency (std::string const &instance)
	Constructor.

virtual	~DarknetSaliency ()
	Virtual destructor for safe inheritance.

virtual void	postUninit () override
	Un-initialization.

virtual void	getSalROI (jevois::RawImage const &inimg, int &rx, int &ry, int &rw, int &rh)
	Helper function: compute saliency ROI in a thread, return top-left corner and size.

virtual void	process (jevois::InputFrame &&inframe) override
	Processing function, no video output.

virtual void	process (jevois::InputFrame &&inframe, jevois::OutputFrame &&outframe) override
	Processing function with video output to USB.

Public Member Functions inherited from jevois::StdModule
	StdModule (std::string const &instance)

virtual	~StdModule ()

void	sendSerialImg1Dx (unsigned int camw, float x, float size=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialStd1Dx (float x, float size=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialImg1Dy (unsigned int camh, float y, float size=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialStd1Dy (float y, float size=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialImg2D (unsigned int camw, unsigned int camh, float x, float y, float w=0.0F, float h=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialStd2D (float x, float y, float w=0.0F, float h=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialContour2D (unsigned int camw, unsigned int camh, std::vector< cv::Point_< T > > points, std::string const &id="", std::string const &extra="")

void	sendSerialStd3D (float x, float y, float z, float w=0.0F, float h=0.0F, float d=0.0F, float q1=0.0F, float q2=0.0F, float q3=0.0f, float q4=0.0F, std::string const &id="", std::string const &extra="")

void	sendSerialStd3D (std::vector< cv::Point3f > points, std::string const &id="", std::string const &extra="")

void	sendSerialObjReco (std::vector< ObjReco > const &res)

void	sendSerialObjDetImg2D (unsigned int camw, unsigned int camh, float x, float y, float w, float h, std::vector< ObjReco > const &res)

void	sendSerialObjDetImg2D (unsigned int camw, unsigned int camh, ObjDetect const &det)

void	sendSerialObjDetImg2D (unsigned int camw, unsigned int camh, ObjDetectOBB const &det)

	JEVOIS_DEFINE_ENUM_CLASS (SerStyle,(Terse)(Normal)(Detail)(Fine))

	JEVOIS_DECLARE_PARAMETER (serstyle, SerStyle, "Style for standardized serial messages as defined in " "http://jevois.org/doc/UserSerialStyle.html", SerStyle::Terse, SerStyle_Values, ParamCateg)

	JEVOIS_DECLARE_PARAMETER (serprec, unsigned int, "Number of decimal points in standardized serial messages as " "defined in http://jevois.org/doc/UserSerialStyle.html", 0U, jevois::Range< unsigned int >(0U, 10U), ParamCateg)

	JEVOIS_DEFINE_ENUM_CLASS (SerStamp,(None)(Frame)(Time)(FrameTime)(FrameDateTime))

	JEVOIS_DECLARE_PARAMETER (serstamp, SerStamp, "Prepend standardized serial messages with a frame number, " "time, frame+time, or frame+date+time. See details in " "http://jevois.org/doc/UserSerialStyle.html", SerStamp::None, SerStamp_Values, ParamCateg)

	JEVOIS_DEFINE_ENUM_CLASS (SerMark,(None)(Start)(Stop)(Both))

	JEVOIS_DECLARE_PARAMETER (sermark, SerMark, "Send serial message to mark the beginning (MARK START) of the " "processing of a video frame from the camera sensor, the end (MARK STOP), or both. " "Useful, among others, if one needs to know when no results were sent over serial " "on a given frame. Combine with parameter serstamp if you need to know the frame number.", SerMark::None, SerMark_Values, ParamCateg)

Public Member Functions inherited from jevois::Module
	Module (std::string const &instance)

virtual	~Module ()

virtual void	process (InputFrame &&inframe, GUIhelper &helper)

virtual void	sendSerial (std::string const &str)

virtual void	parseSerial (std::string const &str, std::shared_ptr< UserInterface > s)

virtual void	supportedCommands (std::ostream &os)

Public Member Functions inherited from jevois::Component
	Component (std::string const &instance)

virtual	~Component ()

std::shared_ptr< Comp >	addSubComponent (std::string const &instance, Args &&...args)

void	removeSubComponent (std::shared_ptr< Comp > &component)

void	removeSubComponent (std::string const &instance, bool warnIfNotFound=true)

std::shared_ptr< Comp >	getSubComponent (std::string const &instance) const

bool	isTopLevel () const

bool	initialized () const

std::string const &	className () const

std::string const &	instanceName () const

std::vector< std::string >	setParamVal (std::string const &paramdescriptor, T const &val)

void	setParamValUnique (std::string const &paramdescriptor, T const &val)

std::vector< std::pair< std::string, T > >	getParamVal (std::string const &paramdescriptor) const

T	getParamValUnique (std::string const &paramdescriptor) const

std::vector< std::string >	setParamString (std::string const &paramdescriptor, std::string const &val)

void	setParamStringUnique (std::string const &paramdescriptor, std::string const &val)

std::vector< std::pair< std::string, std::string > >	getParamString (std::string const &paramdescriptor) const

std::string	getParamStringUnique (std::string const &paramdescriptor) const

void	freezeParam (std::string const &paramdescriptor, bool doit)

void	freezeAllParams (bool doit)

std::string	descriptor () const

void	setParamsFromFile (std::string const &filename)

std::istream &	setParamsFromStream (std::istream &is, std::string const &absfile)

virtual void	paramInfo (std::shared_ptr< UserInterface > s, std::map< std::string, std::string > &categs, bool skipFrozen, std::string const &cname="", std::string const &pfx="")

void	foreachParam (std::function< void(std::string const &compname, ParameterBase *p)> func, std::string const &cname="")

std::shared_ptr< DynamicParameter< T > >	addDynamicParameter (std::string const &name, std::string const &description, T const &defaultValue, ParameterCategory const &category)

std::shared_ptr< DynamicParameter< T > >	addDynamicParameter (std::string const &name, std::string const &description, T const &defaultValue, ValidValuesSpec< T > const &validValuesSpec, ParameterCategory const &category)

void	setDynamicParameterCallback (std::string const &name, std::function< void(T const &)> cb, bool callnow=true)

void	removeDynamicParameter (std::string const &name, bool throw_if_not_found=true)

void	setPath (std::string const &path)

std::filesystem::path	absolutePath (std::filesystem::path const &path="")

std::shared_ptr< Comp >	addSubComponent (std::string const &instance, Args &&...args)

void	removeSubComponent (std::shared_ptr< Comp > &component)

void	removeSubComponent (std::string const &instance, bool warnIfNotFound=true)

std::shared_ptr< Comp >	getSubComponent (std::string const &instance) const

bool	isTopLevel () const

bool	initialized () const

std::string const &	className () const

std::string const &	instanceName () const

std::vector< std::string >	setParamVal (std::string const &paramdescriptor, T const &val)

void	setParamValUnique (std::string const &paramdescriptor, T const &val)

std::vector< std::pair< std::string, T > >	getParamVal (std::string const &paramdescriptor) const

T	getParamValUnique (std::string const &paramdescriptor) const

std::vector< std::string >	setParamString (std::string const &paramdescriptor, std::string const &val)

void	setParamStringUnique (std::string const &paramdescriptor, std::string const &val)

std::vector< std::pair< std::string, std::string > >	getParamString (std::string const &paramdescriptor) const

std::string	getParamStringUnique (std::string const &paramdescriptor) const

void	freezeParam (std::string const &paramdescriptor, bool doit)

void	freezeAllParams (bool doit)

std::string	descriptor () const

void	setParamsFromFile (std::string const &filename)

std::istream &	setParamsFromStream (std::istream &is, std::string const &absfile)

virtual void	paramInfo (std::shared_ptr< UserInterface > s, std::map< std::string, std::string > &categs, bool skipFrozen, std::string const &cname="", std::string const &pfx="")

void	foreachParam (std::function< void(std::string const &compname, ParameterBase *p)> func, std::string const &cname="")

std::shared_ptr< DynamicParameter< T > >	addDynamicParameter (std::string const &name, std::string const &description, T const &defaultValue, ParameterCategory const &category)

std::shared_ptr< DynamicParameter< T > >	addDynamicParameter (std::string const &name, std::string const &description, T const &defaultValue, ValidValuesSpec< T > const &validValuesSpec, ParameterCategory const &category)

void	setDynamicParameterCallback (std::string const &name, std::function< void(T const &)> cb, bool callnow=true)

void	removeDynamicParameter (std::string const &name, bool throw_if_not_found=true)

void	setPath (std::string const &path)

std::filesystem::path	absolutePath (std::filesystem::path const &path="")

Public Member Functions inherited from jevois::ParameterRegistry
virtual	~ParameterRegistry ()

Protected Attributes
std::shared_ptr< Saliency >	itsSaliency

std::shared_ptr< Darknet >	itsDarknet

std::vector< jevois::ObjReco >	itsResults

std::future< float >	itsPredictFut

cv::Mat	itsRawInputCv

cv::Mat	itsCvImg

cv::Mat	itsRawPrevOutputCv

Related Symbols
(Note that these are not member symbols.)
	JEVOIS_DECLARE_PARAMETER (foa, cv::Size, "Width and height (in pixels) of the focus of attention. " "This is the size of the image crop that is taken around the most salient " "location in each frame. The foa size must fit within the camera input frame size.", cv::Size(128, 128), ParamCateg)
	Parameter.

	JEVOIS_DECLARE_PARAMETER (netin, cv::Size, "Width and height (in pixels) of the neural network input " "layer. This is the size to which the image crop taken around the most salient " "location in each frame will be rescaled before feeding to the neural network.", cv::Size(128, 128), ParamCateg)
	Parameter.

Additional Inherited Members
Protected Member Functions inherited from jevois::StdModule
void	sendSerialMarkStart ()

void	sendSerialMarkStop ()

std::string	getStamp () const

Protected Member Functions inherited from jevois::Component
virtual void	preInit ()

virtual void	postInit ()

virtual void	preUninit ()

virtual void	preInit ()

virtual void	postInit ()

virtual void	preUninit ()

Protected Member Functions inherited from jevois::ParameterRegistry
void	addParameter (ParameterBase *const param)

void	removeParameter (ParameterBase *const param)

void	callbackInitCall ()

Detailed Description

Detect salient objects and identify them using Darknet deep neural network.

Darknet is a popular neural network framework. This module first finds the most conspicuous (salient) object in the scene, then identifies it using a deep neural network. It returns the top scoring candidates.

See http://ilab.usc.edu/bu/ for more information about saliency detection, and https://pjreddie.com/darknet for more information about the Darknet deep neural network framework.

This module runs a Darknet network on an image window around the most salient point and shows the top-scoring results. The network is currently a bit slow, hence it is only run once in a while. Point your camera towards some interesting object, and wait for Darknet to tell you what it found. The framerate figures shown at the bottom left of the display reflect the speed at which each new video frame from the camera is processed, but in this module this just amounts to computing the saliency map from the camera input, converting the input image to RGB, cropping it around the most salient location, sending it to the neural network for processing in a separate thread, and creating the demo display. Actual network inference speed (time taken to compute the predictions on one image crop) is shown at the bottom right. See below for how to trade-off speed and accuracy.

Note that by default this module runs the Imagenet1k tiny Darknet (it can also run the slightly slower but a bit more accurate Darknet Reference network; see parameters). There are 1000 different kinds of objects (object classes) that this network can recognize (too long to list here).

Sometimes it will make mistakes! The performance of darknet-tiny is about 58.7% correct (mean average precision) on the test set, and Darknet Reference is about 61.1% correct on the test set. This is when running these networks at 224x224 network input resolution (see parameter netin below).

Neural network size and speed

When using networks that are fully convolutional (as is the case for the default networks provided with this module), one can resize the network to any desired input size. The network size direcly affects both speed and accuracy. Larger networks run slower but are more accurate.

This module provides two parameters that allow you to adjust this tradeoff:

foa determines the size of a region of interest that is cropped around the most salient location
netin determines the size to which that region of interest is rescaled and fed to the neural network

For example:

with netin = (224 224), this module runs at about 450ms/prediction.
with netin = (128 128), this module runs at about 180ms/prediction.

Finally note that, when using video mappings with USB output, irrespective of foa and netin, the crop around the most salient image region (with size given by foa) will always also be rescaled so that, when placed to the right of the input image, it fills the desired USB output dims. For example, if camera mode is 320x240 and USB output size is 544x240, then the attended and recognized object will be rescaled to 224x224 (since 224 = 544-320) for display purposes only. This is so that one does not need to change USB video resolution while playing with different values of foa and netin live.

Serial messages

On every frame where detection results were obtained that are above thresh, this module sends a standardized 2D message as specified in Standardized serial messages formatting

Serial message type: 2D
id: top-scoring category name of the recognized object, followed by ':' and the confidence score in percent
x, y, or vertices: standardized 2D coordinates of object center or corners
w, h: standardized object size
extra: any number of additional category:score pairs which had an above-threshold score, in order of decreasing score where category is the category name (from namefile) and score is the confidence score from 0.0 to 100.0

See Standardized serial messages formatting for more on standardized serial messages, and Helper functions to convert coordinates from camera resolution to standardized for more info on standardized coordinates.

Author: Laurent Itti

Display Name:: Darknet Saliency

Videomapping:: NONE 0 0 0.0 YUYV 320 240 5.0 JeVois DarknetSaliency

Videomapping:: YUYV 460 240 15.0 YUYV 320 240 15.0 JeVois DarknetSaliency # not for mac (width not multiple of 16)

Videomapping:: YUYV 560 240 15.0 YUYV 320 240 15.0 JeVois DarknetSaliency

Videomapping:: YUYV 880 480 15.0 YUYV 640 480 15.0 JeVois DarknetSaliency # set foa param to 256 256

Email:: itti@usc.edu

Address:: University of Southern California, HNB-07A, 3641 Watt Way, Los Angeles, CA 90089-2520, USA

Copyright: Copyright (C) 2017 by Laurent Itti, iLab and the University of Southern California

Main URL:: http://jevois.org

Support URL:: http://jevois.org/doc

Other URL:: http://iLab.usc.edu

License:: GPL v3

Distribution:: Unrestricted

Restrictions:: None

Definition at line 126 of file DarknetSaliency.C.

Constructor & Destructor Documentation

◆ DarknetSaliency()

DarknetSaliency::DarknetSaliency ( std::string const & instance )

inline

Constructor.

Definition at line 133 of file DarknetSaliency.C.

References itsDarknet, and itsSaliency.

◆ ~DarknetSaliency()

virtual DarknetSaliency::~DarknetSaliency ( )

inlinevirtual

Virtual destructor for safe inheritance.

Definition at line 142 of file DarknetSaliency.C.

Member Function Documentation

◆ getSalROI()

virtual void DarknetSaliency::getSalROI	(	jevois::RawImage const &	inimg,
		int &	rx,
		int &	ry,
		int &	rw,
		int &	rh
	)

inlinevirtual

Helper function: compute saliency ROI in a thread, return top-left corner and size.

Definition at line 156 of file DarknetSaliency.C.

References h, jevois::RawImage::height, itsSaliency, and jevois::RawImage::width.

Referenced by process(), and process().

◆ postUninit()

virtual void DarknetSaliency::postUninit ( )

inlineoverridevirtual

Un-initialization.

Reimplemented from jevois::Component.

Definition at line 148 of file DarknetSaliency.C.

References itsPredictFut.

◆ process() [1/2]

virtual void DarknetSaliency::process ( jevois::InputFrame && inframe )

inlineoverridevirtual

Processing function, no video output.

Reimplemented from jevois::Module.

Definition at line 189 of file DarknetSaliency.C.

References jevois::rawimage::cvImage(), getSalROI(), h, jevois::RawImage::height, itsDarknet, itsResults, LINFO, jevois::rescaleCv(), jevois::StdModule::sendSerialObjDetImg2D(), and jevois::RawImage::width.

◆ process() [2/2]

virtual void DarknetSaliency::process	(	jevois::InputFrame &&	inframe,
		jevois::OutputFrame &&	outframe
	)

inlineoverridevirtual

Processing function with video output to USB.

Reimplemented from jevois::Module.

Definition at line 232 of file DarknetSaliency.C.

References jevois::async(), jevois::yuyv::Black, jevois::rawimage::convertCvRGBtoCvYUYV(), jevois::rawimage::cvImage(), jevois::rawimage::drawFilledRect(), jevois::rawimage::drawRect(), getSalROI(), h, jevois::RawImage::height, itsCvImg, itsDarknet, itsPredictFut, itsRawInputCv, itsRawPrevOutputCv, itsResults, jevois::yuyv::LightPink, jevois::rawimage::paste(), jevois::RawImage::require(), jevois::rescaleCv(), jevois::StdModule::sendSerialObjDetImg2D(), jevois::sformat(), jevois::Timer::start(), jevois::Timer::stop(), success, jevois::yuyv::White, jevois::RawImage::width, and jevois::rawimage::writeText().

Friends And Related Symbol Documentation

◆ JEVOIS_DECLARE_PARAMETER() [1/2]

JEVOIS_DECLARE_PARAMETER	(	foa	,
		cv::Size	,
		"Width and height (in pixels) of the focus of attention. " "This is the size of the image crop that is taken around the most salient " "location in each frame. The foa size must fit within the camera input frame size."	,
		cv::Size(128, 128)	,
		ParamCateg
	)

◆ JEVOIS_DECLARE_PARAMETER() [2/2]

JEVOIS_DECLARE_PARAMETER	(	netin	,
		cv::Size	,
		"Width and height (in pixels) of the neural network input " "layer. This is the size to which the image crop taken around the most salient " "location in each frame will be rescaled before feeding to the neural network."	,
		cv::Size(128, 128)	,
		ParamCateg
	)

Member Data Documentation

◆ itsCvImg

cv::Mat DarknetSaliency::itsCvImg

protected

Definition at line 382 of file DarknetSaliency.C.

Referenced by process().

◆ itsDarknet

std::shared_ptr<Darknet> DarknetSaliency::itsDarknet

protected

Definition at line 378 of file DarknetSaliency.C.

Referenced by DarknetSaliency(), process(), and process().

◆ itsPredictFut

std::future<float> DarknetSaliency::itsPredictFut

protected

Definition at line 380 of file DarknetSaliency.C.

Referenced by postUninit(), and process().

◆ itsRawInputCv

cv::Mat DarknetSaliency::itsRawInputCv

protected

Definition at line 381 of file DarknetSaliency.C.

Referenced by process().

◆ itsRawPrevOutputCv

cv::Mat DarknetSaliency::itsRawPrevOutputCv

protected

Definition at line 383 of file DarknetSaliency.C.

Referenced by process().

◆ itsResults

std::vector<jevois::ObjReco> DarknetSaliency::itsResults

protected

Definition at line 379 of file DarknetSaliency.C.

Referenced by process(), and process().

◆ itsSaliency

std::shared_ptr<Saliency> DarknetSaliency::itsSaliency

protected

Definition at line 377 of file DarknetSaliency.C.

Referenced by DarknetSaliency(), and getSalROI().

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

src/Modules/DarknetSaliency/DarknetSaliency.C

Public Member Functions

Protected Attributes

Related Symbols

Additional Inherited Members

Detailed Description

Neural network size and speed

Serial messages

Constructor & Destructor Documentation

◆ DarknetSaliency()

◆ ~DarknetSaliency()

Member Function Documentation

◆ getSalROI()

◆ postUninit()

◆ process() [1/2]

◆ process() [2/2]

Friends And Related Symbol Documentation

◆ JEVOIS_DECLARE_PARAMETER() [1/2]

◆ JEVOIS_DECLARE_PARAMETER() [2/2]

Member Data Documentation

◆ itsCvImg

◆ itsDarknet

◆ itsPredictFut

◆ itsRawInputCv

◆ itsRawPrevOutputCv

◆ itsResults

◆ itsSaliency