Object recognition and localization networks with TensorRT support. More...

#include <detectNet.h>

Inheritance diagram for detectNet:

Classes
struct	Detection
	Object Detection result. More...

Public Types
enum	OverlayFlags { OVERLAY_NONE = 0, OVERLAY_BOX = (1 << 0), OVERLAY_LABEL = (1 << 1) }
	Overlay flags (can be OR'd together). More...

enum	NetworkType { CUSTOM = 0, COCO_AIRPLANE, COCO_BOTTLE, COCO_CHAIR, COCO_DOG, FACENET, PEDNET, PEDNET_MULTI }
	Network choice enumeration. More...

Public Member Functions
virtual	~detectNet ()
	Destory. More...

int	Detect (float input, uint32_t width, uint32_t height, Detection *detections, uint32_t overlay=OVERLAY_BOX)
	Detect object locations from an RGBA image, returning an array containing the detection results. More...

int	Detect (float input, uint32_t width, uint32_t height, Detection detections, uint32_t overlay=OVERLAY_BOX)
	Detect object locations in an RGBA image, into an array of the results allocated by the user. More...

bool	Overlay (float input, float output, uint32_t width, uint32_t height, Detection *detections, uint32_t numDetections, uint32_t flags=OVERLAY_BOX)
	Draw the detected bounding boxes overlayed on an RGBA image. More...

float	GetThreshold () const
	Retrieve the minimum threshold for detection. More...

void	SetThreshold (float threshold)
	Set the minimum threshold for detection. More...

uint32_t	GetMaxDetections () const
	Retrieve the maximum number of simultaneous detections the network supports. More...

uint32_t	GetNumClasses () const
	Retrieve the number of object classes supported in the detector. More...

const char *	GetClassDesc (uint32_t index) const
	Retrieve the description of a particular class. More...

const char *	GetClassSynset (uint32_t index) const
	Retrieve the class synset category of a particular class. More...

const char *	GetClassPath () const
	Retrieve the path to the file containing the class descriptions. More...

void	SetClassColor (uint32_t classIndex, float r, float g, float b, float a=255.0f)
	Set the visualization color of a particular class of object. More...

Public Member Functions inherited from tensorNet
virtual	~tensorNet ()
	Destory. More...

bool	LoadNetwork (const char prototxt, const char model, const char mean=NULL, const char input_blob="data", const char output_blob="prob", uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator calibrator=NULL, cudaStream_t stream=NULL)
	Load a new network instance. More...

bool	LoadNetwork (const char prototxt, const char model, const char mean, const char input_blob, const std::vector< std::string > &output_blobs, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)
	Load a new network instance with multiple output layers. More...

bool	LoadNetwork (const char prototxt, const char model, const char mean, const char input_blob, const Dims3 &input_dims, const std::vector< std::string > &output_blobs, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)
	Load a new network instance (this variant is used for UFF models) More...

void	EnableLayerProfiler ()
	Manually enable layer profiling times. More...

void	EnableDebug ()
	Manually enable debug messages and synchronization. More...

bool	AllowGPUFallback () const
	Return true if GPU fallback is enabled. More...

deviceType	GetDevice () const
	Retrieve the device being used for execution. More...

precisionType	GetPrecision () const
	Retrieve the type of precision being used. More...

bool	IsPrecision (precisionType type) const
	Check if a particular precision is being used. More...

cudaStream_t	GetStream () const
	Retrieve the stream that the device is operating on. More...

cudaStream_t	CreateStream (bool nonBlocking=true)
	Create and use a new stream for execution. More...

void	SetStream (cudaStream_t stream)
	Set the stream that the device is operating on. More...

const char *	GetPrototxtPath () const
	Retrieve the path to the network prototxt file. More...

const char *	GetModelPath () const
	Retrieve the path to the network model file. More...

modelType	GetModelType () const
	Retrieve the format of the network model. More...

bool	IsModelType (modelType type) const
	Return true if the model is of the specified format. More...

float	GetNetworkTime ()
	Retrieve the network runtime (in milliseconds). More...

float2	GetProfilerTime (profilerQuery query)
	Retrieve the profiler runtime (in milliseconds). More...

float	GetProfilerTime (profilerQuery query, profilerDevice device)
	Retrieve the profiler runtime (in milliseconds). More...

void	PrintProfilerTimes ()
	Print the profiler times (in millseconds). More...

Static Public Member Functions
static NetworkType	NetworkTypeFromStr (const char *model_name)
	Parse a string to one of the built-in pretrained models. More...

static detectNet *	Create (NetworkType networkType=PEDNET_MULTI, float threshold=DETECTNET_DEFAULT_THRESHOLD, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)
	Load a new network instance. More...

static detectNet *	Create (const char prototxt_path, const char model_path, const char mean_binary, const char class_labels, float threshold=DETECTNET_DEFAULT_THRESHOLD, const char input=DETECTNET_DEFAULT_INPUT, const char coverage=DETECTNET_DEFAULT_COVERAGE, const char *bboxes=DETECTNET_DEFAULT_BBOX, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)
	Load a custom network instance. More...

static detectNet *	Create (const char prototxt_path, const char model_path, float mean_pixel=0.0f, const char class_labels=NULL, float threshold=DETECTNET_DEFAULT_THRESHOLD, const char input=DETECTNET_DEFAULT_INPUT, const char coverage=DETECTNET_DEFAULT_COVERAGE, const char bboxes=DETECTNET_DEFAULT_BBOX, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)
	Load a custom network instance. More...

static detectNet *	Create (const char model_path, const char class_labels, float threshold, const char input, const Dims3 &inputDims, const char output, const char *numDetections, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)
	Load a custom network instance of a UFF model. More...

static detectNet *	Create (int argc, char **argv)
	Load a new network instance by parsing the command line. More...

static const char *	Usage ()
	Usage string for command line arguments to Create() More...

Static Public Member Functions inherited from tensorNet
static precisionType	FindFastestPrecision (deviceType device=DEVICE_GPU, bool allowInt8=true)
	Determine the fastest native precision on a device. More...

static std::vector< precisionType >	DetectNativePrecisions (deviceType device=DEVICE_GPU)
	Detect the precisions supported natively on a device. More...

static bool	DetectNativePrecision (const std::vector< precisionType > &nativeTypes, precisionType type)
	Detect if a particular precision is supported natively. More...

static bool	DetectNativePrecision (precisionType precision, deviceType device=DEVICE_GPU)
	Detect if a particular precision is supported natively. More...

Protected Member Functions
	detectNet (float meanPixel=0.0f)

bool	allocDetections ()

bool	defaultColors ()

void	defaultClassDesc ()

bool	loadClassDesc (const char *filename)

bool	init (const char prototxt_path, const char model_path, const char mean_binary, const char class_labels, float threshold, const char input, const char coverage, const char *bboxes, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback)

int	clusterDetections (Detection *detections, uint32_t width, uint32_t height)

Protected Member Functions inherited from tensorNet
	tensorNet ()
	Constructor. More...

bool	ProfileModel (const std::string &deployFile, const std::string &modelFile, const char input, const Dims3 &inputDims, const std::vector< std::string > &outputs, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator calibrator, std::ostream &modelStream)
	Create and output an optimized network model. More...

void	PROFILER_BEGIN (profilerQuery query)
	Begin a profiling query, before network is run. More...

void	PROFILER_END (profilerQuery query)
	End a profiling query, after the network is run. More...

bool	PROFILER_QUERY (profilerQuery query)
	Query the CUDA part of a profiler query. More...

Protected Attributes
float	mCoverageThreshold

float *	mClassColors [2]

float	mMeanPixel

std::vector< std::string >	mClassDesc

std::vector< std::string >	mClassSynset

std::string	mClassPath

uint32_t	mCustomClasses

uint32_t	mNumClasses

Detection *	mDetectionSets [2]

uint32_t	mDetectionSet

uint32_t	mMaxDetections

Protected Attributes inherited from tensorNet
tensorNet::Logger	gLogger

tensorNet::Profiler	gProfiler

std::string	mPrototxtPath

std::string	mModelPath

std::string	mMeanPath

std::string	mInputBlobName

std::string	mCacheEnginePath

std::string	mCacheCalibrationPath

deviceType	mDevice

precisionType	mPrecision

modelType	mModelType

cudaStream_t	mStream

cudaEvent_t	mEventsGPU [PROFILER_TOTAL *2]

timespec	mEventsCPU [PROFILER_TOTAL *2]

nvinfer1::IRuntime *	mInfer

nvinfer1::ICudaEngine *	mEngine

nvinfer1::IExecutionContext *	mContext

uint32_t	mWidth

uint32_t	mHeight

uint32_t	mInputSize

float *	mInputCPU

float *	mInputCUDA

float2	mProfilerTimes [PROFILER_TOTAL+1]

uint32_t	mProfilerQueriesUsed

uint32_t	mProfilerQueriesDone

uint32_t	mMaxBatchSize

bool	mEnableProfiler

bool	mEnableDebug

bool	mAllowGPUFallback

Dims3	mInputDims

std::vector< outputLayer >	mOutputs

Static Protected Attributes
static const uint32_t	mNumDetectionSets = 16

Detailed Description

Object recognition and localization networks with TensorRT support.

Member Enumeration Documentation

◆ NetworkType

enum detectNet::NetworkType

Network choice enumeration.

Enumerator
CUSTOM	Custom model from user.
COCO_AIRPLANE	MS-COCO airplane class.
COCO_BOTTLE	MS-COCO bottle class.
COCO_CHAIR	MS-COCO chair class.
COCO_DOG	MS-COCO dog class.
FACENET	Human facial detector trained on FDDB.
PEDNET	Pedestrian / person detector.
PEDNET_MULTI	Multi-class pedestrian + baggage detector.

◆ OverlayFlags

enum detectNet::OverlayFlags

Overlay flags (can be OR'd together).

Enumerator
OVERLAY_NONE	No overlay.
OVERLAY_BOX	Overlay the object bounding boxes.
OVERLAY_LABEL	Overlay the class description labels.

Constructor & Destructor Documentation

◆ ~detectNet()

virtual detectNet::~detectNet ( )

virtual

Destory.

◆ detectNet()

detectNet::detectNet ( float meanPixel = 0.0f )

protected

Member Function Documentation

◆ allocDetections()

bool detectNet::allocDetections ( )

protected

◆ clusterDetections()

int detectNet::clusterDetections	(	Detection *	detections,
		uint32_t	width,
		uint32_t	height
	)

protected

◆ Create() [1/5]

static detectNet* detectNet::Create	(	NetworkType	networkType = `PEDNET_MULTI`,
		float	threshold = `DETECTNET_DEFAULT_THRESHOLD`,
		uint32_t	maxBatchSize = `DEFAULT_MAX_BATCH_SIZE`,
		precisionType	precision = `TYPE_FASTEST`,
		deviceType	device = `DEVICE_GPU`,
		bool	allowGPUFallback = `true`
	)

static

Load a new network instance.

Parameters

networkType	type of pre-supported network to load
threshold	default minimum threshold for detection
maxBatchSize	The maximum batch size that the network will support and be optimized for.

◆ Create() [2/5]

static detectNet* detectNet::Create	(	const char *	prototxt_path,
		const char *	model_path,
		const char *	mean_binary,
		const char *	class_labels,
		float	threshold = `DETECTNET_DEFAULT_THRESHOLD`,
		const char *	input = `DETECTNET_DEFAULT_INPUT`,
		const char *	coverage = `DETECTNET_DEFAULT_COVERAGE`,
		const char *	bboxes = `DETECTNET_DEFAULT_BBOX`,
		uint32_t	maxBatchSize = `DEFAULT_MAX_BATCH_SIZE`,
		precisionType	precision = `TYPE_FASTEST`,
		deviceType	device = `DEVICE_GPU`,
		bool	allowGPUFallback = `true`
	)

static

Load a custom network instance.

Parameters

prototxt_path	File path to the deployable network prototxt
model_path	File path to the caffemodel
mean_binary	File path to the mean value binary proto
class_labels	File path to list of class name labels
threshold	default minimum threshold for detection
input	Name of the input layer blob.
coverage	Name of the output coverage classifier layer blob, which contains the confidence values for each bbox.
bboxes	Name of the output bounding box layer blob, which contains a grid of rectangles in the image.
maxBatchSize	The maximum batch size that the network will support and be optimized for.

◆ Create() [3/5]

static detectNet* detectNet::Create	(	const char *	prototxt_path,
		const char *	model_path,
		float	mean_pixel = `0.0f`,
		const char *	class_labels = `NULL`,
		float	threshold = `DETECTNET_DEFAULT_THRESHOLD`,
		const char *	input = `DETECTNET_DEFAULT_INPUT`,
		const char *	coverage = `DETECTNET_DEFAULT_COVERAGE`,
		const char *	bboxes = `DETECTNET_DEFAULT_BBOX`,
		uint32_t	maxBatchSize = `DEFAULT_MAX_BATCH_SIZE`,
		precisionType	precision = `TYPE_FASTEST`,
		deviceType	device = `DEVICE_GPU`,
		bool	allowGPUFallback = `true`
	)

static

Load a custom network instance.

Parameters

prototxt_path	File path to the deployable network prototxt
model_path	File path to the caffemodel
mean_pixel	Input transform subtraction value (use 0.0 if the network already does this)
class_labels	File path to list of class name labels
threshold	default minimum threshold for detection
input	Name of the input layer blob.
coverage	Name of the output coverage classifier layer blob, which contains the confidence values for each bbox.
bboxes	Name of the output bounding box layer blob, which contains a grid of rectangles in the image.
maxBatchSize	The maximum batch size that the network will support and be optimized for.

◆ Create() [4/5]

static detectNet* detectNet::Create	(	const char *	model_path,
		const char *	class_labels,
		float	threshold,
		const char *	input,
		const Dims3 &	inputDims,
		const char *	output,
		const char *	numDetections,
		uint32_t	maxBatchSize = `DEFAULT_MAX_BATCH_SIZE`,
		precisionType	precision = `TYPE_FASTEST`,
		deviceType	device = `DEVICE_GPU`,
		bool	allowGPUFallback = `true`
	)

static

Load a custom network instance of a UFF model.

Parameters

model_path	File path to the UFF model
class_labels	File path to list of class name labels
threshold	default minimum threshold for detection
input	Name of the input layer blob.
inputDims	Dimensions of the input layer blob.
output	Name of the output layer blob containing the bounding boxes, ect.
numDetections	Name of the output layer blob containing the detection count.
maxBatchSize	The maximum batch size that the network will support and be optimized for.

◆ Create() [5/5]

static detectNet* detectNet::Create	(	int	argc,
		char **	argv
	)

static

Load a new network instance by parsing the command line.

◆ defaultClassDesc()

void detectNet::defaultClassDesc ( )

protected

◆ defaultColors()

bool detectNet::defaultColors ( )

protected

◆ Detect() [1/2]

int detectNet::Detect	(	float *	input,
		uint32_t	width,
		uint32_t	height,
		Detection **	detections,
		uint32_t	overlay = `OVERLAY_BOX`
	)

Detect object locations from an RGBA image, returning an array containing the detection results.

Parameters

[in]	input	float4 RGBA input image in CUDA device memory.
[in]	width	width of the input image in pixels.
[in]	height	height of the input image in pixels.
[out]	detections	pointer that will be set to array of detection results (residing in shared CPU/GPU memory)
[in]	overlay	bitwise OR combination of overlay flags (

See also: OverlayFlags and; Overlay()), or OVERLAY_NONE.

Returns: The number of detected objects, 0 if there were no detected objects, and -1 if an error was encountered.

◆ Detect() [2/2]

int detectNet::Detect	(	float *	input,
		uint32_t	width,
		uint32_t	height,
		Detection *	detections,
		uint32_t	overlay = `OVERLAY_BOX`
	)

Detect object locations in an RGBA image, into an array of the results allocated by the user.

Parameters

[in]	input	float4 RGBA input image in CUDA device memory.
[in]	width	width of the input image in pixels.
[in]	height	height of the input image in pixels.
[out]	detections	pointer to user-allocated array that will be filled with the detection results.

See also: GetMaxDetections() for the number of detection results that should be allocated in this buffer.

Parameters

[in] overlay bitwise OR combination of overlay flags (

See also: OverlayFlags and; Overlay()), or OVERLAY_NONE.

Returns: The number of detected objects, 0 if there were no detected objects, and -1 if an error was encountered.

◆ GetClassDesc()

const char* detectNet::GetClassDesc ( uint32_t index ) const

inline

Retrieve the description of a particular class.

◆ GetClassPath()

const char* detectNet::GetClassPath ( ) const

inline

Retrieve the path to the file containing the class descriptions.

◆ GetClassSynset()

const char* detectNet::GetClassSynset ( uint32_t index ) const

inline

Retrieve the class synset category of a particular class.

◆ GetMaxDetections()

uint32_t detectNet::GetMaxDetections ( ) const

inline

Retrieve the maximum number of simultaneous detections the network supports.

Knowing this is useful for allocating the buffers to store the output detection results.

◆ GetNumClasses()

uint32_t detectNet::GetNumClasses ( ) const

inline

Retrieve the number of object classes supported in the detector.

◆ GetThreshold()

float detectNet::GetThreshold ( ) const

inline

Retrieve the minimum threshold for detection.

TODO: change this to per-class in the future

◆ init()

bool detectNet::init	(	const char *	prototxt_path,
		const char *	model_path,
		const char *	mean_binary,
		const char *	class_labels,
		float	threshold,
		const char *	input,
		const char *	coverage,
		const char *	bboxes,
		uint32_t	maxBatchSize,
		precisionType	precision,
		deviceType	device,
		bool	allowGPUFallback
	)

protected

◆ loadClassDesc()

bool detectNet::loadClassDesc ( const char * filename )

protected

◆ NetworkTypeFromStr()

static NetworkType detectNet::NetworkTypeFromStr ( const char * model_name )

static

Parse a string to one of the built-in pretrained models.

Valid names are "pednet", "multiped", "facenet", "face", "coco-airplane", "airplane", "coco-bottle", "bottle", "coco-chair", "chair", "coco-dog", or "dog".

Returns: one of the detectNet::NetworkType enums, or detectNet::CUSTOM on invalid string.

◆ Overlay()

bool detectNet::Overlay	(	float *	input,
		float *	output,
		uint32_t	width,
		uint32_t	height,
		Detection *	detections,
		uint32_t	numDetections,
		uint32_t	flags = `OVERLAY_BOX`
	)

Draw the detected bounding boxes overlayed on an RGBA image.

Note: Overlay() will automatically be called by default by Detect(), if the overlay parameter is true

Parameters

input	float4 RGBA input image in CUDA device memory.
output	float4 RGBA output image in CUDA device memory.
detections	Array of detections allocated in CUDA device memory.

◆ SetClassColor()

void detectNet::SetClassColor	(	uint32_t	classIndex,
		float	r,
		float	g,
		float	b,
		float	a = `255.0f`
	)

Set the visualization color of a particular class of object.

◆ SetThreshold()

void detectNet::SetThreshold ( float threshold )

inline

Set the minimum threshold for detection.

◆ Usage()

static const char* detectNet::Usage ( )

inlinestatic

Usage string for command line arguments to Create()

Member Data Documentation

◆ mClassColors

float* detectNet::mClassColors[2]

protected

◆ mClassDesc

std::vector<std::string> detectNet::mClassDesc

protected

◆ mClassPath

std::string detectNet::mClassPath

protected

◆ mClassSynset

std::vector<std::string> detectNet::mClassSynset

protected

◆ mCoverageThreshold

float detectNet::mCoverageThreshold

protected

◆ mCustomClasses

uint32_t detectNet::mCustomClasses

protected

◆ mDetectionSet

uint32_t detectNet::mDetectionSet

protected

◆ mDetectionSets

Detection* detectNet::mDetectionSets[2]

protected

◆ mMaxDetections

uint32_t detectNet::mMaxDetections

protected

◆ mMeanPixel

float detectNet::mMeanPixel

protected

◆ mNumClasses

uint32_t detectNet::mNumClasses

protected

◆ mNumDetectionSets

const uint32_t detectNet::mNumDetectionSets = 16

staticprotected

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

jetson-inference/detectNet.h

Classes

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Static Protected Attributes

Detailed Description

Member Enumeration Documentation

◆ NetworkType

◆ OverlayFlags

Constructor & Destructor Documentation

◆ ~detectNet()

◆ detectNet()

Member Function Documentation

◆ allocDetections()

◆ clusterDetections()

◆ Create() [1/5]

◆ Create() [2/5]

◆ Create() [3/5]

◆ Create() [4/5]

◆ Create() [5/5]

◆ defaultClassDesc()

◆ defaultColors()

◆ Detect() [1/2]

◆ Detect() [2/2]

◆ GetClassDesc()

◆ GetClassPath()

◆ GetClassSynset()

◆ GetMaxDetections()

◆ GetNumClasses()

◆ GetThreshold()

◆ init()

◆ loadClassDesc()

◆ NetworkTypeFromStr()

◆ Overlay()

◆ SetClassColor()

◆ SetThreshold()

◆ Usage()

Member Data Documentation

◆ mClassColors

◆ mClassDesc

◆ mClassPath

◆ mClassSynset

◆ mCoverageThreshold

◆ mCustomClasses

◆ mDetectionSet

◆ mDetectionSets

◆ mMaxDetections

◆ mMeanPixel

◆ mNumClasses

◆ mNumDetectionSets