Image recognition with classification networks, using TensorRT. More...

#include <imageNet.h>

Inheritance diagram for imageNet:

Public Types
enum	NetworkType { CUSTOM, ALEXNET, GOOGLENET, GOOGLENET_12, RESNET_18, RESNET_50, RESNET_101, RESNET_152, VGG_16, VGG_19, INCEPTION_V4 }
	Network choice enumeration. More...

Public Member Functions
virtual	~imageNet ()
	Destroy. More...

int	Classify (float rgba, uint32_t width, uint32_t height, float confidence=NULL)
	Determine the maximum likelihood image class. More...

int	Classify (float *confidence=NULL)
	Determine the maximum likelihood image class. More...

bool	PreProcess (float *rgba, uint32_t width, uint32_t height)
	Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCHW format and BGR colorspace that the networks expect. More...

bool	Process ()
	Process the network, without determining the classification argmax. More...

uint32_t	GetNumClasses () const
	Retrieve the number of image recognition classes (typically 1000) 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...

NetworkType	GetNetworkType () const
	Retrieve the network type (alexnet or googlenet) More...

const char *	GetNetworkName () const
	Retrieve a string describing the network name. 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 const char *	NetworkTypeToStr (NetworkType network)
	Convert a NetworkType enum to a string. More...

static imageNet *	Create (NetworkType networkType=GOOGLENET, 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 imageNet *	Create (const char prototxt_path, const char model_path, const char mean_binary, const char class_labels, const char input=IMAGENET_DEFAULT_INPUT, const char output=IMAGENET_DEFAULT_OUTPUT, 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 imageNet *	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
	imageNet ()

bool	init (NetworkType networkType, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback)

bool	init (const char prototxt_path, const char model_path, const char mean_binary, const char class_path, const char input, const char output, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback)

bool	loadClassInfo (const char *filename)

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
uint32_t	mCustomClasses

uint32_t	mOutputClasses

std::vector< std::string >	mClassSynset

std::vector< std::string >	mClassDesc

std::string	mClassPath

NetworkType	mNetworkType

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

Detailed Description

Image recognition with classification networks, using TensorRT.

Member Enumeration Documentation

◆ NetworkType

enum imageNet::NetworkType

Network choice enumeration.

Enumerator
CUSTOM	Custom model provided by the user.
ALEXNET	AlexNet trained on 1000-class ILSVRC12.
GOOGLENET	GoogleNet trained 1000-class ILSVRC12.
GOOGLENET_12	GoogleNet trained on 12-class subset of ImageNet ILSVRC12 from the tutorial.
RESNET_18	ResNet-18 trained on 1000-class ILSVRC15.
RESNET_50	ResNet-50 trained on 1000-class ILSVRC15.
RESNET_101	ResNet-101 trained on 1000-class ILSVRC15.
RESNET_152	ResNet-50 trained on 1000-class ILSVRC15.
VGG_16	VGG-16 trained on 1000-class ILSVRC14.
VGG_19	VGG-19 trained on 1000-class ILSVRC14.
INCEPTION_V4	Inception-v4 trained on 1000-class ILSVRC12.

Constructor & Destructor Documentation

◆ ~imageNet()

virtual imageNet::~imageNet ( )

virtual

Destroy.

◆ imageNet()

imageNet::imageNet ( )

protected

Member Function Documentation

◆ Classify() [1/2]

int imageNet::Classify	(	float *	rgba,
		uint32_t	width,
		uint32_t	height,
		float *	confidence = `NULL`
	)

Determine the maximum likelihood image class.

This function performs pre-processing to the image (apply mean-value subtraction and NCHW format),

See also: PreProcess()

Parameters

rgba	float4 input image in CUDA device memory.
width	width of the input image in pixels.
height	height of the input image in pixels.
confidence	optional pointer to float filled with confidence value.

Returns: Index of the maximum class, or -1 on error.

◆ Classify() [2/2]

int imageNet::Classify ( float * confidence = NULL )

Determine the maximum likelihood image class.

Note: before calling this function, you must call PreProcess() with the image.

Parameters

confidence optional pointer to float filled with confidence value.

Returns: Index of the maximum class, or -1 on error.

◆ Create() [1/3]

static imageNet* imageNet::Create	(	NetworkType	networkType = `GOOGLENET`,
		uint32_t	maxBatchSize = `DEFAULT_MAX_BATCH_SIZE`,
		precisionType	precision = `TYPE_FASTEST`,
		deviceType	device = `DEVICE_GPU`,
		bool	allowGPUFallback = `true`
	)

static

Load a new network instance.

◆ Create() [2/3]

static imageNet* imageNet::Create	(	const char *	prototxt_path,
		const char *	model_path,
		const char *	mean_binary,
		const char *	class_labels,
		const char *	input = `IMAGENET_DEFAULT_INPUT`,
		const char *	output = `IMAGENET_DEFAULT_OUTPUT`,
		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

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 (can be NULL)
class_labels	File path to list of class name labels
input	Name of the input layer blob.
output	Name of the output layer blob.
maxBatchSize	The maximum batch size that the network will support and be optimized for.

◆ Create() [3/3]

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

static

Load a new network instance by parsing the command line.

◆ GetClassDesc()

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

inline

Retrieve the description of a particular class.

◆ GetClassPath()

const char* imageNet::GetClassPath ( ) const

inline

Retrieve the path to the file containing the class descriptions.

◆ GetClassSynset()

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

inline

Retrieve the class synset category of a particular class.

◆ GetNetworkName()

const char* imageNet::GetNetworkName ( ) const

inline

Retrieve a string describing the network name.

◆ GetNetworkType()

NetworkType imageNet::GetNetworkType ( ) const

inline

Retrieve the network type (alexnet or googlenet)

◆ GetNumClasses()

uint32_t imageNet::GetNumClasses ( ) const

inline

Retrieve the number of image recognition classes (typically 1000)

◆ init() [1/2]

bool imageNet::init	(	NetworkType	networkType,
		uint32_t	maxBatchSize,
		precisionType	precision,
		deviceType	device,
		bool	allowGPUFallback
	)

protected

◆ init() [2/2]

bool imageNet::init	(	const char *	prototxt_path,
		const char *	model_path,
		const char *	mean_binary,
		const char *	class_path,
		const char *	input,
		const char *	output,
		uint32_t	maxBatchSize,
		precisionType	precision,
		deviceType	device,
		bool	allowGPUFallback
	)

protected

◆ loadClassInfo()

bool imageNet::loadClassInfo ( const char * filename )

protected

◆ NetworkTypeFromStr()

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

static

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

Valid names are "alexnet", "googlenet", "googlenet-12", or "googlenet_12", ect.

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

◆ NetworkTypeToStr()

static const char* imageNet::NetworkTypeToStr ( NetworkType network )

static

Convert a NetworkType enum to a string.

◆ PreProcess()

bool imageNet::PreProcess	(	float *	rgba,
		uint32_t	width,
		uint32_t	height
	)

Perform pre-processing on the image to apply mean-value subtraction and to organize the data into NCHW format and BGR colorspace that the networks expect.

After calling PreProcess(), you can call Classify() without supplying all the parameters.

◆ Process()

bool imageNet::Process ( )

Process the network, without determining the classification argmax.

To perform the actual classification via post-processing, Classify() should be used instead.

◆ Usage()

static const char* imageNet::Usage ( )

inlinestatic

Usage string for command line arguments to Create()

Member Data Documentation

◆ mClassDesc

std::vector<std::string> imageNet::mClassDesc

protected

◆ mClassPath

std::string imageNet::mClassPath

protected

◆ mClassSynset

std::vector<std::string> imageNet::mClassSynset

protected

◆ mCustomClasses

uint32_t imageNet::mCustomClasses

protected

◆ mNetworkType

NetworkType imageNet::mNetworkType

protected

◆ mOutputClasses

uint32_t imageNet::mOutputClasses

protected

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

jetson-inference/imageNet.h

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Enumeration Documentation

◆ NetworkType

Constructor & Destructor Documentation

◆ ~imageNet()

◆ imageNet()

Member Function Documentation

◆ Classify() [1/2]

◆ Classify() [2/2]

◆ Create() [1/3]

◆ Create() [2/3]

◆ Create() [3/3]

◆ GetClassDesc()

◆ GetClassPath()

◆ GetClassSynset()

◆ GetNetworkName()

◆ GetNetworkType()

◆ GetNumClasses()

◆ init() [1/2]

◆ init() [2/2]

◆ loadClassInfo()

◆ NetworkTypeFromStr()

◆ NetworkTypeToStr()

◆ PreProcess()

◆ Process()

◆ Usage()

Member Data Documentation

◆ mClassDesc

◆ mClassPath

◆ mClassSynset

◆ mCustomClasses

◆ mNetworkType

◆ mOutputClasses