Mono depth estimation from monocular images. More...

Classes
class	depthNet
	Mono depth estimation from monocular images, using TensorRT. More...

Macros
#define	DEPTHNET_DEFAULT_INPUT "input_0"
	Name of default input blob for depthNet model. More...

#define	DEPTHNET_DEFAULT_OUTPUT "output_0"
	Name of default output blob for depthNet model. More...

#define	DEPTHNET_MODEL_TYPE "monodepth"
	The model type for depthNet in data/networks/models.json. More...

#define	DEPTHNET_USAGE_STRING
	Command-line options able to be passed to depthNet::Create() More...

Detailed Description

Mono depth estimation from monocular images.

Class Documentation

◆ depthNet

class depthNet

Mono depth estimation from monocular images, using TensorRT.

Inheritance diagram for depthNet:

Public Types
enum	VisualizationFlags { VISUALIZE_INPUT = (1 << 0), VISUALIZE_DEPTH = (1 << 1) }
	Visualization flags. More...

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

template<typename T >
bool	Process (T *image, uint32_t width, uint32_t height)
	Compute the depth field from a monocular RGB/RGBA image. More...

bool	Process (void *input, uint32_t width, uint32_t height, imageFormat format)
	Compute the depth field from a monocular RGB/RGBA image. More...

template<typename T1 , typename T2 >
bool	Process (T1 input, T2 output, uint32_t width, uint32_t height, cudaColormapType colormap=COLORMAP_VIRIDIS_INVERTED, cudaFilterMode filter=FILTER_LINEAR)
	Process an RGB/RGBA image and map the depth image with the specified colormap. More...

bool	Process (void input, imageFormat input_format, void output, imageFormat output_format, uint32_t width, uint32_t height, cudaColormapType colormap=COLORMAP_VIRIDIS_INVERTED, cudaFilterMode filter=FILTER_LINEAR)
	Process an RGB/RGBA image and map the depth image with the specified colormap. More...

template<typename T1 , typename T2 >
bool	Process (T1 input, uint32_t input_width, uint32_t input_height, T2 output, uint32_t output_width, uint32_t output_height, cudaColormapType colormap=COLORMAP_DEFAULT, cudaFilterMode filter=FILTER_LINEAR)
	Process an RGB/RGBA image and map the depth image with the specified colormap. More...

bool	Process (void input, uint32_t input_width, uint32_t input_height, imageFormat input_format, void output, uint32_t output_width, uint32_t output_height, imageFormat output_format, cudaColormapType colormap=COLORMAP_DEFAULT, cudaFilterMode filter=FILTER_LINEAR)
	Process an RGB/RGBA image and map the depth image with the specified colormap. More...

template<typename T >
bool	Visualize (T *output, uint32_t width, uint32_t height, cudaColormapType colormap=COLORMAP_DEFAULT, cudaFilterMode filter=FILTER_LINEAR)
	Visualize the raw depth field into a colorized RGB/RGBA depth map. More...

bool	Visualize (void *output, uint32_t width, uint32_t height, imageFormat format, cudaColormapType colormap=COLORMAP_DEFAULT, cudaFilterMode filter=FILTER_LINEAR)
	Visualize the raw depth field into a colorized RGB/RGBA depth map. More...

float *	GetDepthField () const
	Return the raw depth field. More...

uint32_t	GetDepthFieldWidth () const
	Return the width of the depth field. More...

uint32_t	GetDepthFieldHeight () const
	Return the height of the depth field. More...

bool	SavePointCloud (const char *filename)
	Extract and save the point cloud to a PCD file (depth only). More...

bool	SavePointCloud (const char filename, float rgba, uint32_t width, uint32_t height)
	Extract and save the point cloud to a PCD file (depth + RGB). More...

bool	SavePointCloud (const char filename, float rgba, uint32_t width, uint32_t height, const float2 &focalLength, const float2 &principalPoint)
	Extract and save the point cloud to a PCD file (depth + RGB). More...

bool	SavePointCloud (const char filename, float rgba, uint32_t width, uint32_t height, const float intrinsicCalibration[3][3])
	Extract and save the point cloud to a PCD file (depth + RGB). More...

bool	SavePointCloud (const char filename, float rgba, uint32_t width, uint32_t height, const char *intrinsicCalibrationPath)
	Extract and save the point cloud to a PCD file (depth + RGB). 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 std::vector< std::string > &input_blobs, 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 input 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...

bool	LoadNetwork (const char prototxt, const char model, const char mean, const std::vector< std::string > &input_blobs, const std::vector< 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 with multiple input layers (used for UFF models) More...

bool	LoadEngine (const char engine_filename, const std::vector< std::string > &input_blobs, const std::vector< std::string > &output_blobs, nvinfer1::IPluginFactory pluginFactory=NULL, deviceType device=DEVICE_GPU, cudaStream_t stream=NULL)
	Load a network instance from a serialized engine plan file. More...

bool	LoadEngine (char engine_stream, size_t engine_size, const std::vector< std::string > &input_blobs, const std::vector< std::string > &output_blobs, nvinfer1::IPluginFactory pluginFactory=NULL, deviceType device=DEVICE_GPU, cudaStream_t stream=NULL)
	Load a network instance from a serialized engine plan file. More...

bool	LoadEngine (nvinfer1::ICudaEngine *engine, const std::vector< std::string > &input_blobs, const std::vector< std::string > &output_blobs, deviceType device=DEVICE_GPU, cudaStream_t stream=NULL)
	Load network resources from an existing TensorRT engine instance. More...

bool	LoadEngine (const char filename, char stream, size_t size)
	Load a serialized engine plan file into memory. 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 full path to model file, including the filename. More...

const char *	GetModelFilename () const
	Retrieve the filename of the file, excluding the directory. 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...

uint32_t	GetInputLayers () const
	Retrieve the number of input layers to the network. More...

uint32_t	GetOutputLayers () const
	Retrieve the number of output layers to the network. More...

Dims3	GetInputDims (uint32_t layer=0) const
	Retrieve the dimensions of network input layer. More...

uint32_t	GetInputWidth (uint32_t layer=0) const
	Retrieve the width of network input layer. More...

uint32_t	GetInputHeight (uint32_t layer=0) const
	Retrieve the height of network input layer. More...

uint32_t	GetInputSize (uint32_t layer=0) const
	Retrieve the size (in bytes) of network input layer. More...

float *	GetInputPtr (uint32_t layer=0) const
	Get the CUDA pointer to the input layer's memory. More...

Dims3	GetOutputDims (uint32_t layer=0) const
	Retrieve the dimensions of network output layer. More...

uint32_t	GetOutputWidth (uint32_t layer=0) const
	Retrieve the width of network output layer. More...

uint32_t	GetOutputHeight (uint32_t layer=0) const
	Retrieve the height of network output layer. More...

uint32_t	GetOutputSize (uint32_t layer=0) const
	Retrieve the size (in bytes) of network output layer. More...

float *	GetOutputPtr (uint32_t layer=0) const
	Get the CUDA pointer to the output memory. More...

float	GetNetworkFPS ()
	Retrieve the network frames per second (FPS). More...

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

const char *	GetNetworkName () const
	Retrieve the network name (it's filename). 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 uint32_t	VisualizationFlagsFromStr (const char *str, uint32_t default_value=VISUALIZE_INPUT\|VISUALIZE_DEPTH)
	Parse a string of one of more VisualizationMode values. More...

static depthNet *	Create (const char *network="fcn-mobilenet", uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)
	Load a pre-trained model. More...

static depthNet *	Create (const char model_path, const char input=DEPTHNET_DEFAULT_INPUT, const char *output=DEPTHNET_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 depthNet *	Create (const char model_path, const char input, const Dims3 &inputDims, const char *output, 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 depthNet *	Create (int argc, char **argv)
	Load a new network instance by parsing the command line. More...

static depthNet *	Create (const commandLine &cmdLine)
	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 bool	LoadClassLabels (const char *filename, std::vector< std::string > &descriptions, int expectedClasses=-1)
	Load class descriptions from a label file. More...

static bool	LoadClassLabels (const char *filename, std::vector< std::string > &descriptions, std::vector< std::string > &synsets, int expectedClasses=-1)
	Load class descriptions and synset strings from a label file. More...

static bool	LoadClassColors (const char filename, float4 colors, int expectedClasses, float defaultAlpha=255.0f)
	Load class colors from a text file. More...

static bool	LoadClassColors (const char filename, float4 *colors, int expectedClasses, float defaultAlpha=255.0f)
	Load class colors from a text file. More...

static float4	GenerateColor (uint32_t classID, float alpha=255.0f)
	Procedurally generate a color for a given class index with the specified alpha value. More...

static precisionType	SelectPrecision (precisionType precision, deviceType device=DEVICE_GPU, bool allowInt8=true)
	Resolve a desired precision to a specific one that's available. More...

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
	depthNet ()

bool	allocHistogramBuffers ()

bool	histogramEqualization ()

bool	histogramEqualizationCUDA ()

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

bool	ProcessNetwork (bool sync=true)
	Execute processing of the network. More...

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

bool	ConfigureBuilder (nvinfer1::IBuilder builder, uint32_t maxBatchSize, uint32_t workspaceSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator calibrator)
	Configure builder options. More...

bool	ValidateEngine (const char model_path, const char cache_path, const char *checksum_path)
	Validate that the model already has a built TensorRT engine that exists and doesn't need updating. 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
int2 *	mDepthRange

float *	mDepthEqualized

uint32_t *	mHistogram

float *	mHistogramPDF

float *	mHistogramCDF

uint32_t *	mHistogramEDU

Protected Attributes inherited from tensorNet
tensorNet::Logger	gLogger

tensorNet::Profiler	gProfiler

std::string	mPrototxtPath

std::string	mModelPath

std::string	mModelFile

std::string	mMeanPath

std::string	mCacheEnginePath

std::string	mCacheCalibrationPath

std::string	mChecksumPath

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

float2	mProfilerTimes [PROFILER_TOTAL+1]

uint32_t	mProfilerQueriesUsed

uint32_t	mProfilerQueriesDone

uint32_t	mWorkspaceSize

uint32_t	mMaxBatchSize

bool	mEnableProfiler

bool	mEnableDebug

bool	mAllowGPUFallback

void **	mBindings

std::vector< layerInfo >	mInputs

std::vector< layerInfo >	mOutputs

Member Enumeration Documentation

◆ VisualizationFlags

enum depthNet::VisualizationFlags

Visualization flags.

Enumerator
VISUALIZE_INPUT	Display the original input image.
VISUALIZE_DEPTH	Display the colorized depth field.

Constructor & Destructor Documentation

◆ ~depthNet()

virtual depthNet::~depthNet ( )

virtual

Destroy.

◆ depthNet()

depthNet::depthNet ( )

protected

Member Function Documentation

◆ allocHistogramBuffers()

bool depthNet::allocHistogramBuffers ( )

protected

◆ Create() [1/5]

static depthNet* depthNet::Create	(	const char *	model_path,
		const char *	input,
		const Dims3 &	inputDims,
		const char *	output,
		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
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.
maxBatchSize	The maximum batch size that the network will support and be optimized for.

◆ Create() [2/5]

static depthNet* depthNet::Create	(	const char *	model_path,
		const char *	input = `DEPTHNET_DEFAULT_INPUT`,
		const char *	output = `DEPTHNET_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

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() [3/5]

static depthNet* depthNet::Create	(	const char *	network = `"fcn-mobilenet"`,
		uint32_t	maxBatchSize = `DEFAULT_MAX_BATCH_SIZE`,
		precisionType	precision = `TYPE_FASTEST`,
		deviceType	device = `DEVICE_GPU`,
		bool	allowGPUFallback = `true`
	)

static

Load a pre-trained model.

See also: DEPTHNET_USAGE_STRING for the available models.

◆ Create() [4/5]

static depthNet* depthNet::Create ( const commandLine & cmdLine )

static

Load a new network instance by parsing the command line.

◆ Create() [5/5]

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

static

Load a new network instance by parsing the command line.

◆ GetDepthField()

float* depthNet::GetDepthField ( ) const

inline

Return the raw depth field.

◆ GetDepthFieldHeight()

uint32_t depthNet::GetDepthFieldHeight ( ) const

inline

Return the height of the depth field.

◆ GetDepthFieldWidth()

uint32_t depthNet::GetDepthFieldWidth ( ) const

inline

Return the width of the depth field.

◆ histogramEqualization()

bool depthNet::histogramEqualization ( )

protected

◆ histogramEqualizationCUDA()

bool depthNet::histogramEqualizationCUDA ( )

protected

◆ Process() [1/6]

template<typename T >

bool depthNet::Process	(	T *	image,
		uint32_t	width,
		uint32_t	height
	)

inline

Compute the depth field from a monocular RGB/RGBA image.

Note: the raw depth field can be retrieved with GetDepthField().

◆ Process() [2/6]

template<typename T1 , typename T2 >

bool depthNet::Process	(	T1 *	input,
		T2 *	output,
		uint32_t	width,
		uint32_t	height,
		cudaColormapType	colormap = `COLORMAP_VIRIDIS_INVERTED`,
		cudaFilterMode	filter = `FILTER_LINEAR`
	)

inline

Process an RGB/RGBA image and map the depth image with the specified colormap.

Note: this function calls Process() followed by Visualize().

◆ Process() [3/6]

template<typename T1 , typename T2 >

bool depthNet::Process	(	T1 *	input,
		uint32_t	input_width,
		uint32_t	input_height,
		T2 *	output,
		uint32_t	output_width,
		uint32_t	output_height,
		cudaColormapType	colormap = `COLORMAP_DEFAULT`,
		cudaFilterMode	filter = `FILTER_LINEAR`
	)

inline

Process an RGB/RGBA image and map the depth image with the specified colormap.

Note: this function calls Process() followed by Visualize().

◆ Process() [4/6]

bool depthNet::Process	(	void *	input,
		imageFormat	input_format,
		void *	output,
		imageFormat	output_format,
		uint32_t	width,
		uint32_t	height,
		cudaColormapType	colormap = `COLORMAP_VIRIDIS_INVERTED`,
		cudaFilterMode	filter = `FILTER_LINEAR`
	)

Process an RGB/RGBA image and map the depth image with the specified colormap.

Note: this function calls Process() followed by Visualize().

◆ Process() [5/6]

bool depthNet::Process	(	void *	input,
		uint32_t	input_width,
		uint32_t	input_height,
		imageFormat	input_format,
		void *	output,
		uint32_t	output_width,
		uint32_t	output_height,
		imageFormat	output_format,
		cudaColormapType	colormap = `COLORMAP_DEFAULT`,
		cudaFilterMode	filter = `FILTER_LINEAR`
	)

Process an RGB/RGBA image and map the depth image with the specified colormap.

Note: this function calls Process() followed by Visualize().

◆ Process() [6/6]

bool depthNet::Process	(	void *	input,
		uint32_t	width,
		uint32_t	height,
		imageFormat	format
	)

Compute the depth field from a monocular RGB/RGBA image.

Note: the raw depth field can be retrieved with GetDepthField().

◆ SavePointCloud() [1/5]

bool depthNet::SavePointCloud ( const char * filename )

Extract and save the point cloud to a PCD file (depth only).

Note: SavePointCloud() should only be called after Process()

◆ SavePointCloud() [2/5]

bool depthNet::SavePointCloud	(	const char *	filename,
		float *	rgba,
		uint32_t	width,
		uint32_t	height
	)

Extract and save the point cloud to a PCD file (depth + RGB).

Note: SavePointCloud() should only be called after Process()

◆ SavePointCloud() [3/5]

bool depthNet::SavePointCloud	(	const char *	filename,
		float *	rgba,
		uint32_t	width,
		uint32_t	height,
		const char *	intrinsicCalibrationPath
	)

Extract and save the point cloud to a PCD file (depth + RGB).

Note: SavePointCloud() should only be called after Process()

◆ SavePointCloud() [4/5]

bool depthNet::SavePointCloud	(	const char *	filename,
		float *	rgba,
		uint32_t	width,
		uint32_t	height,
		const float	intrinsicCalibration[3][3]
	)

Extract and save the point cloud to a PCD file (depth + RGB).

Note: SavePointCloud() should only be called after Process()

◆ SavePointCloud() [5/5]

bool depthNet::SavePointCloud	(	const char *	filename,
		float *	rgba,
		uint32_t	width,
		uint32_t	height,
		const float2 &	focalLength,
		const float2 &	principalPoint
	)

Extract and save the point cloud to a PCD file (depth + RGB).

Note: SavePointCloud() should only be called after Process()

◆ Usage()

static const char* depthNet::Usage ( )

inlinestatic

Usage string for command line arguments to Create()

◆ VisualizationFlagsFromStr()

static uint32_t depthNet::VisualizationFlagsFromStr	(	const char *	str,
		uint32_t	default_value = `VISUALIZE_INPUT\|VISUALIZE_DEPTH`
	)

static

Parse a string of one of more VisualizationMode values.

Valid strings are "depth" "input" "input|depth" "input,depth" ect.

◆ Visualize() [1/2]

template<typename T >

bool depthNet::Visualize	(	T *	output,
		uint32_t	width,
		uint32_t	height,
		cudaColormapType	colormap = `COLORMAP_DEFAULT`,
		cudaFilterMode	filter = `FILTER_LINEAR`
	)

inline

Visualize the raw depth field into a colorized RGB/RGBA depth map.

Note: Visualize() should only be called after Process()

◆ Visualize() [2/2]

bool depthNet::Visualize	(	void *	output,
		uint32_t	width,
		uint32_t	height,
		imageFormat	format,
		cudaColormapType	colormap = `COLORMAP_DEFAULT`,
		cudaFilterMode	filter = `FILTER_LINEAR`
	)

Visualize the raw depth field into a colorized RGB/RGBA depth map.

Note: Visualize() should only be called after Process()

Member Data Documentation

◆ mDepthEqualized

float* depthNet::mDepthEqualized

protected

◆ mDepthRange

int2* depthNet::mDepthRange

protected

◆ mHistogram

uint32_t* depthNet::mHistogram

protected

◆ mHistogramCDF

float* depthNet::mHistogramCDF

protected

◆ mHistogramEDU

uint32_t* depthNet::mHistogramEDU

protected

◆ mHistogramPDF

float* depthNet::mHistogramPDF

protected

Macro Definition Documentation

◆ DEPTHNET_DEFAULT_INPUT

#define DEPTHNET_DEFAULT_INPUT "input_0"

Name of default input blob for depthNet model.

◆ DEPTHNET_DEFAULT_OUTPUT

#define DEPTHNET_DEFAULT_OUTPUT "output_0"

Name of default output blob for depthNet model.

◆ DEPTHNET_MODEL_TYPE

#define DEPTHNET_MODEL_TYPE "monodepth"

The model type for depthNet in data/networks/models.json.

◆ DEPTHNET_USAGE_STRING

#define DEPTHNET_USAGE_STRING

Value:

                  "depthNet arguments: \n"                                                      \
                  "  --network NETWORK    pre-trained model to load, one of the following:\n"   \
                  "                           * fcn-mobilenet\n"                                        \
                  "                           * fcn-resnet18\n"                                         \
                  "                           * fcn-resnet50\n"                                         \
                  "  --model MODEL        path to custom model to load (onnx)\n"                        \
                  "  --input_blob INPUT   name of the input layer (default is '" DEPTHNET_DEFAULT_INPUT "')\n"  \
                  "  --output_blob OUTPUT name of the output layer (default is '" DEPTHNET_DEFAULT_OUTPUT "')\n"        \
                  "  --profile            enable layer profiling in TensorRT\n\n"

Command-line options able to be passed to depthNet::Create()

Classes

Macros

Detailed Description

Class Documentation

◆ depthNet

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Member Enumeration Documentation

◆ VisualizationFlags

Constructor & Destructor Documentation

◆ ~depthNet()

◆ depthNet()

Member Function Documentation

◆ allocHistogramBuffers()

◆ Create() [1/5]

◆ Create() [2/5]

◆ Create() [3/5]

◆ Create() [4/5]

◆ Create() [5/5]

◆ GetDepthField()

◆ GetDepthFieldHeight()

◆ GetDepthFieldWidth()

◆ histogramEqualization()

◆ histogramEqualizationCUDA()

◆ Process() [1/6]

◆ Process() [2/6]

◆ Process() [3/6]

◆ Process() [4/6]

◆ Process() [5/6]

◆ Process() [6/6]

◆ SavePointCloud() [1/5]

◆ SavePointCloud() [2/5]

◆ SavePointCloud() [3/5]

◆ SavePointCloud() [4/5]

◆ SavePointCloud() [5/5]

◆ Usage()

◆ VisualizationFlagsFromStr()

◆ Visualize() [1/2]

◆ Visualize() [2/2]

Member Data Documentation

◆ mDepthEqualized

◆ mDepthRange

◆ mHistogram

◆ mHistogramCDF

◆ mHistogramEDU

◆ mHistogramPDF

Macro Definition Documentation

◆ DEPTHNET_DEFAULT_INPUT

◆ DEPTHNET_DEFAULT_OUTPUT

◆ DEPTHNET_MODEL_TYPE

◆ DEPTHNET_USAGE_STRING