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Jetson Inference: depthNet Class Reference

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Public Types | Public Member Functions | Static Public Member Functions | Protected Member Functions | Protected Attributes | List of all members

depthNet Class Reference DNN Vision Library (jetson-inference) » depthNet

Mono depth estimation from monocular images, using TensorRT. More...

#include <depthNet.h>

Inheritance diagram for depthNet:

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Public Types

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

Detailed Description

Mono depth estimation from monocular images, using TensorRT.

Member Enumeration Documentation

◆VisualizationFlags

| enum depthNet::VisualizationFlags |

Visualization flags.

Enumerator
VISUALIZE_INPUT

Display the original input image.

| | VISUALIZE_DEPTH |

Display the colorized depth field.

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Constructor & Destructor Documentation

◆~depthNet()

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| virtual depthNet::~depthNet | ( | | ) | |

| virtual |

Destroy.

◆depthNet()

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| depthNet::depthNet | ( | | ) | |

| protected |

Member Function Documentation

◆allocHistogramBuffers()

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| bool depthNet::allocHistogramBuffers | ( | | ) | |

| protected |

◆Create() [1/5]

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| 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]

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| 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]

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| 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 alsoDEPTHNET_USAGE_STRING for the available models.

◆Create() [4/5]

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

| static |

Load a new network instance by parsing the command line.

◆Create() [5/5]

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

| static |

Load a new network instance by parsing the command line.

◆GetDepthField()

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| float* depthNet::GetDepthField | ( | | ) | const |

| inline |

Return the raw depth field.

◆GetDepthFieldHeight()

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| uint32_t depthNet::GetDepthFieldHeight | ( | | ) | const |

| inline |

Return the height of the depth field.

◆GetDepthFieldWidth()

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| uint32_t depthNet::GetDepthFieldWidth | ( | | ) | const |

| inline |

Return the width of the depth field.

◆histogramEqualization()

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| bool depthNet::histogramEqualization | ( | | ) | |

| protected |

◆histogramEqualizationCUDA()

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| 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.

Notethe 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.

Notethis 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.

Notethis 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.

Notethis 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.

Notethis 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.

Notethe 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).

NoteSavePointCloud() 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).

NoteSavePointCloud() 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).

NoteSavePointCloud() 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).

NoteSavePointCloud() 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).

NoteSavePointCloud() 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.

NoteVisualize() 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.

NoteVisualize() 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 |

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

  • jetson-inference/depthNet.h

  • depthNet

  • Generated on Fri Mar 17 2023 14:29:30 for Jetson Inference by 1.8.17