docs/html/group__depthNet.html
| | Jetson Inference
DNN Vision Library |
depthNet DNN Vision Library (jetson-inference)
Mono depth estimation from monocular images. More...
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| class | depthNet |
| | Mono depth estimation from monocular images, using TensorRT. More...
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| #define | DEPTHNET_DEFAULT_INPUT "input_0" |
| | Name of default input blob for depthNet model. More...
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| #define | DEPTHNET_DEFAULT_OUTPUT "output_0" |
| | Name of default output blob for depthNet model. More...
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| #define | DEPTHNET_MODEL_TYPE "monodepth" |
| | The model type for depthNet in data/networks/models.json. More...
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| #define | DEPTHNET_USAGE_STRING |
| | Command-line options able to be passed to depthNet::Create()More...
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Mono depth estimation from monocular images.
| class depthNet |
Mono depth estimation from monocular images, using TensorRT.
Inheritance diagram for depthNet:
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| enum | VisualizationFlags { VISUALIZE_INPUT = (1 << 0), VISUALIZE_DEPTH = (1 << 1) } |
| | Visualization flags. More...
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| virtual | ~depthNet () |
| | Destroy. More...
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| template<typename T > |
| bool | Process (T *image, uint32_t width, uint32_t height) |
| | Compute the depth field from a monocular RGB/RGBA image. More...
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| bool | Process (void *input, uint32_t width, uint32_t height, imageFormat format) |
| | Compute the depth field from a monocular RGB/RGBA image. More...
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| 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...
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| 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...
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| 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...
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| 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...
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| 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...
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| 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...
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| float * | GetDepthField () const |
| | Return the raw depth field. More...
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| uint32_t | GetDepthFieldWidth () const |
| | Return the width of the depth field. More...
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| uint32_t | GetDepthFieldHeight () const |
| | Return the height of the depth field. More...
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| bool | SavePointCloud (const char *filename) |
| | Extract and save the point cloud to a PCD file (depth only). More...
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| 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...
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| 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...
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| 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...
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| 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...
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| Public Member Functions inherited from tensorNet |
| virtual | ~tensorNet () |
| | Destory. More...
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| 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...
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| 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...
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| 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...
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| 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...
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| 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...
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| 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...
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| 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...
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| 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...
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| bool | LoadEngine (const char *filename, char **stream, size_t *size) |
| | Load a serialized engine plan file into memory. More...
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| void | EnableLayerProfiler () |
| | Manually enable layer profiling times. More...
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| void | EnableDebug () |
| | Manually enable debug messages and synchronization. More...
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| bool | AllowGPUFallback () const |
| | Return true if GPU fallback is enabled. More...
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| deviceType | GetDevice () const |
| | Retrieve the device being used for execution. More...
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| precisionType | GetPrecision () const |
| | Retrieve the type of precision being used. More...
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| bool | IsPrecision (precisionType type) const |
| | Check if a particular precision is being used. More...
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| cudaStream_t | GetStream () const |
| | Retrieve the stream that the device is operating on. More...
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| cudaStream_t | CreateStream (bool nonBlocking=true) |
| | Create and use a new stream for execution. More...
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| void | SetStream (cudaStream_t stream) |
| | Set the stream that the device is operating on. More...
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| const char * | GetPrototxtPath () const |
| | Retrieve the path to the network prototxt file. More...
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| const char * | GetModelPath () const |
| | Retrieve the full path to model file, including the filename. More...
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| const char * | GetModelFilename () const |
| | Retrieve the filename of the file, excluding the directory. More...
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| modelType | GetModelType () const |
| | Retrieve the format of the network model. More...
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| bool | IsModelType (modelType type) const |
| | Return true if the model is of the specified format. More...
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| uint32_t | GetInputLayers () const |
| | Retrieve the number of input layers to the network. More...
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| uint32_t | GetOutputLayers () const |
| | Retrieve the number of output layers to the network. More...
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| Dims3 | GetInputDims (uint32_t layer=0) const |
| | Retrieve the dimensions of network input layer. More...
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| uint32_t | GetInputWidth (uint32_t layer=0) const |
| | Retrieve the width of network input layer. More...
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| uint32_t | GetInputHeight (uint32_t layer=0) const |
| | Retrieve the height of network input layer. More...
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| uint32_t | GetInputSize (uint32_t layer=0) const |
| | Retrieve the size (in bytes) of network input layer. More...
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| float * | GetInputPtr (uint32_t layer=0) const |
| | Get the CUDA pointer to the input layer's memory. More...
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| Dims3 | GetOutputDims (uint32_t layer=0) const |
| | Retrieve the dimensions of network output layer. More...
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| uint32_t | GetOutputWidth (uint32_t layer=0) const |
| | Retrieve the width of network output layer. More...
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| uint32_t | GetOutputHeight (uint32_t layer=0) const |
| | Retrieve the height of network output layer. More...
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| uint32_t | GetOutputSize (uint32_t layer=0) const |
| | Retrieve the size (in bytes) of network output layer. More...
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| float * | GetOutputPtr (uint32_t layer=0) const |
| | Get the CUDA pointer to the output memory. More...
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| float | GetNetworkFPS () |
| | Retrieve the network frames per second (FPS). More...
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| float | GetNetworkTime () |
| | Retrieve the network runtime (in milliseconds). More...
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| const char * | GetNetworkName () const |
| | Retrieve the network name (it's filename). More...
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| float2 | GetProfilerTime (profilerQuery query) |
| | Retrieve the profiler runtime (in milliseconds). More...
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| float | GetProfilerTime (profilerQuery query, profilerDevice device) |
| | Retrieve the profiler runtime (in milliseconds). More...
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| void | PrintProfilerTimes () |
| | Print the profiler times (in millseconds). More...
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| 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...
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| 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...
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| 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...
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| 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...
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| static depthNet * | Create (int argc, char **argv) |
| | Load a new network instance by parsing the command line. More...
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| static depthNet * | Create (const commandLine &cmdLine) |
| | Load a new network instance by parsing the command line. More...
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| static const char * | Usage () |
| | Usage string for command line arguments to Create()More...
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| 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...
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| 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...
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| static bool | LoadClassColors (const char *filename, float4 *colors, int expectedClasses, float defaultAlpha=255.0f) |
| | Load class colors from a text file. More...
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| static bool | LoadClassColors (const char *filename, float4 **colors, int expectedClasses, float defaultAlpha=255.0f) |
| | Load class colors from a text file. More...
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| 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...
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| static precisionType | SelectPrecision (precisionType precision, deviceType device=DEVICE_GPU, bool allowInt8=true) |
| | Resolve a desired precision to a specific one that's available. More...
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| static precisionType | FindFastestPrecision (deviceType device=DEVICE_GPU, bool allowInt8=true) |
| | Determine the fastest native precision on a device. More...
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| static std::vector< precisionType > | DetectNativePrecisions (deviceType device=DEVICE_GPU) |
| | Detect the precisions supported natively on a device. More...
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| static bool | DetectNativePrecision (const std::vector< precisionType > &nativeTypes, precisionType type) |
| | Detect if a particular precision is supported natively. More...
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| static bool | DetectNativePrecision (precisionType precision, deviceType device=DEVICE_GPU) |
| | Detect if a particular precision is supported natively. More...
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| | depthNet () |
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| bool | allocHistogramBuffers () |
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| bool | histogramEqualization () |
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| bool | histogramEqualizationCUDA () |
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| Protected Member Functions inherited from tensorNet |
| | tensorNet () |
| | Constructor. More...
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| bool | ProcessNetwork (bool sync=true) |
| | Execute processing of the network. More...
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| 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...
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| bool | ConfigureBuilder (nvinfer1::IBuilder *builder, uint32_t maxBatchSize, uint32_t workspaceSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator) |
| | Configure builder options. More...
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| 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...
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| void | PROFILER_BEGIN (profilerQuery query) |
| | Begin a profiling query, before network is run. More...
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| void | PROFILER_END (profilerQuery query) |
| | End a profiling query, after the network is run. More...
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| bool | PROFILER_QUERY (profilerQuery query) |
| | Query the CUDA part of a profiler query. More...
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| | 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 | | |
| enum depthNet::VisualizationFlags |
Visualization flags.
| Enumerator |
|---|
| VISUALIZE_INPUT |
Display the original input image.
| | VISUALIZE_DEPTH |
Display the colorized depth field.
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| virtual depthNet::~depthNet | ( | | ) | |
| virtual |
Destroy.
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| depthNet::depthNet | ( | | ) | |
| protected |
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| bool depthNet::allocHistogramBuffers | ( | | ) | |
| protected |
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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. |
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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. |
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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.
|
| static depthNet* depthNet::Create | ( | const commandLine & | cmdLine | ) | |
| static |
Load a new network instance by parsing the command line.
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| static depthNet* depthNet::Create | ( | int | argc, | | | | char ** | argv | | | ) | | |
| static |
Load a new network instance by parsing the command line.
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| float* depthNet::GetDepthField | ( | | ) | const |
| inline |
Return the raw depth field.
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| uint32_t depthNet::GetDepthFieldHeight | ( | | ) | const |
| inline |
Return the height of the depth field.
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| uint32_t depthNet::GetDepthFieldWidth | ( | | ) | const |
| inline |
Return the width of the depth field.
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| bool depthNet::histogramEqualization | ( | | ) | |
| protected |
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| bool depthNet::histogramEqualizationCUDA | ( | | ) | |
| protected |
template<typename T >
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| 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().
template<typename T1 , typename T2 >
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| 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().
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().
| 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().
| 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().
| 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().
| 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()
| 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()
| 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()
| 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()
| 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()
|
| static const char* depthNet::Usage | ( | | ) | |
| inlinestatic |
Usage string for command line arguments to Create()
|
| 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.
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()
| 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()
|
| float* depthNet::mDepthEqualized |
| protected |
|
| int2* depthNet::mDepthRange |
| protected |
|
| uint32_t* depthNet::mHistogram |
| protected |
|
| float* depthNet::mHistogramCDF |
| protected |
|
| uint32_t* depthNet::mHistogramEDU |
| protected |
|
| float* depthNet::mHistogramPDF |
| protected |
| #define DEPTHNET_DEFAULT_INPUT "input_0" |
Name of default input blob for depthNet model.
| #define DEPTHNET_DEFAULT_OUTPUT "output_0" |
Name of default output blob for depthNet model.
| #define DEPTHNET_MODEL_TYPE "monodepth" |
The model type for depthNet in data/networks/models.json.
| #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()
#define DEPTHNET_DEFAULT_OUTPUT
Name of default output blob for depthNet model.
Definition: depthNet.h:40
#define DEPTHNET_DEFAULT_INPUT
Name of default input blob for depthNet model.
Definition: depthNet.h:34