docs/html/group__segNet.html
| | Jetson Inference
DNN Vision Library |
segNet DNN Vision Library (jetson-inference)
Semantic segmentation DNN (FCN or Fully-Convolutional Networks) More...
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| class | segNet |
| | Image segmentation with FCN-Alexnet or custom models, using TensorRT. More...
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| #define | SEGNET_DEFAULT_INPUT "input_0" |
| | Name of default input blob for segmentation model. More...
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| #define | SEGNET_DEFAULT_OUTPUT "output_0" |
| | Name of default output blob for segmentation model. More...
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| #define | SEGNET_DEFAULT_ALPHA 150 |
| | Default alpha blending value used during overlay. More...
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| #define | SEGNET_MODEL_TYPE "segmentation" |
| | The model type for segNet in data/networks/models.json. More...
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| #define | SEGNET_USAGE_STRING |
| | Standard command-line options able to be passed to segNet::Create()More...
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Semantic segmentation DNN (FCN or Fully-Convolutional Networks)
| class segNet |
Image segmentation with FCN-Alexnet or custom models, using TensorRT.
Inheritance diagram for segNet:
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| enum | FilterMode { FILTER_POINT = 0, FILTER_LINEAR } |
| | Enumeration of mask/overlay filtering modes. More...
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| enum | VisualizationFlags { VISUALIZE_OVERLAY = (1 << 0), VISUALIZE_MASK = (1 << 1) } |
| | Visualization flags. More...
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| virtual | ~segNet () |
| | Destroy. More...
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| template<typename T > |
| bool | Process (T *input, uint32_t width, uint32_t height, const char *ignore_class="void") |
| | Perform the initial inferencing processing portion of the segmentation. More...
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| bool | Process (void *input, uint32_t width, uint32_t height, imageFormat format, const char *ignore_class="void") |
| | Perform the initial inferencing processing portion of the segmentation. More...
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| bool | Process (float *input, uint32_t width, uint32_t height, const char *ignore_class="void") |
| | Perform the initial inferencing processing portion of the segmentation. More...
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| template<typename T > |
| bool | Mask (T *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) |
| | Produce a colorized segmentation mask. More...
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| bool | Mask (void *output, uint32_t width, uint32_t height, imageFormat format, FilterMode filter=FILTER_LINEAR) |
| | Produce a colorized segmentation mask. More...
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| bool | Mask (float *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) |
| | Produce a colorized RGBA segmentation mask. More...
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| bool | Mask (uint8_t *output, uint32_t width, uint32_t height) |
| | Produce a grayscale binary segmentation mask, where the pixel values correspond to the class ID of the corresponding class type. More...
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| template<typename T > |
| bool | Overlay (T *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) |
| | Produce the segmentation overlay alpha blended on top of the original image. More...
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| bool | Overlay (void *output, uint32_t width, uint32_t height, imageFormat format, FilterMode filter=FILTER_LINEAR) |
| | Produce the segmentation overlay alpha blended on top of the original image. More...
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| bool | Overlay (float *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) |
| | Produce the segmentation overlay alpha blended on top of the original image. More...
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| int | FindClassID (const char *label_name) |
| | Find the ID of a particular class (by label name). More...
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| uint32_t | GetNumClasses () const |
| | Retrieve the number of object classes supported in the detector. More...
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| const char * | GetClassLabel (uint32_t id) const |
| | Retrieve the description of a particular class. More...
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| const char * | GetClassDesc (uint32_t id) const |
| | Retrieve the description of a particular class. More...
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| float4 | GetClassColor (uint32_t id) const |
| | Retrieve the RGBA visualization color a particular class. More...
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| void | SetClassColor (uint32_t classIndex, const float4 &color) |
| | Set the visualization color of a particular class of object. More...
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| void | SetClassColor (uint32_t classIndex, float r, float g, float b, float a=255.0f) |
| | Set the visualization color of a particular class of object. More...
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| float | GetOverlayAlpha () const |
| | Retrieve the overlay alpha blending value for classes that don't have it explicitly set. More...
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| void | SetOverlayAlpha (float alpha, bool explicit_exempt=true) |
| | Set overlay alpha blending value for all classes (between 0-255), (optionally except for those that have been explicitly set). More...
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| const char * | GetClassPath () const |
| | Retrieve the path to the file containing the class label descriptions. More...
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| uint32_t | GetGridWidth () const |
| | Retrieve the number of columns in the classification grid. More...
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| uint32_t | GetGridHeight () const |
| | Retrieve the number of rows in the classification grid. 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_OVERLAY) |
| | Parse a string of one of more VisualizationMode values. More...
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| static FilterMode | FilterModeFromStr (const char *str, FilterMode default_value=FILTER_LINEAR) |
| | Parse a string from one of the FilterMode values. More...
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| static segNet * | Create (const char *network="fcn-resnet18-voc", 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 segNet * | Create (const char *prototxt_path, const char *model_path, const char *class_labels, const char *class_colors=NULL, const char *input=SEGNET_DEFAULT_INPUT, const char *output=SEGNET_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 segNet * | Create (int argc, char **argv) |
| | Load a new network instance by parsing the command line. More...
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| static segNet * | 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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| | segNet () |
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| bool | classify (const char *ignore_class) |
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| bool | overlayPoint (void *input, uint32_t in_width, uint32_t in_height, imageFormat in_format, void *output, uint32_t out_width, uint32_t out_height, imageFormat out_format, bool mask_only) |
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| bool | overlayLinear (void *input, uint32_t in_width, uint32_t in_height, imageFormat in_format, void *output, uint32_t out_width, uint32_t out_height, imageFormat out_format, bool mask_only) |
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| bool | loadClassColors (const char *filename) |
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| bool | loadClassLabels (const char *filename) |
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| bool | saveClassLegend (const char *filename) |
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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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| std::vector< std::string > | mClassLabels |
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| std::string | mClassPath |
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| bool * | mColorsAlphaSet |
| | true if class color had been explicitly set from file or user More...
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| float4 * | mClassColors |
| | array of overlay colors in shared CPU/GPU memory More...
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| uint8_t * | mClassMap |
| | runtime buffer for the argmax-classified class index of each tile More...
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| void * | mLastInputImg |
| | last input image to be processed, stored for overlay More...
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| uint32_t | mLastInputWidth |
| | width in pixels of last input image to be processed More...
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| uint32_t | mLastInputHeight |
| | height in pixels of last input image to be processed More...
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| imageFormat | mLastInputFormat |
| | pixel format of last input image More...
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| Protected Attributes inherited from tensorNet |
| tensorNet::Logger | gLogger |
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| tensorNet::Profiler | gProfiler |
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| std::string | mPrototxtPath |
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| std::string | mModelPath |
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| std::string | mModelFile |
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| std::string | mMeanPath |
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| std::string | mCacheEnginePath |
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| std::string | mCacheCalibrationPath |
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| std::string | mChecksumPath |
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| deviceType | mDevice |
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| precisionType | mPrecision |
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| modelType | mModelType |
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| cudaStream_t | mStream |
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| cudaEvent_t | mEventsGPU [PROFILER_TOTAL *2] |
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| timespec | mEventsCPU [PROFILER_TOTAL *2] |
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| nvinfer1::IRuntime * | mInfer |
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| nvinfer1::ICudaEngine * | mEngine |
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| nvinfer1::IExecutionContext * | mContext |
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| float2 | mProfilerTimes [PROFILER_TOTAL+1] |
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| uint32_t | mProfilerQueriesUsed |
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| uint32_t | mProfilerQueriesDone |
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| uint32_t | mWorkspaceSize |
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| uint32_t | mMaxBatchSize |
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| bool | mEnableProfiler |
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| bool | mEnableDebug |
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| bool | mAllowGPUFallback |
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| void ** | mBindings |
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| std::vector< layerInfo > | mInputs |
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| std::vector< layerInfo > | mOutputs |
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| enum segNet::FilterMode |
Enumeration of mask/overlay filtering modes.
| Enumerator |
|---|
| FILTER_POINT |
Nearest point sampling.
| | FILTER_LINEAR |
Bilinear filtering.
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| enum segNet::VisualizationFlags |
Visualization flags.
| Enumerator |
|---|
| VISUALIZE_OVERLAY |
Overlay the segmentation class colors with alpha blending.
| | VISUALIZE_MASK |
View just the colorized segmentation class mask.
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| virtual segNet::~segNet | ( | | ) | |
| virtual |
Destroy.
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| segNet::segNet | ( | | ) | |
| protected |
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| bool segNet::classify | ( | const char * | ignore_class | ) | |
| protected |
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| static segNet* segNet::Create | ( | const char * | network = "fcn-resnet18-voc", |
| | | 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 alsoSEGNET_USAGE_STRING for the models available.
|
| static segNet* segNet::Create | ( | const char * | prototxt_path, |
| | | const char * | model_path, |
| | | const char * | class_labels, |
| | | const char * | class_colors = NULL, |
| | | const char * | input = SEGNET_DEFAULT_INPUT, |
| | | const char * | output = SEGNET_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 | | class_labels | File path to list of class name labels | | class_colors | File path to list of class colors | | input | Name of the input layer blob. |
See alsoSEGNET_DEFAULT_INPUT Parameters
| output | Name of the output layer blob. |
See alsoSEGNET_DEFAULT_OUTPUT Parameters
| maxBatchSize | The maximum batch size that the network will support and be optimized for. |
|
| static segNet* segNet::Create | ( | const commandLine & | cmdLine | ) | |
| static |
Load a new network instance by parsing the command line.
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| static segNet* segNet::Create | ( | int | argc, | | | | char ** | argv | | | ) | | |
| static |
Load a new network instance by parsing the command line.
|
| static FilterMode segNet::FilterModeFromStr | ( | const char * | str, |
| | | FilterMode | default_value = FILTER_LINEAR |
| | ) | | |
| static |
Parse a string from one of the FilterMode values.
Valid strings are "point", and "linear"
Returnsone of the segNet::FilterMode enums, or default segNet::FILTER_LINEAR on an error.
| int segNet::FindClassID | ( | const char * | label_name | ) | |
Find the ID of a particular class (by label name).
|
| float4 segNet::GetClassColor | ( | uint32_t | id | ) | const |
| inline |
Retrieve the RGBA visualization color a particular class.
|
| const char* segNet::GetClassDesc | ( | uint32_t | id | ) | const |
| inline |
Retrieve the description of a particular class.
|
| const char* segNet::GetClassLabel | ( | uint32_t | id | ) | const |
| inline |
Retrieve the description of a particular class.
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| const char* segNet::GetClassPath | ( | | ) | const |
| inline |
Retrieve the path to the file containing the class label descriptions.
|
| uint32_t segNet::GetGridHeight | ( | | ) | const |
| inline |
Retrieve the number of rows in the classification grid.
This indicates the resolution of the raw segmentation output.
|
| uint32_t segNet::GetGridWidth | ( | | ) | const |
| inline |
Retrieve the number of columns in the classification grid.
This indicates the resolution of the raw segmentation output.
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| uint32_t segNet::GetNumClasses | ( | | ) | const |
| inline |
Retrieve the number of object classes supported in the detector.
| float segNet::GetOverlayAlpha | ( | | ) | const |
Retrieve the overlay alpha blending value for classes that don't have it explicitly set.
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| bool segNet::loadClassColors | ( | const char * | filename | ) | |
| protected |
|
| bool segNet::loadClassLabels | ( | const char * | filename | ) | |
| protected |
| bool segNet::Mask | ( | float * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | FilterMode | filter = FILTER_LINEAR |
| | ) | | |
Produce a colorized RGBA segmentation mask.
**Deprecated:**this overload is for legacy compatibility. It expects float4 RGBA image.
template<typename T >
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| bool segNet::Mask | ( | T * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | FilterMode | filter = FILTER_LINEAR |
| | ) | | |
| inline |
Produce a colorized segmentation mask.
| bool segNet::Mask | ( | uint8_t * | output, | | | | uint32_t | width, | | | | uint32_t | height | | | ) | | |
Produce a grayscale binary segmentation mask, where the pixel values correspond to the class ID of the corresponding class type.
| bool segNet::Mask | ( | void * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | imageFormat | format, |
| | | FilterMode | filter = FILTER_LINEAR |
| | ) | | |
Produce a colorized segmentation mask.
| bool segNet::Overlay | ( | float * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | FilterMode | filter = FILTER_LINEAR |
| | ) | | |
Produce the segmentation overlay alpha blended on top of the original image.
**Deprecated:**this overload is for legacy compatibility. It expects float4 RGBA image. Parameters
| input | float4 input image in CUDA device memory, RGBA colorspace with values 0-255. | | output | float4 output image in CUDA device memory, RGBA colorspace with values 0-255. | | width | width of the input image in pixels. | | height | height of the input image in pixels. | | ignore_class | label name of class to ignore in the classification (or NULL to process all). | | type | overlay visualization options |
Returnstrue on success, false on error.
template<typename T >
|
| bool segNet::Overlay | ( | T * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | FilterMode | filter = FILTER_LINEAR |
| | ) | | |
| inline |
Produce the segmentation overlay alpha blended on top of the original image.
Parameters
| output | output image in CUDA device memory, RGB/RGBA colorspace with values 0-255. | | width | width of the input image in pixels. | | height | height of the input image in pixels. | | ignore_class | label name of class to ignore in the classification (or NULL to process all). | | type | overlay visualization options |
Returnstrue on success, false on error.
| bool segNet::Overlay | ( | void * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | imageFormat | format, |
| | | FilterMode | filter = FILTER_LINEAR |
| | ) | | |
Produce the segmentation overlay alpha blended on top of the original image.
Parameters
| output | output image in CUDA device memory, RGB/RGBA colorspace with values 0-255. | | width | width of the input image in pixels. | | height | height of the input image in pixels. | | ignore_class | label name of class to ignore in the classification (or NULL to process all). | | type | overlay visualization options |
Returnstrue on success, false on error.
|
| bool segNet::overlayLinear | ( | void * | input, | | | | uint32_t | in_width, | | | | uint32_t | in_height, | | | | imageFormat | in_format, | | | | void * | output, | | | | uint32_t | out_width, | | | | uint32_t | out_height, | | | | imageFormat | out_format, | | | | bool | mask_only | | | ) | | |
| protected |
|
| bool segNet::overlayPoint | ( | void * | input, | | | | uint32_t | in_width, | | | | uint32_t | in_height, | | | | imageFormat | in_format, | | | | void * | output, | | | | uint32_t | out_width, | | | | uint32_t | out_height, | | | | imageFormat | out_format, | | | | bool | mask_only | | | ) | | |
| protected |
| bool segNet::Process | ( | float * | input, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | const char * | ignore_class = "void" |
| | ) | | |
Perform the initial inferencing processing portion of the segmentation.
The results can then be visualized using the Overlay() and Mask() functions.
**Deprecated:**this overload is for legacy compatibility. It expects float4 RGBA image. Parameters
| input | float4 input image in CUDA device memory, RGBA colorspace with values 0-255. | | width | width of the input image in pixels. | | height | height of the input image in pixels. | | ignore_class | label name of class to ignore in the classification (or NULL to process all). |
template<typename T >
|
| bool segNet::Process | ( | T * | input, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | const char * | ignore_class = "void" |
| | ) | | |
| inline |
Perform the initial inferencing processing portion of the segmentation.
The results can then be visualized using the Overlay() and Mask() functions.
Parameters
| input | the input image in CUDA device memory, with pixel values 0-255. | | width | width of the input image in pixels. | | height | height of the input image in pixels. | | ignore_class | label name of class to ignore in the classification (or NULL to process all). |
| bool segNet::Process | ( | void * | input, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | imageFormat | format, |
| | | const char * | ignore_class = "void" |
| | ) | | |
Perform the initial inferencing processing portion of the segmentation.
The results can then be visualized using the Overlay() and Mask() functions.
Parameters
| input | the input image in CUDA device memory, with pixel values 0-255. | | width | width of the input image in pixels. | | height | height of the input image in pixels. | | ignore_class | label name of class to ignore in the classification (or NULL to process all). |
|
| bool segNet::saveClassLegend | ( | const char * | filename | ) | |
| protected |
| void segNet::SetClassColor | ( | uint32_t | classIndex, | | | | const float4 & | color | | | ) | | |
Set the visualization color of a particular class of object.
| void segNet::SetClassColor | ( | uint32_t | classIndex, |
| | | float | r, |
| | | float | g, |
| | | float | b, |
| | | float | a = 255.0f |
| | ) | | |
Set the visualization color of a particular class of object.
| void segNet::SetOverlayAlpha | ( | float | alpha, |
| | | bool | explicit_exempt = true |
| | ) | | |
Set overlay alpha blending value for all classes (between 0-255), (optionally except for those that have been explicitly set).
|
| static const char* segNet::Usage | ( | | ) | |
| inlinestatic |
Usage string for command line arguments to Create()
|
| static uint32_t segNet::VisualizationFlagsFromStr | ( | const char * | str, |
| | | uint32_t | default_value = VISUALIZE_OVERLAY |
| | ) | | |
| static |
Parse a string of one of more VisualizationMode values.
Valid strings are "overlay" "mask" "overlay|mask" "overlay,mask" ect.
|
| float4* segNet::mClassColors |
| protected |
array of overlay colors in shared CPU/GPU memory
|
| std::vector<std::string> segNet::mClassLabels |
| protected |
|
| uint8_t* segNet::mClassMap |
| protected |
runtime buffer for the argmax-classified class index of each tile
|
| std::string segNet::mClassPath |
| protected |
|
| bool* segNet::mColorsAlphaSet |
| protected |
true if class color had been explicitly set from file or user
|
| imageFormat segNet::mLastInputFormat |
| protected |
pixel format of last input image
|
| uint32_t segNet::mLastInputHeight |
| protected |
height in pixels of last input image to be processed
|
| void* segNet::mLastInputImg |
| protected |
last input image to be processed, stored for overlay
|
| uint32_t segNet::mLastInputWidth |
| protected |
width in pixels of last input image to be processed
| #define SEGNET_DEFAULT_ALPHA 150 |
Default alpha blending value used during overlay.
| #define SEGNET_DEFAULT_INPUT "input_0" |
Name of default input blob for segmentation model.
| #define SEGNET_DEFAULT_OUTPUT "output_0" |
Name of default output blob for segmentation model.
| #define SEGNET_MODEL_TYPE "segmentation" |
The model type for segNet in data/networks/models.json.
| #define SEGNET_USAGE_STRING |
Value:
"segNet arguments: \n" \
" --network=NETWORK pre-trained model to load, one of the following:\n" \
" * fcn-resnet18-cityscapes-512x256\n" \
" * fcn-resnet18-cityscapes-1024x512\n" \
" * fcn-resnet18-cityscapes-2048x1024\n" \
" * fcn-resnet18-deepscene-576x320\n" \
" * fcn-resnet18-deepscene-864x480\n" \
" * fcn-resnet18-mhp-512x320\n" \
" * fcn-resnet18-mhp-640x360\n" \
" * fcn-resnet18-voc-320x320 (default)\n" \
" * fcn-resnet18-voc-512x320\n" \
" * fcn-resnet18-sun-512x400\n" \
" * fcn-resnet18-sun-640x512\n" \
" --model=MODEL path to custom model to load (caffemodel, uff, or onnx)\n" \
" --prototxt=PROTOTXT path to custom prototxt to load (for .caffemodel only)\n" \
" --labels=LABELS path to text file containing the labels for each class\n" \
" --colors=COLORS path to text file containing the colors for each class\n" \
" --input-blob=INPUT name of the input layer (default: '" SEGNET_DEFAULT_INPUT "')\n" \
" --output-blob=OUTPUT name of the output layer (default: '" SEGNET_DEFAULT_OUTPUT "')\n" \
" --alpha=ALPHA overlay alpha blending value, range 0-255 (default: 150)\n" \
" --visualize=VISUAL visualization flags (e.g. --visualize=overlay,mask)\n" \
" valid combinations are: 'overlay', 'mask'\n" \
" --profile enable layer profiling in TensorRT\n\n"
Standard command-line options able to be passed to segNet::Create()
#define SEGNET_DEFAULT_INPUT
Name of default input blob for segmentation model.
Definition: segNet.h:34
#define SEGNET_DEFAULT_OUTPUT
Name of default output blob for segmentation model.
Definition: segNet.h:40