docs/html/group__poseNet.html
| | Jetson Inference
DNN Vision Library |
poseNet DNN Vision Library (jetson-inference)
Pose estimation DNN. More...
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| class | poseNet |
| | Pose estimation models with TensorRT support. More...
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| #define | POSENET_DEFAULT_INPUT "input" |
| | Name of default input blob for pose estimation ONNX model. More...
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| #define | POSENET_DEFAULT_CMAP "cmap" |
| | Name of default output blob of the confidence map for pose estimation ONNX model. More...
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| #define | POSENET_DEFAULT_PAF "paf" |
| | Name of default output blob of the Part Affinity Field (PAF) for pose estimation ONNX model. More...
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| #define | POSENET_DEFAULT_THRESHOLD 0.15f |
| | Default value of the minimum confidence threshold. More...
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| #define | POSENET_DEFAULT_KEYPOINT_SCALE 0.0052f |
| | Default scale used for drawing keypoint circles. More...
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| #define | POSENET_DEFAULT_LINK_SCALE 0.0013f |
| | Default scale used for drawing link lines. More...
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| #define | POSENET_MODEL_TYPE "pose" |
| | The model type for poseNet in data/networks/models.json. More...
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Pose estimation DNN.
| class poseNet |
Pose estimation models with TensorRT support.
Inheritance diagram for poseNet:
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| enum | OverlayFlags {
OVERLAY_NONE = 0, OVERLAY_BOX = (1 << 0), OVERLAY_LINKS = (1 << 1), OVERLAY_KEYPOINTS = (1 << 2),
OVERLAY_DEFAULT = OVERLAY_LINKS|OVERLAY_KEYPOINTS
} |
| | Overlay flags (can be OR'd together). More...
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| virtual | ~poseNet () |
| | Destory. More...
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| |
| template<typename T > |
| bool | Process (T *image, uint32_t width, uint32_t height, std::vector< ObjectPose > &poses, uint32_t overlay=OVERLAY_DEFAULT) |
| | Perform pose estimation on the given image, returning object poses, and overlay the results. More...
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| bool | Process (void *image, uint32_t width, uint32_t height, imageFormat format, std::vector< ObjectPose > &poses, uint32_t overlay=OVERLAY_DEFAULT) |
| | Perform pose estimation on the given image, and overlay the results. More...
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| |
| template<typename T > |
| bool | Process (T *image, uint32_t width, uint32_t height, uint32_t overlay=OVERLAY_DEFAULT) |
| | Perform pose estimation on the given image, and overlay the results. More...
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| bool | Process (void *image, uint32_t width, uint32_t height, imageFormat format, uint32_t overlay=OVERLAY_DEFAULT) |
| | Perform pose estimation on the given image, and overlay the results. More...
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| template<typename T > |
| bool | Overlay (T *input, T *output, uint32_t width, uint32_t height, const std::vector< ObjectPose > &poses, uint32_t overlay=OVERLAY_DEFAULT) |
| | Overlay the results on the image. More...
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| bool | Overlay (void *input, void *output, uint32_t width, uint32_t height, imageFormat format, const std::vector< ObjectPose > &poses, uint32_t overlay=OVERLAY_DEFAULT) |
| | Overlay the results on the image. More...
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| float | GetThreshold () const |
| | Retrieve the minimum confidence threshold. More...
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| void | SetThreshold (float threshold) |
| | Set the minimum confidence threshold. More...
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| const char * | GetCategory () const |
| | Get the category of objects that are detected (e.g. More...
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| uint32_t | GetNumKeypoints () const |
| | Get the number of keypoints in the topology. More...
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| const char * | GetKeypointName (uint32_t index) const |
| | Get the name of a keypoint in the topology by it's ID. More...
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| int | FindKeypointID (const char *name) const |
| | Find the ID of a keypoint by name, or return -1 if not found. More...
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| float4 | GetKeypointColor (uint32_t index) const |
| | Get the overlay color of a keypoint. More...
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| void | SetKeypointColor (uint32_t index, const float4 &color) |
| | Set the overlay color for a keypoint. More...
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| void | SetKeypointAlpha (uint32_t index, float alpha) |
| | Set the alpha channel for a keypoint color (between 0-255). More...
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| void | SetKeypointAlpha (float alpha) |
| | Set the alpha channel for all keypoints colors used during overlay. More...
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| float | GetKeypointScale () const |
| | Get the scale used to calculate the radius of keypoints relative to input image dimensions. More...
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| void | SetKeypointScale (float scale) |
| | Set the scale used to calculate the radius of keypoint circles. More...
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| float | GetLinkScale () const |
| | Get the scale used to calculate the width of link lines relative to input image dimensions. More...
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| void | SetLinkScale (float scale) |
| | Set the scale used to calculate the width of link lines. 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 | OverlayFlagsFromStr (const char *flags) |
| | Parse a string sequence into OverlayFlags enum. More...
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| static poseNet * | Create (const char *network="resnet18-body", float threshold=POSENET_DEFAULT_THRESHOLD, 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 poseNet * | Create (const char *model_path, const char *topology, const char *colors, float threshold=POSENET_DEFAULT_THRESHOLD, const char *input=POSENET_DEFAULT_INPUT, const char *cmap=POSENET_DEFAULT_CMAP, const char *paf=POSENET_DEFAULT_PAF, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true) |
| | Load a custom network instance. More...
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| static poseNet * | Create (int argc, char **argv) |
| | Load a new network instance by parsing the command line. More...
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| static poseNet * | 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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| | poseNet () |
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| bool | init (const char *model_path, const char *topology, const char *colors, float threshold, const char *input, const char *cmap, const char *paf, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback) |
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| bool | postProcess (std::vector< ObjectPose > &poses, uint32_t width, uint32_t height) |
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| bool | loadTopology (const char *json_path, Topology *topology) |
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| bool | loadKeypointColors (const char *filename) |
| |
| 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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| | Topology | mTopology | | | | float | mThreshold | | | | float | mLinkScale | | | | float | mKeypointScale | | | | float4 * | mKeypointColors | | | | int * | mPeaks | | | | int * | mPeakCounts | | | | int * | mConnections | | | | int * | mObjects | | | | int | mNumObjects | | | | float * | mRefinedPeaks | | | | float * | mScoreGraph | | | | void * | mAssignmentWorkspace | | | | void * | mConnectionWorkspace | | | | 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 | | | |
| | static const int | CMAP_WINDOW_SIZE =5 | | | | static const int | PAF_INTEGRAL_SAMPLES =7 | | | | static const int | MAX_LINKS =100 | | | | static const int | MAX_OBJECTS =100 | | |
| enum poseNet::OverlayFlags |
Overlay flags (can be OR'd together).
| Enumerator |
|---|
| OVERLAY_NONE |
No overlay.
| | OVERLAY_BOX |
Overlay object bounding boxes.
| | OVERLAY_LINKS |
Overlay the skeleton links (bones) as lines
| | OVERLAY_KEYPOINTS |
Overlay the keypoints (joints) as circles.
| | OVERLAY_DEFAULT | |
|
| virtual poseNet::~poseNet | ( | | ) | |
| virtual |
Destory.
|
| poseNet::poseNet | ( | | ) | |
| protected |
|
| static poseNet* poseNet::Create | ( | const char * | model_path, |
| | | const char * | topology, |
| | | const char * | colors, |
| | | float | threshold = POSENET_DEFAULT_THRESHOLD, |
| | | const char * | input = POSENET_DEFAULT_INPUT, |
| | | const char * | cmap = POSENET_DEFAULT_CMAP, |
| | | const char * | paf = POSENET_DEFAULT_PAF, |
| | | uint32_t | maxBatchSize = DEFAULT_MAX_BATCH_SIZE, |
| | | precisionType | precision = TYPE_FASTEST, |
| | | deviceType | device = DEVICE_GPU, |
| | | bool | allowGPUFallback = true |
| | ) | | |
| static |
Load a custom network instance.
Parameters
| model_path | File path to the ONNX model | | topology | File path to the topology JSON | | colors | File path to the keypoint colors text file | | threshold | default minimum confidence thrshold | | input | Name of the input layer blob. | | cmap | Name of the output confidence map layer. | | paf | Name of the output Part Affinity Field (PAF) layer. | | maxBatchSize | The maximum batch size that the network will support and be optimized for. |
|
| static poseNet* poseNet::Create | ( | const char * | network = "resnet18-body", |
| | | float | threshold = POSENET_DEFAULT_THRESHOLD, |
| | | uint32_t | maxBatchSize = DEFAULT_MAX_BATCH_SIZE, |
| | | precisionType | precision = TYPE_FASTEST, |
| | | deviceType | device = DEVICE_GPU, |
| | | bool | allowGPUFallback = true |
| | ) | | |
| static |
Load a pre-trained model.
Parameters
| network | type of pre-supported network to load ( |
See alsoPOSENET_USAGE_STRING for models) Parameters
| threshold | default minimum threshold for detection | | maxBatchSize | The maximum batch size that the network will support and be optimized for. |
|
| static poseNet* poseNet::Create | ( | const commandLine & | cmdLine | ) | |
| static |
Load a new network instance by parsing the command line.
|
| static poseNet* poseNet::Create | ( | int | argc, | | | | char ** | argv | | | ) | | |
| static |
Load a new network instance by parsing the command line.
|
| int poseNet::FindKeypointID | ( | const char * | name | ) | const |
| inline |
Find the ID of a keypoint by name, or return -1 if not found.
|
| const char* poseNet::GetCategory | ( | | ) | const |
| inline |
Get the category of objects that are detected (e.g.
'person', 'hand')
|
| float4 poseNet::GetKeypointColor | ( | uint32_t | index | ) | const |
| inline |
Get the overlay color of a keypoint.
|
| const char* poseNet::GetKeypointName | ( | uint32_t | index | ) | const |
| inline |
Get the name of a keypoint in the topology by it's ID.
|
| float poseNet::GetKeypointScale | ( | | ) | const |
| inline |
Get the scale used to calculate the radius of keypoints relative to input image dimensions.
|
| float poseNet::GetLinkScale | ( | | ) | const |
| inline |
Get the scale used to calculate the width of link lines relative to input image dimensions.
|
| uint32_t poseNet::GetNumKeypoints | ( | | ) | const |
| inline |
Get the number of keypoints in the topology.
|
| float poseNet::GetThreshold | ( | | ) | const |
| inline |
Retrieve the minimum confidence threshold.
|
| bool poseNet::init | ( | const char * | model_path, | | | | const char * | topology, | | | | const char * | colors, | | | | float | threshold, | | | | const char * | input, | | | | const char * | cmap, | | | | const char * | paf, | | | | uint32_t | maxBatchSize, | | | | precisionType | precision, | | | | deviceType | device, | | | | bool | allowGPUFallback | | | ) | | |
| protected |
|
| bool poseNet::loadKeypointColors | ( | const char * | filename | ) | |
| protected |
|
| bool poseNet::loadTopology | ( | const char * | json_path, | | | | Topology * | topology | | | ) | | |
| protected |
template<typename T >
|
| bool poseNet::Overlay | ( | T * | input, |
| | | T * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | const std::vector< ObjectPose > & | poses, |
| | | uint32_t | overlay = OVERLAY_DEFAULT |
| | ) | | |
| inline |
Overlay the results on the image.
| bool poseNet::Overlay | ( | void * | input, |
| | | void * | output, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | imageFormat | format, |
| | | const std::vector< ObjectPose > & | poses, |
| | | uint32_t | overlay = OVERLAY_DEFAULT |
| | ) | | |
Overlay the results on the image.
|
| static uint32_t poseNet::OverlayFlagsFromStr | ( | const char * | flags | ) | |
| static |
Parse a string sequence into OverlayFlags enum.
Valid flags are "none", "box", "label", and "conf" and it is possible to combine flags (bitwise OR) together with commas or pipe (|) symbol. For example, the string sequence "box,label,conf" would return the flags OVERLAY_BOX|OVERLAY_LABEL|OVERLAY_CONFIDENCE.
|
| bool poseNet::postProcess | ( | std::vector< ObjectPose > & | poses, | | | | uint32_t | width, | | | | uint32_t | height | | | ) | | |
| protected |
template<typename T >
|
| bool poseNet::Process | ( | T * | image, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | std::vector< ObjectPose > & | poses, |
| | | uint32_t | overlay = OVERLAY_DEFAULT |
| | ) | | |
| inline |
Perform pose estimation on the given image, returning object poses, and overlay the results.
Parameters
| [in] | image | input image in CUDA device memory (uchar3/uchar4/float3/float4) | | [in] | width | width of the input image in pixels. | | [in] | height | height of the input image in pixels. | | [out] | poses | array of ObjectPose structs that will be filled for each detected object. | | [in] | overlay | bitwise OR combination of overlay flags ( |
See alsoOverlayFlags and Overlay()), or OVERLAY_NONE. ReturnsTrue on success, or false if an error occurred.
template<typename T >
|
| bool poseNet::Process | ( | T * | image, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | uint32_t | overlay = OVERLAY_DEFAULT |
| | ) | | |
| inline |
Perform pose estimation on the given image, and overlay the results.
Parameters
| [in] | image | input image in CUDA device memory (uchar3/uchar4/float3/float4) | | [in] | width | width of the input image in pixels. | | [in] | height | height of the input image in pixels. | | [in] | overlay | bitwise OR combination of overlay flags ( |
See alsoOverlayFlags and Overlay()), or OVERLAY_NONE. ReturnsTrue on success, or false if an error occurred.
| bool poseNet::Process | ( | void * | image, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | imageFormat | format, |
| | | std::vector< ObjectPose > & | poses, |
| | | uint32_t | overlay = OVERLAY_DEFAULT |
| | ) | | |
Perform pose estimation on the given image, and overlay the results.
Parameters
| [in] | image | input image in CUDA device memory (uchar3/uchar4/float3/float4) | | [in] | width | width of the input image in pixels. | | [in] | height | height of the input image in pixels. | | [out] | poses | array of ObjectPose structs that will be filled for each detected object. | | [in] | overlay | bitwise OR combination of overlay flags ( |
See alsoOverlayFlags and Overlay()), or OVERLAY_NONE. ReturnsTrue on success, or false if an error occurred.
| bool poseNet::Process | ( | void * | image, |
| | | uint32_t | width, |
| | | uint32_t | height, |
| | | imageFormat | format, |
| | | uint32_t | overlay = OVERLAY_DEFAULT |
| | ) | | |
Perform pose estimation on the given image, and overlay the results.
Parameters
| [in] | image | input image in CUDA device memory (uchar3/uchar4/float3/float4) | | [in] | width | width of the input image in pixels. | | [in] | height | height of the input image in pixels. | | [in] | overlay | bitwise OR combination of overlay flags ( |
See alsoOverlayFlags and Overlay()), or OVERLAY_NONE. ReturnsTrue on success, or false if an error occurred.
|
| void poseNet::SetKeypointAlpha | ( | float | alpha | ) | |
| inline |
Set the alpha channel for all keypoints colors used during overlay.
|
| void poseNet::SetKeypointAlpha | ( | uint32_t | index, | | | | float | alpha | | | ) | | |
| inline |
Set the alpha channel for a keypoint color (between 0-255).
|
| void poseNet::SetKeypointColor | ( | uint32_t | index, | | | | const float4 & | color | | | ) | | |
| inline |
Set the overlay color for a keypoint.
|
| void poseNet::SetKeypointScale | ( | float | scale | ) | |
| inline |
Set the scale used to calculate the radius of keypoint circles.
This scale will be multiplied by the largest image dimension.
|
| void poseNet::SetLinkScale | ( | float | scale | ) | |
| inline |
Set the scale used to calculate the width of link lines.
This scale will be multiplied by the largest image dimension.
|
| void poseNet::SetThreshold | ( | float | threshold | ) | |
| inline |
Set the minimum confidence threshold.
|
| static const char* poseNet::Usage | ( | | ) | |
| inlinestatic |
Usage string for command line arguments to Create()
|
| const int poseNet::CMAP_WINDOW_SIZE =5 |
| staticprotected |
|
| void* poseNet::mAssignmentWorkspace |
| protected |
|
| const int poseNet::MAX_LINKS =100 |
| staticprotected |
|
| const int poseNet::MAX_OBJECTS =100 |
| staticprotected |
|
| int* poseNet::mConnections |
| protected |
|
| void* poseNet::mConnectionWorkspace |
| protected |
|
| float4* poseNet::mKeypointColors |
| protected |
|
| float poseNet::mKeypointScale |
| protected |
|
| float poseNet::mLinkScale |
| protected |
|
| int poseNet::mNumObjects |
| protected |
|
| int* poseNet::mObjects |
| protected |
|
| int* poseNet::mPeakCounts |
| protected |
|
| int* poseNet::mPeaks |
| protected |
|
| float* poseNet::mRefinedPeaks |
| protected |
|
| float* poseNet::mScoreGraph |
| protected |
|
| float poseNet::mThreshold |
| protected |
|
| Topology poseNet::mTopology |
| protected |
|
| const int poseNet::PAF_INTEGRAL_SAMPLES =7 |
| staticprotected |
| #define POSENET_DEFAULT_CMAP "cmap" |
Name of default output blob of the confidence map for pose estimation ONNX model.
| #define POSENET_DEFAULT_INPUT "input" |
Name of default input blob for pose estimation ONNX model.
| #define POSENET_DEFAULT_KEYPOINT_SCALE 0.0052f |
Default scale used for drawing keypoint circles.
This scale is multiplied by the largest image dimension to arrive at the radius.
| #define POSENET_DEFAULT_LINK_SCALE 0.0013f |
Default scale used for drawing link lines.
This scale is multiplied by the largest image dimension to arrive at the line width.
| #define POSENET_DEFAULT_PAF "paf" |
Name of default output blob of the Part Affinity Field (PAF) for pose estimation ONNX model.
| #define POSENET_DEFAULT_THRESHOLD 0.15f |
Default value of the minimum confidence threshold.
| #define POSENET_MODEL_TYPE "pose" |
The model type for poseNet in data/networks/models.json.