docs/html/classsegNet-members.html
| | Jetson Inference
DNN Vision Library |
segNet Member List
This is the complete list of members for segNet, including all inherited members.
| AllowGPUFallback() const | tensorNet | inline | | classify(const char *ignore_class) | segNet | protected | | ConfigureBuilder(nvinfer1::IBuilder *builder, uint32_t maxBatchSize, uint32_t workspaceSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator) | tensorNet | protected | | 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) | segNet | static | | 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) | segNet | static | | Create(int argc, char **argv) | segNet | static | | Create(const commandLine &cmdLine) | segNet | static | | CreateStream(bool nonBlocking=true) | tensorNet | | | DetectNativePrecision(const std::vector< precisionType > &nativeTypes, precisionType type) | tensorNet | static | | DetectNativePrecision(precisionType precision, deviceType device=DEVICE_GPU) | tensorNet | static | | DetectNativePrecisions(deviceType device=DEVICE_GPU) | tensorNet | static | | EnableDebug() | tensorNet | | | EnableLayerProfiler() | tensorNet | | | FILTER_LINEAR enum value | segNet | | | FILTER_POINT enum value | segNet | | | FilterMode enum name | segNet | | | FilterModeFromStr(const char *str, FilterMode default_value=FILTER_LINEAR) | segNet | static | | FindClassID(const char *label_name) | segNet | | | FindFastestPrecision(deviceType device=DEVICE_GPU, bool allowInt8=true) | tensorNet | static | | GenerateColor(uint32_t classID, float alpha=255.0f) | tensorNet | static | | GetClassColor(uint32_t id) const | segNet | inline | | GetClassDesc(uint32_t id) const | segNet | inline | | GetClassLabel(uint32_t id) const | segNet | inline | | GetClassPath() const | segNet | inline | | GetDevice() const | tensorNet | inline | | GetGridHeight() const | segNet | inline | | GetGridWidth() const | segNet | inline | | GetInputDims(uint32_t layer=0) const | tensorNet | inline | | GetInputHeight(uint32_t layer=0) const | tensorNet | inline | | GetInputLayers() const | tensorNet | inline | | GetInputPtr(uint32_t layer=0) const | tensorNet | inline | | GetInputSize(uint32_t layer=0) const | tensorNet | inline | | GetInputWidth(uint32_t layer=0) const | tensorNet | inline | | GetModelFilename() const | tensorNet | inline | | GetModelPath() const | tensorNet | inline | | GetModelType() const | tensorNet | inline | | GetNetworkFPS() | tensorNet | inline | | GetNetworkName() const | tensorNet | inline | | GetNetworkTime() | tensorNet | inline | | GetNumClasses() const | segNet | inline | | GetOutputDims(uint32_t layer=0) const | tensorNet | inline | | GetOutputHeight(uint32_t layer=0) const | tensorNet | inline | | GetOutputLayers() const | tensorNet | inline | | GetOutputPtr(uint32_t layer=0) const | tensorNet | inline | | GetOutputSize(uint32_t layer=0) const | tensorNet | inline | | GetOutputWidth(uint32_t layer=0) const | tensorNet | inline | | GetOverlayAlpha() const | segNet | | | GetPrecision() const | tensorNet | inline | | GetProfilerTime(profilerQuery query) | tensorNet | inline | | GetProfilerTime(profilerQuery query, profilerDevice device) | tensorNet | inline | | GetPrototxtPath() const | tensorNet | inline | | GetStream() const | tensorNet | inline | | gLogger | tensorNet | protected | | gProfiler | tensorNet | protected | | IsModelType(modelType type) const | tensorNet | inline | | IsPrecision(precisionType type) const | tensorNet | inline | | LoadClassColors(const char *filename, float4 *colors, int expectedClasses, float defaultAlpha=255.0f) | tensorNet | static | | LoadClassColors(const char *filename, float4 **colors, int expectedClasses, float defaultAlpha=255.0f) | tensorNet | static | | loadClassColors(const char *filename) | segNet | protected | | LoadClassLabels(const char *filename, std::vector< std::string > &descriptions, int expectedClasses=-1) | tensorNet | static | | LoadClassLabels(const char *filename, std::vector< std::string > &descriptions, std::vector< std::string > &synsets, int expectedClasses=-1) | tensorNet | static | | loadClassLabels(const char *filename) | segNet | protected | | 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) | tensorNet | | | 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) | tensorNet | | | 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) | tensorNet | | | LoadEngine(const char *filename, char **stream, size_t *size) | tensorNet | | | 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) | tensorNet | | | 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) | tensorNet | | | 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) | tensorNet | | | 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) | tensorNet | | | 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) | tensorNet | | | mAllowGPUFallback | tensorNet | protected | | Mask(T *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) | segNet | inline | | Mask(void *output, uint32_t width, uint32_t height, imageFormat format, FilterMode filter=FILTER_LINEAR) | segNet | | | Mask(float *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) | segNet | | | Mask(uint8_t *output, uint32_t width, uint32_t height) | segNet | | | mBindings | tensorNet | protected | | mCacheCalibrationPath | tensorNet | protected | | mCacheEnginePath | tensorNet | protected | | mChecksumPath | tensorNet | protected | | mClassColors | segNet | protected | | mClassLabels | segNet | protected | | mClassMap | segNet | protected | | mClassPath | segNet | protected | | mColorsAlphaSet | segNet | protected | | mContext | tensorNet | protected | | mDevice | tensorNet | protected | | mEnableDebug | tensorNet | protected | | mEnableProfiler | tensorNet | protected | | mEngine | tensorNet | protected | | mEventsCPU | tensorNet | protected | | mEventsGPU | tensorNet | protected | | mInfer | tensorNet | protected | | mInputs | tensorNet | protected | | mLastInputFormat | segNet | protected | | mLastInputHeight | segNet | protected | | mLastInputImg | segNet | protected | | mLastInputWidth | segNet | protected | | mMaxBatchSize | tensorNet | protected | | mMeanPath | tensorNet | protected | | mModelFile | tensorNet | protected | | mModelPath | tensorNet | protected | | mModelType | tensorNet | protected | | mOutputs | tensorNet | protected | | mPrecision | tensorNet | protected | | mProfilerQueriesDone | tensorNet | protected | | mProfilerQueriesUsed | tensorNet | protected | | mProfilerTimes | tensorNet | protected | | mPrototxtPath | tensorNet | protected | | mStream | tensorNet | protected | | mWorkspaceSize | tensorNet | protected | | Overlay(T *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) | segNet | inline | | Overlay(void *output, uint32_t width, uint32_t height, imageFormat format, FilterMode filter=FILTER_LINEAR) | segNet | | | Overlay(float *output, uint32_t width, uint32_t height, FilterMode filter=FILTER_LINEAR) | 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) | segNet | protected | | 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) | segNet | protected | | PrintProfilerTimes() | tensorNet | inline | | Process(T *input, uint32_t width, uint32_t height, const char *ignore_class="void") | segNet | inline | | Process(void *input, uint32_t width, uint32_t height, imageFormat format, const char *ignore_class="void") | segNet | | | Process(float *input, uint32_t width, uint32_t height, const char *ignore_class="void") | segNet | | | ProcessNetwork(bool sync=true) | tensorNet | protected | | 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) | tensorNet | protected | | PROFILER_BEGIN(profilerQuery query) | tensorNet | inlineprotected | | PROFILER_END(profilerQuery query) | tensorNet | inlineprotected | | PROFILER_QUERY(profilerQuery query) | tensorNet | inlineprotected | | saveClassLegend(const char *filename) | segNet | protected | | segNet() | segNet | protected | | SelectPrecision(precisionType precision, deviceType device=DEVICE_GPU, bool allowInt8=true) | tensorNet | static | | SetClassColor(uint32_t classIndex, const float4 &color) | segNet | | | SetClassColor(uint32_t classIndex, float r, float g, float b, float a=255.0f) | segNet | | | SetOverlayAlpha(float alpha, bool explicit_exempt=true) | segNet | | | SetStream(cudaStream_t stream) | tensorNet | | | tensorNet() | tensorNet | protected | | Usage() | segNet | inlinestatic | | ValidateEngine(const char *model_path, const char *cache_path, const char *checksum_path) | tensorNet | protected | | VisualizationFlags enum name | segNet | | | VisualizationFlagsFromStr(const char *str, uint32_t default_value=VISUALIZE_OVERLAY) | segNet | static | | VISUALIZE_MASK enum value | segNet | | | VISUALIZE_OVERLAY enum value | segNet | | | ~segNet() | segNet | virtual | | ~tensorNet() | tensorNet | virtual |