imageNet Member List

This is the complete list of members for imageNet, including all inherited members.

ALEXNET enum value	imageNet
AllowGPUFallback() const	tensorNet	inline
Classify(float *rgba, uint32_t width, uint32_t height, float *confidence=NULL)	imageNet
Classify(float *confidence=NULL)	imageNet
Create(NetworkType networkType=GOOGLENET, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)	imageNet	static
Create(const char *prototxt_path, const char *model_path, const char *mean_binary, const char *class_labels, const char *input=IMAGENET_DEFAULT_INPUT, const char *output=IMAGENET_DEFAULT_OUTPUT, uint32_t maxBatchSize=DEFAULT_MAX_BATCH_SIZE, precisionType precision=TYPE_FASTEST, deviceType device=DEVICE_GPU, bool allowGPUFallback=true)	imageNet	static
Create(int argc, char **argv)	imageNet	static
CreateStream(bool nonBlocking=true)	tensorNet
CUSTOM enum value	imageNet
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
FindFastestPrecision(deviceType device=DEVICE_GPU, bool allowInt8=true)	tensorNet	static
GetClassDesc(uint32_t index) const	imageNet	inline
GetClassPath() const	imageNet	inline
GetClassSynset(uint32_t index) const	imageNet	inline
GetDevice() const	tensorNet	inline
GetModelPath() const	tensorNet	inline
GetModelType() const	tensorNet	inline
GetNetworkName() const	imageNet	inline
GetNetworkTime()	tensorNet	inline
GetNetworkType() const	imageNet	inline
GetNumClasses() const	imageNet	inline
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
GOOGLENET enum value	imageNet
GOOGLENET_12 enum value	imageNet
gProfiler	tensorNet	protected
imageNet()	imageNet	protected
INCEPTION_V4 enum value	imageNet
init(NetworkType networkType, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback)	imageNet	protected
init(const char *prototxt_path, const char *model_path, const char *mean_binary, const char *class_path, const char *input, const char *output, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback)	imageNet	protected
IsModelType(modelType type) const	tensorNet	inline
IsPrecision(precisionType type) const	tensorNet	inline
loadClassInfo(const char *filename)	imageNet	protected
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 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
mAllowGPUFallback	tensorNet	protected
mCacheCalibrationPath	tensorNet	protected
mCacheEnginePath	tensorNet	protected
mClassDesc	imageNet	protected
mClassPath	imageNet	protected
mClassSynset	imageNet	protected
mContext	tensorNet	protected
mCustomClasses	imageNet	protected
mDevice	tensorNet	protected
mEnableDebug	tensorNet	protected
mEnableProfiler	tensorNet	protected
mEngine	tensorNet	protected
mEventsCPU	tensorNet	protected
mEventsGPU	tensorNet	protected
mHeight	tensorNet	protected
mInfer	tensorNet	protected
mInputBlobName	tensorNet	protected
mInputCPU	tensorNet	protected
mInputCUDA	tensorNet	protected
mInputDims	tensorNet	protected
mInputSize	tensorNet	protected
mMaxBatchSize	tensorNet	protected
mMeanPath	tensorNet	protected
mModelPath	tensorNet	protected
mModelType	tensorNet	protected
mNetworkType	imageNet	protected
mOutputClasses	imageNet	protected
mOutputs	tensorNet	protected
mPrecision	tensorNet	protected
mProfilerQueriesDone	tensorNet	protected
mProfilerQueriesUsed	tensorNet	protected
mProfilerTimes	tensorNet	protected
mPrototxtPath	tensorNet	protected
mStream	tensorNet	protected
mWidth	tensorNet	protected
NetworkType enum name	imageNet
NetworkTypeFromStr(const char *model_name)	imageNet	static
NetworkTypeToStr(NetworkType network)	imageNet	static
PreProcess(float *rgba, uint32_t width, uint32_t height)	imageNet
PrintProfilerTimes()	tensorNet	inline
Process()	imageNet
ProfileModel(const std::string &deployFile, const std::string &modelFile, const char *input, const Dims3 &inputDims, const std::vector< std::string > &outputs, uint32_t maxBatchSize, precisionType precision, deviceType device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator, std::ostream &modelStream)	tensorNet	protected
PROFILER_BEGIN(profilerQuery query)	tensorNet	inlineprotected
PROFILER_END(profilerQuery query)	tensorNet	inlineprotected
PROFILER_QUERY(profilerQuery query)	tensorNet	inlineprotected
RESNET_101 enum value	imageNet
RESNET_152 enum value	imageNet
RESNET_18 enum value	imageNet
RESNET_50 enum value	imageNet
SetStream(cudaStream_t stream)	tensorNet
tensorNet()	tensorNet	protected
Usage()	imageNet	inlinestatic
VGG_16 enum value	imageNet
VGG_19 enum value	imageNet
~imageNet()	imageNet	virtual
~tensorNet()	tensorNet	virtual