eVision Python API
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eVision.EasyDeepLearning.EDeepLearningBenchmark Class Reference

Deep Learning benchmark results. More...

Public Member Functions

None __init__ (self)
 Constructors.
None __init__ (self, eVision.EasyDeepLearning.EDeepLearningBenchmark other)
 Constructors.
None __init__ (self, eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings settings)
 Constructors.
bool IsValid (self)
 Whether the benchmark is ready and valid.
None Load (self, str filePath)
 Load a eVision.EasyDeepLearning.EDeepLearningBenchmark object.
None Load (self, eVision.ESerializer|None serializer)
 Load a eVision.EasyDeepLearning.EDeepLearningBenchmark object.
None Save (self, str filePath)
 Save the eVision.EasyDeepLearning.EDeepLearningBenchmark object.
None Save (self, eVision.ESerializer|None serializer)
 Save the eVision.EasyDeepLearning.EDeepLearningBenchmark object.

Protected Member Functions

eVision.EError _ErrorCode__getter (self)
 \cond
str _ErrorDescription__getter (self)
 \cond
int _NumImagesByInference__getter (self)
 \cond
int _NumInferences__getter (self)
 \cond
list[float] _TimePerInference__getter (self)
 \cond
int _NumDroppedInference__getter (self)
 \cond
float _MinLatency__getter (self)
 \cond
float _MaxLatency__getter (self)
 \cond
float _MeanLatency__getter (self)
 \cond
float _Throughput__getter (self)
 \cond
float _MinTimePerInference__getter (self)
 \cond
float _MaxTimePerInference__getter (self)
 \cond
float _MeanTimePerInference__getter (self)
 \cond
float _StdTimePerInference__getter (self)
 \cond
float _MinTimePerImage__getter (self)
 \cond
float _MaxTimePerImage__getter (self)
 \cond
float _MeanTimePerImage__getter (self)
 \cond
float _StdTimePerImage__getter (self)
 \cond
int _DatasetWidth__getter (self)
 \cond
int _DatasetHeight__getter (self)
 \cond
int _BenchmarkWidth__getter (self)
 \cond
int _BenchmarkHeight__getter (self)
 \cond
eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings _BenchmarkSettings__getter (self)
 \cond

Properties

 ErrorCode = property(_ErrorCode__getter, None)
 \endcond
 ErrorDescription = property(_ErrorDescription__getter, None)
 \endcond
 NumImagesByInference = property(_NumImagesByInference__getter, None)
 \endcond
 NumInferences = property(_NumInferences__getter, None)
 \endcond
 TimePerInference = property(_TimePerInference__getter, None)
 \endcond
 NumDroppedInference = property(_NumDroppedInference__getter, None)
 \endcond
 MinLatency = property(_MinLatency__getter, None)
 \endcond
 MaxLatency = property(_MaxLatency__getter, None)
 \endcond
 MeanLatency = property(_MeanLatency__getter, None)
 \endcond
 Throughput = property(_Throughput__getter, None)
 \endcond
 MinTimePerInference = property(_MinTimePerInference__getter, None)
 \endcond
 MaxTimePerInference = property(_MaxTimePerInference__getter, None)
 \endcond
 MeanTimePerInference = property(_MeanTimePerInference__getter, None)
 \endcond
 StdTimePerInference = property(_StdTimePerInference__getter, None)
 \endcond
 MinTimePerImage = property(_MinTimePerImage__getter, None)
 \endcond
 MaxTimePerImage = property(_MaxTimePerImage__getter, None)
 \endcond
 MeanTimePerImage = property(_MeanTimePerImage__getter, None)
 \endcond
 StdTimePerImage = property(_StdTimePerImage__getter, None)
 \endcond
 DatasetWidth = property(_DatasetWidth__getter, None)
 \endcond
 DatasetHeight = property(_DatasetHeight__getter, None)
 \endcond
 BenchmarkWidth = property(_BenchmarkWidth__getter, None)
 \endcond
 BenchmarkHeight = property(_BenchmarkHeight__getter, None)
 \endcond
 BenchmarkSettings = property(_BenchmarkSettings__getter, None)
 \endcond

Detailed Description

Deep Learning benchmark results.

Remarks:

License(s): EasyClassify or EasySegment or EasyLocate

Constructor & Destructor Documentation

◆ __init__() [1/3]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.__init__ ( self)

Constructors.

◆ __init__() [2/3]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.__init__ ( self,
eVision.EasyDeepLearning.EDeepLearningBenchmark other )

Constructors.

Parameters
otherThe other eVision.EasyDeepLearning.EDeepLearningBenchmark that we will copy into this one.

◆ __init__() [3/3]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.__init__ ( self,
eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings settings )

Constructors.

Parameters
settingsThe settings used to configure this eVision.EasyDeepLearning.EDeepLearningBenchmark.

Member Function Documentation

◆ _BenchmarkHeight__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._BenchmarkHeight__getter ( self)
protected

◆ _BenchmarkSettings__getter()

eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings eVision.EasyDeepLearning.EDeepLearningBenchmark._BenchmarkSettings__getter ( self)
protected

\cond

Settings of the benchmark.

◆ _BenchmarkWidth__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._BenchmarkWidth__getter ( self)
protected

◆ _DatasetHeight__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._DatasetHeight__getter ( self)
protected

\cond

Height of the dataset used to run the benchmark.

◆ _DatasetWidth__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._DatasetWidth__getter ( self)
protected

\cond

Width of the dataset used to run the benchmark.

◆ _ErrorCode__getter()

eVision.EError eVision.EasyDeepLearning.EDeepLearningBenchmark._ErrorCode__getter ( self)
protected

\cond

Error code thrown when computing the benchmark.

◆ _ErrorDescription__getter()

str eVision.EasyDeepLearning.EDeepLearningBenchmark._ErrorDescription__getter ( self)
protected

\cond

Description of the error that occurred during the benchmark.

◆ _MaxLatency__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MaxLatency__getter ( self)
protected

\cond

Maximum latency (time between the acquisition of an image and the computation of its result).

◆ _MaxTimePerImage__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MaxTimePerImage__getter ( self)
protected

◆ _MaxTimePerInference__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MaxTimePerInference__getter ( self)
protected

\cond

Maximum time for a single inference call (in seconds).

◆ _MeanLatency__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MeanLatency__getter ( self)
protected

\cond

Mean latency.

◆ _MeanTimePerImage__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MeanTimePerImage__getter ( self)
protected

◆ _MeanTimePerInference__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MeanTimePerInference__getter ( self)
protected

\cond

Mean time for a single inference call (in seconds).

◆ _MinLatency__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MinLatency__getter ( self)
protected

\cond

Minimum latency (time between the acquisition of an image and the computation of its result).

◆ _MinTimePerImage__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MinTimePerImage__getter ( self)
protected

◆ _MinTimePerInference__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._MinTimePerInference__getter ( self)
protected

\cond

Minimum time for a single inference call (in seconds).

◆ _NumDroppedInference__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._NumDroppedInference__getter ( self)
protected

\cond

The number of dropped inference call. Dropped inference call happens when simulating a camera framerate and the processing speed isn't fast enough.

◆ _NumImagesByInference__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._NumImagesByInference__getter ( self)
protected

\cond

The number of images that were processed together in one inference call to exploit the specified batch size. For EasyClassify and EasyLocate, this is equal to the batch size. For EasySegment, it depends on the number of patches that are extracted from input images.

◆ _NumInferences__getter()

int eVision.EasyDeepLearning.EDeepLearningBenchmark._NumInferences__getter ( self)
protected

\cond

Number of inference made in the benchmark. It is equal to eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.NumInferences

◆ _StdTimePerImage__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._StdTimePerImage__getter ( self)
protected

◆ _StdTimePerInference__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._StdTimePerInference__getter ( self)
protected

\cond

Standard deviation of the inference time for a single inference call (in seconds).

◆ _Throughput__getter()

float eVision.EasyDeepLearning.EDeepLearningBenchmark._Throughput__getter ( self)
protected

\cond

Number of images per second that were processed by the Deep Learning tool.

◆ _TimePerInference__getter()

list[float] eVision.EasyDeepLearning.EDeepLearningBenchmark._TimePerInference__getter ( self)
protected

\cond

Inference time (in nanoseconds) for all the inference calls (an inference processes eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference images together). A time of 0 means that the images for this inference call were dropped (not processed).

◆ IsValid()

bool eVision.EasyDeepLearning.EDeepLearningBenchmark.IsValid ( self)

Whether the benchmark is ready and valid.

◆ Load() [1/2]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.Load ( self,
eVision.ESerializer | None serializer )

Load a eVision.EasyDeepLearning.EDeepLearningBenchmark object.

The given eVision.ESerializer must have been created for reading.

Parameters
serializerPointer to the eVision.ESerializer created for reading.

◆ Load() [2/2]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.Load ( self,
str filePath )

Load a eVision.EasyDeepLearning.EDeepLearningBenchmark object.

The given eVision.ESerializer must have been created for reading.

Parameters
filePathFile path.

◆ Save() [1/2]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.Save ( self,
eVision.ESerializer | None serializer )

Save the eVision.EasyDeepLearning.EDeepLearningBenchmark object.

The given eVision.ESerializer must have been created for writing.

Parameters
serializerPointer to the eVision.ESerializer created for writing.

◆ Save() [2/2]

None eVision.EasyDeepLearning.EDeepLearningBenchmark.Save ( self,
str filePath )

Save the eVision.EasyDeepLearning.EDeepLearningBenchmark object.

The given eVision.ESerializer must have been created for writing.

Parameters
filePathFile path.

Property Documentation

◆ BenchmarkHeight

eVision.EasyDeepLearning.EDeepLearningBenchmark.BenchmarkHeight = property(_BenchmarkHeight__getter, None)
static

◆ BenchmarkSettings

eVision.EasyDeepLearning.EDeepLearningBenchmark.BenchmarkSettings = property(_BenchmarkSettings__getter, None)
static

\endcond

Settings of the benchmark.

◆ BenchmarkWidth

eVision.EasyDeepLearning.EDeepLearningBenchmark.BenchmarkWidth = property(_BenchmarkWidth__getter, None)
static

◆ DatasetHeight

eVision.EasyDeepLearning.EDeepLearningBenchmark.DatasetHeight = property(_DatasetHeight__getter, None)
static

\endcond

Height of the dataset used to run the benchmark.

◆ DatasetWidth

eVision.EasyDeepLearning.EDeepLearningBenchmark.DatasetWidth = property(_DatasetWidth__getter, None)
static

\endcond

Width of the dataset used to run the benchmark.

◆ ErrorCode

eVision.EasyDeepLearning.EDeepLearningBenchmark.ErrorCode = property(_ErrorCode__getter, None)
static

\endcond

Error code thrown when computing the benchmark.

◆ ErrorDescription

eVision.EasyDeepLearning.EDeepLearningBenchmark.ErrorDescription = property(_ErrorDescription__getter, None)
static

\endcond

Description of the error that occurred during the benchmark.

◆ MaxLatency

eVision.EasyDeepLearning.EDeepLearningBenchmark.MaxLatency = property(_MaxLatency__getter, None)
static

\endcond

Maximum latency (time between the acquisition of an image and the computation of its result).

◆ MaxTimePerImage

eVision.EasyDeepLearning.EDeepLearningBenchmark.MaxTimePerImage = property(_MaxTimePerImage__getter, None)
static

◆ MaxTimePerInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.MaxTimePerInference = property(_MaxTimePerInference__getter, None)
static

\endcond

Maximum time for a single inference call (in seconds).

◆ MeanLatency

eVision.EasyDeepLearning.EDeepLearningBenchmark.MeanLatency = property(_MeanLatency__getter, None)
static

\endcond

Mean latency.

◆ MeanTimePerImage

eVision.EasyDeepLearning.EDeepLearningBenchmark.MeanTimePerImage = property(_MeanTimePerImage__getter, None)
static

◆ MeanTimePerInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.MeanTimePerInference = property(_MeanTimePerInference__getter, None)
static

\endcond

Mean time for a single inference call (in seconds).

◆ MinLatency

eVision.EasyDeepLearning.EDeepLearningBenchmark.MinLatency = property(_MinLatency__getter, None)
static

\endcond

Minimum latency (time between the acquisition of an image and the computation of its result).

◆ MinTimePerImage

eVision.EasyDeepLearning.EDeepLearningBenchmark.MinTimePerImage = property(_MinTimePerImage__getter, None)
static

◆ MinTimePerInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.MinTimePerInference = property(_MinTimePerInference__getter, None)
static

\endcond

Minimum time for a single inference call (in seconds).

◆ NumDroppedInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.NumDroppedInference = property(_NumDroppedInference__getter, None)
static

\endcond

The number of dropped inference call. Dropped inference call happens when simulating a camera framerate and the processing speed isn't fast enough.

◆ NumImagesByInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference = property(_NumImagesByInference__getter, None)
static

\endcond

The number of images that were processed together in one inference call to exploit the specified batch size. For EasyClassify and EasyLocate, this is equal to the batch size. For EasySegment, it depends on the number of patches that are extracted from input images.

◆ NumInferences

eVision.EasyDeepLearning.EDeepLearningBenchmark.NumInferences = property(_NumInferences__getter, None)
static

\endcond

Number of inference made in the benchmark. It is equal to eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.NumInferences

◆ StdTimePerImage

eVision.EasyDeepLearning.EDeepLearningBenchmark.StdTimePerImage = property(_StdTimePerImage__getter, None)
static

◆ StdTimePerInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.StdTimePerInference = property(_StdTimePerInference__getter, None)
static

\endcond

Standard deviation of the inference time for a single inference call (in seconds).

◆ Throughput

eVision.EasyDeepLearning.EDeepLearningBenchmark.Throughput = property(_Throughput__getter, None)
static

\endcond

Number of images per second that were processed by the Deep Learning tool.

◆ TimePerInference

eVision.EasyDeepLearning.EDeepLearningBenchmark.TimePerInference = property(_TimePerInference__getter, None)
static

\endcond

Inference time (in nanoseconds) for all the inference calls (an inference processes eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference images together). A time of 0 means that the images for this inference call were dropped (not processed).