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. | |
Deep Learning benchmark results.
Remarks:
License(s): EasyClassify or EasySegment or EasyLocate
| None eVision.EasyDeepLearning.EDeepLearningBenchmark.__init__ | ( | self | ) |
Constructors.
| None eVision.EasyDeepLearning.EDeepLearningBenchmark.__init__ | ( | self, | |
| eVision.EasyDeepLearning.EDeepLearningBenchmark | other ) |
Constructors.
| other | The other eVision.EasyDeepLearning.EDeepLearningBenchmark that we will copy into this one. |
| None eVision.EasyDeepLearning.EDeepLearningBenchmark.__init__ | ( | self, | |
| eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings | settings ) |
Constructors.
| settings | The settings used to configure this eVision.EasyDeepLearning.EDeepLearningBenchmark. |
|
protected |
\cond
Height of the images generated in the benchmark. It depends on eVision.EasyDeepLearning.EDeepLearningBenchmark.DatasetHeight and eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.InternalResizeDisabled).
|
protected |
\cond
Settings of the benchmark.
|
protected |
\cond
Width of the images generated in the benchmark. It depends on eVision.EasyDeepLearning.EDeepLearningBenchmark.DatasetWidth and eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.InternalResizeDisabled).
|
protected |
\cond
Height of the dataset used to run the benchmark.
|
protected |
\cond
Width of the dataset used to run the benchmark.
|
protected |
\cond
Error code thrown when computing the benchmark.
|
protected |
\cond
Description of the error that occurred during the benchmark.
|
protected |
\cond
Maximum latency (time between the acquisition of an image and the computation of its result).
|
protected |
\cond
Maximum time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.MaxTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
protected |
\cond
Maximum time for a single inference call (in seconds).
|
protected |
\cond
Mean latency.
|
protected |
\cond
Mean time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.MeanTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
protected |
\cond
Mean time for a single inference call (in seconds).
|
protected |
\cond
Minimum latency (time between the acquisition of an image and the computation of its result).
|
protected |
\cond
Minimum time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.MinTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
protected |
\cond
Minimum time for a single inference call (in seconds).
|
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.
|
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.
|
protected |
\cond
Number of inference made in the benchmark. It is equal to eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.NumInferences
|
protected |
\cond
Standard deviation of the time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.StdTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
protected |
\cond
Standard deviation of the inference time for a single inference call (in seconds).
|
protected |
\cond
Number of images per second that were processed by the Deep Learning tool.
|
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).
| bool eVision.EasyDeepLearning.EDeepLearningBenchmark.IsValid | ( | self | ) |
Whether the benchmark is ready and valid.
| 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.
| serializer | Pointer to the eVision.ESerializer created for reading. |
| None eVision.EasyDeepLearning.EDeepLearningBenchmark.Load | ( | self, | |
| str | filePath ) |
Load a eVision.EasyDeepLearning.EDeepLearningBenchmark object.
The given eVision.ESerializer must have been created for reading.
| filePath | File path. |
| 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.
| serializer | Pointer to the eVision.ESerializer created for writing. |
| None eVision.EasyDeepLearning.EDeepLearningBenchmark.Save | ( | self, | |
| str | filePath ) |
Save the eVision.EasyDeepLearning.EDeepLearningBenchmark object.
The given eVision.ESerializer must have been created for writing.
| filePath | File path. |
|
static |
\endcond
Height of the images generated in the benchmark. It depends on eVision.EasyDeepLearning.EDeepLearningBenchmark.DatasetHeight and eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.InternalResizeDisabled).
|
static |
\endcond
Settings of the benchmark.
|
static |
\endcond
Width of the images generated in the benchmark. It depends on eVision.EasyDeepLearning.EDeepLearningBenchmark.DatasetWidth and eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.InternalResizeDisabled).
|
static |
\endcond
Height of the dataset used to run the benchmark.
|
static |
\endcond
Width of the dataset used to run the benchmark.
|
static |
\endcond
Error code thrown when computing the benchmark.
|
static |
\endcond
Description of the error that occurred during the benchmark.
|
static |
\endcond
Maximum latency (time between the acquisition of an image and the computation of its result).
|
static |
\endcond
Maximum time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.MaxTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
static |
\endcond
Maximum time for a single inference call (in seconds).
|
static |
\endcond
Mean latency.
|
static |
\endcond
Mean time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.MeanTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
static |
\endcond
Mean time for a single inference call (in seconds).
|
static |
\endcond
Minimum latency (time between the acquisition of an image and the computation of its result).
|
static |
\endcond
Minimum time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.MinTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
static |
\endcond
Minimum time for a single inference call (in seconds).
|
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.
|
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.
|
static |
\endcond
Number of inference made in the benchmark. It is equal to eVision.EasyDeepLearning.EDeepLearningBenchmarkSettings.NumInferences
|
static |
\endcond
Standard deviation of the time in seconds for an image (equal to eVision.EasyDeepLearning.EDeepLearningBenchmark.StdTimePerInference / eVision.EasyDeepLearning.EDeepLearningBenchmark.NumImagesByInference).
|
static |
\endcond
Standard deviation of the inference time for a single inference call (in seconds).
|
static |
\endcond
Number of images per second that were processed by the Deep Learning tool.
|
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).