openvino/samples/python/benchmark/sync_benchmark
Maciej Smyk 717875cd43
[DOCS] Update of hyperlinks to 2024 + new ov homepage diagram image for 2024 (#23132)
Port from https://github.com/openvinotoolkit/openvino/pull/23091

* Update of links in docs to 2024 in repo.
* Replaced ov homepage diagram with a new version without Kalid, MXNet
and Caffe
2024-02-28 12:27:23 +00:00
..
README.md [DOCS] Update of hyperlinks to 2024 + new ov homepage diagram image for 2024 (#23132) 2024-02-28 12:27:23 +00:00
sync_benchmark.py Extend sync benchmark CLI parameters (#20844) 2023-11-03 09:51:22 +01:00

README.md

Sync Benchmark Python Sample

This sample demonstrates how to estimate performance of a model using Synchronous Inference Request API. It makes sense to use synchronous inference only in latency oriented scenarios. Models with static input shapes are supported. Unlike demos this sample doesn't have other configurable command line arguments. Feel free to modify sample's source code to try out different options.

For more detailed information on how this sample works, check the dedicated article

Requirements

Options Values
Validated Models yolo-v3-tf,
face-detection-0200
Model Format OpenVINO™ toolkit Intermediate Representation
(*.xml + *.bin), ONNX (*.onnx)
Supported devices All
Other language realization C++

The following Python API is used in the application:

Feature API Description
OpenVINO Runtime Version [openvino.runtime.get_version] Get Openvino API version.
Basic Infer Flow [openvino.runtime.Core], Common API to do inference: compile a model,
[openvino.runtime.Core.compile_model], configure input tensors.
[openvino.runtime.InferRequest.get_tensor]
Synchronous Infer [openvino.runtime.InferRequest.infer], Do synchronous inference.
Model Operations [openvino.runtime.CompiledModel.inputs] Get inputs of a model.
Tensor Operations [openvino.runtime.Tensor.get_shape], Get a tensor shape and its data.
[openvino.runtime.Tensor.data]