openvino/samples/cpp/classification_sample_async
Maciej Smyk 8d49595476
[DOCS] Update of hyperlinks to 2024 + new ov homepage diagram image for master (#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 07:54:04 +00:00
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CMakeLists.txt Moved cmake functions, variables to API 2.0 naming style (#20281) 2023-10-09 22:30:32 +04:00
README.md [DOCS] Update of hyperlinks to 2024 + new ov homepage diagram image for master (#23091) 2024-02-28 07:54:04 +00:00
classification_sample_async.h Updated copyright headers (#15124) 2023-01-16 11:02:17 +04:00
main.cpp fix a wrong comment (#20307) 2023-10-09 12:44:42 +04:00

README.md

Image Classification Async C++ Sample

This sample demonstrates how to do inference of image classification models using Asynchronous Inference Request API.

Models with only one input and output are supported.

In addition to regular images, the sample also supports single-channel ubyte images as an input for LeNet model.

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

Requirements

Options Values
Model Format OpenVINO™ toolkit Intermediate Representation (*.xml + *.bin), ONNX (*.onnx)
Supported devices All
Other language realization Python

The following C++ API is used in the application:

Feature API Description
Asynchronous Infer ov::InferRequest::start_async, ov::InferRequest::set_callback Do asynchronous inference with callback.
Model Operations ov::Output::get_shape, ov::set_batch Manage the model, operate with its batch size. Set batch size using input image count.
Infer Request Operations ov::InferRequest::get_input_tensor Get an input tensor.
Tensor Operations ov::shape_size, ov::Tensor::data Get a tensor shape size and its data.