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.