openvino/samples/cpp/classification_sample_async
Jacek Pawlak 239466ca5d
copyright year update (#23370)
New PR due to merge
conflicts(https://github.com/openvinotoolkit/openvino/pull/22917)

Updated the copyright year from 2018-2023 to 2018-2024 in all openvino
files

Ref. to script: CVS-101144

Command used:
```bash
git grep -lz '2018-2023 Intel Corporation' | xargs -0 sed -i '' -e 's/2018-2023 Intel Corporation/2018-2024 Intel Corporation/g'
```
2024-03-14 09:37:02 +00:00
..
CMakeLists.txt copyright year update (#23370) 2024-03-14 09:37:02 +00:00
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 copyright year update (#23370) 2024-03-14 09:37:02 +00:00
main.cpp copyright year update (#23370) 2024-03-14 09:37:02 +00:00

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.