openvino/samples/cpp/model_creation_sample

Model Creation C++ Sample

This sample demonstrates how to execute an synchronous inference using model built on the fly which uses weights from LeNet classification model, which is known to work well on digit classification tasks.

You do not need an XML file to create a model. The API of ov::Model allows creating a model on the fly from the source code.

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

Requirements

Options	Values
Validated Models	LeNet
Model Format	model weights file (*.bin)
Validated images	single-channel MNIST ubyte images
Supported devices	All
Other language realization	Python

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

Feature	API	Description
OpenVINO Runtime Info	ov::Core::get_versions	Get device plugins versions
Shape Operations	ov::Output::get_shape,	Operate with shape
	ov::Shape::size,
	ov::shape_size
Tensor Operations	ov::Tensor::get_byte_size,	Get tensor byte size and its data
	ov::Tensor:data
Model Operations	ov::set_batch	Operate with model batch size
Infer Request Operations	ov::InferRequest::get_input_tensor	Get a input tensor
Model creation objects	ov::opset8::Parameter,	Used to construct an OpenVINO model
	ov::Node::output,
	ov::opset8::Constant,
	ov::opset8::Convolution,
	ov::opset8::Add,
	ov::opset1::MaxPool,
	ov::opset8::Reshape,
	ov::opset8::MatMul,
	ov::opset8::Relu,
	ov::opset8::Softmax,
	ov::descriptor::Tensor::set_names,
	ov::opset8::Result,
	ov::Model,
	ov::ParameterVector::vector

<<<<<<< HEAD Basic OpenVINO™ Runtime API is covered by Hello Classification C++ sample.

Basic OpenVINO™ Runtime API is covered by Hello Classification C++ sample.

cf2b238df2 (Merge samples)