openvino/samples/python/hello_classification

Hello Classification Python Sample

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

Models with only 1 input and output are supported.

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

Requirements

Options	Values
Validated Models	alexnet,
	googlenet-v1
Model Format	OpenVINO™ toolkit Intermediate Representation (.xml + .bin), ONNX (.onnx)
Supported devices	All
Other language realization	C++,
	C

The following Python API is used in the application:

Feature	API	Description
Basic Infer Flow	openvino.runtime.Core ,
	openvino.runtime.Core.read_model,
	openvino.runtime.Core.compile_model	Common API to do inference
Synchronous Infer	openvino.runtime.CompiledModel.infer_new_request,	Do synchronous inference
Model Operations	openvino.runtime.Model.inputs,	Managing of model
	openvino.runtime.Model.outputs,
Preprocessing	openvino.preprocess.PrePostProcessor,	Set image of the original size as input for a model with other input size.
	openvino.preprocess.InputTensorInfo.set_element_type,	Resize and layout conversions will be performed automatically by the corresponding plugin just before inference
	openvino.preprocess.InputTensorInfo.set_layout,
	openvino.preprocess.InputTensorInfo.set_spatial_static_shape,
	openvino.preprocess.PreProcessSteps.resize,
	openvino.preprocess.InputModelInfo.set_layout,
	openvino.preprocess.OutputTensorInfo.set_element_type,
	openvino.preprocess.PrePostProcessor.build