[Good First Issue]: Implement PostProcess "mean/scale" operators method

Context

Some customer need run super-resolution models, which need convert original NV12 video data to RGB format with scale/mean before inference and do reversed operations (RGB->NV12 and scale/mean) after inference. Current ov::preprocess::PostProcessSteps doesn't support RGB->NV12 and scale/mean, this ticket is used to implement "scale/mean" operator support.

What needs to be done?

PostProcess supports mean/scale operators:

ov::preprocess::PostProcessSteps &ov::preprocess::PreProcessSteps::mean(const float values);
ov::preprocess::PostProcessSteps &ov::preprocess::PreProcessSteps::mean(const std::vector<float> &values);
ov::preprocess::PostProcessSteps &ov::preprocess::PreProcessSteps::scale(const float values);
ov::preprocess::PostProcessSteps &ov::preprocess::PreProcessSteps::scale(const std::vector<float> &values);

1. Implement above 4 APIs in posprocess
2. Add test cases

Example Pull Requests

No response

Resources

• Contribution guide - start here!
• Intel DevHub Discord channel - engage in discussions, ask questions and talk to OpenVINO developers

target source code: https://github.com/openvinotoolkit/openvino/tree/master/src/core/include/openvino/core/preprocess https://github.com/openvinotoolkit/openvino/tree/master/src/core/src/preprocess

Contact points

@ilya-lavrenov @riverlijunjie

Ticket

No response