fix: Improve detection and classification pipelines

[antoniomtz]

PR Checklist

• Added label to the Pull Request for easier discoverability and search
• Commit Message meets guidelines as indicated in the URL https://github.com/intel-retail/automated-self-checkout/blob/main/CONTRIBUTING.md
• Every commit is a single defect fix and does not mix feature addition or changes
• Unit Tests have been added for new changes
• Updated Documentation as relevant to the changes
• All commented code has been removed
• If you've added a dependency, you've ensured license is compatible with repository license and clearly outlined the added dependency.
• PR change contains code related to security
• PR introduces changes that breaks compatibility with other modules (If YES, please provide details below)

What are you changing?

• Optimized pipelines for CPU and GPU
• README updates

Issue this PR will close

close: #issue_number

Anything the reviewer should know when reviewing this PR?

Test Instructions if applicable

Run:

DEVICE_ENV=res/all-gpu.env PIPELINE_SCRIPT=yolov5s_effnetb0.sh make run-demo

If the there are associated PRs in other repositories, please link them here (i.e. intel-retail/automated-self-checkout )

[NeethuES-intel]

Suggested change

	- [Run pipeline on integrated GPU](#run-pipeline-on-integrated-gpu)
	- [Run pipeline on integrated GPU (iGPU)](#run-pipeline-on-integrated-gpu)

[ejlee3]

Do we need to add or modify a make target to call the docker-compose-sensors along with the main compose file?

[antoniomtz]

Do we need to add or modify a make target to call the docker-compose-sensors along with the main compose file?

@ejlee3 I will create another make target for that compose. The reason is, if we want to run benchmarks, we don't want any extra overhead.

I will create a separate PR