[Custom Vision sample] improve performance for amr32v7 template

[czgtest]

• VSCode Version: 1.31.1
• OS Version: windows
• Extension Version:1.10.0-rc

Steps to Reproduce:
From your PC:

1. Clone this sample
2. Update the .env file with the values for your container registry and make sure that your docker engine has access to it
3. Build the entire solution by right-clicking on the deployment.template.json file and select Build and push IoT Edge Solution (this can take a while...especially to build open-cv, numpy and pillow...)

It need to run 3 docker file for CameraCapture.arm32v7 & SenseHatDisplay.arm32v7 & ImageClassifierService.arm32v7 image,
When build CameraCapture.arm32v7 docker file , step5,6,7 will take 6 hours , only 70% compiled in 4 and a half hours, it is so slow. Can we improve performance for arm32v7 template?

[adashen]

@czgtest please add the issue to the custom vision repo. I will close it here since it is not edge tooling issue.