Add Streamed transform.

[gleize]

Motivation and Context

There are currently no easy way to handle the processing / transform of large video files without loading them fully in memory (which can blow-up rather quickly).
The proposed solution tackles that issue by making transforms iterable over clip of upper bounded duration.

Example :

iterable_transform = Streamed(
  clip_duration=2.,
  clip_transform=BlaBlaClipTransform(...),
  return_iterable=True,
)
for transformed_clip in iterable_transform(video):
  clip_result = model(transformed_clip)

How Has This Been Tested

Added unit test and ran python -m unittest discover -v -s ./tests -p test_transforms.py.
I'm also using this same code in my own training pipeline.

Types of changes

• Docs change / refactoring / dependency upgrade
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Breaking change (fix or feature that would cause existing functionality to change)

Checklist

• My code follows the code style of this project.
• My change requires a change to the documentation.
• I have updated the documentation accordingly.
• I have read the CONTRIBUTING document.
• I have completed my CLA (see CONTRIBUTING)
• I have added tests to cover my changes.
• All new and existing tests passed.

[gleize]

Any update / feedback on this ? It's been there for a while.