added tensor and numpy array support for image input in Flux2KleinPipeline

[abhixb]

Fixed issue #13177

The problem

If you pass a tensor or numpy array as the image to the Klein pipeline, it errors even though the docstring explicitly says these types are supported. Three things cause this:

• The image processor's validation method has a hard isinstance check for PIL and just rejects everything else on the spot
• The image loop in the pipeline's call method does image_width, image_height = img.size which is PIL only on a tensor .size is a method, on a numpy array it's a single int, both explode when you try to unpack them
• The type annotation on the image parameter only mentions PIL types, so your IDE would tell you not to even try

The fix

• Added a to_pil helper on the image processor that converts tensors and numpy arrays into PIL images, PIL inputs just pass through
• Wired it into the validation method so it converts first, validates second, and returns a guaranteed PIL image
• The call method's image loop now uses that return value instead of throwing it away
• Updated the type annotation to match the docstring

Nothing changes for people already passing PIL images, same code path as before.

Tests

Added tests for tensor input, numpy input, and a list of tensors for multi-reference editing. Existing PIL test still passes. All 4 green locally.

[abhixb]

@sayakpaul hello can u please look into/review this