🐞 Fix model-specific transforms for DRÆM and DSR

[abc-125]

📝 Description

These models do not use Imagenet normalization. They had configure_transforms() to handle it, but it is never called, so default transforms with Imagenet normalization are applied. The training code is below, printing image values show that they are not between 0 and 1, as they should be.

from anomalib.data import MVTecAD
from anomalib.models import Draem
from anomalib.engine import Engine

# Initialize components
datamodule = MVTecAD()
model = Draem()
engine = Engine()

# Train the model
engine.fit(datamodule=datamodule, model=model)

✨ Changes

This PR changes configure_transforms() in DRÆM and DSR to configure_pre_processor() to apply model-specific transforms properly.

Select what type of change your PR is:

• 🐞 Bug fix (non-breaking change which fixes an issue)
• 🔨 Refactor (non-breaking change which refactors the code base)
• 🚀 New feature (non-breaking change which adds functionality)
• 💥 Breaking change (fix or feature that would cause existing functionality to not work as expected)
• 📚 Documentation update
• 🔒 Security update

✅ Checklist

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• 📋 I have summarized my changes in the CHANGELOG and followed the guidelines for my type of change (skip for minor changes, documentation updates, and test enhancements).
• 📚 I have made the necessary updates to the documentation (if applicable).
• 🧪 I have written tests that support my changes and prove that my fix is effective or my feature works (if applicable).

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[samet-akcay]

Thanks for reporting this and proposing a solution, @abc-125!