Implement robust dataset validation and config file for Super Resolution#217
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abhiram123467 wants to merge 4 commits intoML4SCI:mainfrom
Open
Implement robust dataset validation and config file for Super Resolution#217abhiram123467 wants to merge 4 commits intoML4SCI:mainfrom
abhiram123467 wants to merge 4 commits intoML4SCI:mainfrom
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Added a robust loader for DeepLense .npy files that supports multiple formats and includes a PyTorch Dataset class for easy data handling.
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Description:
Resolves the feature request outlined in #196 (Follow-up to #135).
This PR introduces a lightweight validation pipeline for the Super-Resolution datasets to catch silent alignment and dimensionality errors before the training loop begins.
Changes included:
config.yaml: Externalizes dataset parameters (HR/LR paths, scale factor, patch size) to ensure reproducibility without requiring users to modify core training logic.validate_dataset.py: A pre-training utility that strictly asserts:scale_factor.