Add processed OCTID dataset with 5 experimental splits

README.md

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+# OCTID Processed Dataset
+
+Processed version of the OCTID retinal OCT dataset prepared for
+research experiments comparing Swin Transformer architectures.
+
+## Dataset Summary
+
+- Dataset: OCTID
+- Total images: 572
+- Number of classes: 5
+- Image size: 224 x 224
+- Image mode: RGB
+- Image format: JPEG
+
+## Classes
+
+| Class | Images |
+|---|---:|
+| Normal | 206 |
+| AMD | 55 |
+| CSR | 102 |
+| DR | 107 |
+| MH | 102 |
+| Total | 572 |
+
+## Preprocessing
+
+The preprocessing pipeline consists of:
+
+1. Aspect-ratio-preserving resize
+2. Center crop to 224 x 224
+3. Non-Local Means denoising
+4. CLAHE enhancement
+
+ImageNet normalization is intentionally not stored in the images.
+It will be applied during the PyTorch training pipeline.
+
+## Experimental Splits
+
+Five repeated stratified splits are provided.
+
+Each split contains approximately:
+
+- 50% training
+- 20% validation
+- 30% testing
+
+Seeds:
+
+- 42
+- 52
+- 62
+- 72
+- 82
+
+The same split files should be used when comparing different
+models to ensure a fair experimental comparison.
+
+## Repository Structure
+
+images/
+splits/
+metadata/
+README.md
+
+## Intended Use
+
+This processed dataset is intended for research experiments
+involving retinal OCT image classification and comparison of
+deep learning models, including Swin Transformer and custom
+Swin Transformer architectures.
+
+The provided split files should be used consistently across
+models to maintain a fair comparison.
+
+## Image Preprocessing
+
+The saved images have already undergone:
+
+- Aspect-ratio-preserving resize
+- Center crop
+- Non-Local Means denoising
+- CLAHE enhancement
+
+ImageNet normalization is NOT included in the saved JPEG files.
+
+For model training, ImageNet normalization should be applied
+after loading the image and converting it to a tensor.
+
+## Reproducibility
+
+The repository includes five stratified train/validation/test
+splits and the experiment configuration used during dataset
+preparation.
+
+These files are provided so that the same experimental partitions
+can be reused across different models.
+
+## Dataset Integrity
+
+- Original images checked: 572
+- Corrupted original images: 0
+- Original duplicate files: 0
+- Processed images: 572
+- Missing processed images: 0
+- Processed duplicate files: 0
+- Processed image size: 224 x 224
+- Processed image mode: RGB
+
+## License and Citation
+
+This repository contains processed research data derived from OCTID.
+
+Please consult the original OCTID dataset/source for its licensing,
+citation requirements, and redistribution conditions before using
+or publishing this dataset.