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Add processed OCTID dataset with 5 experimental splits (part 3)
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{
"dataset_name": "OCTID",
"total_images": 572,
"num_classes": 5,
"classes": {
"Normal": 206,
"AMD": 55,
"CSR": 102,
"DR": 107,
"MH": 102
},
"image_format": "JPEG",
"image_size": "224x224",
"image_mode": "RGB",
"preprocessing": [
"Aspect-ratio-preserving resize",
"Center crop",
"Non-Local Means denoising",
"CLAHE"
],
"normalization": "ImageNet normalization applied later in the PyTorch training pipeline",
"splits": {
"repetitions": 5,
"train": 0.5,
"validation": 0.2,
"test": 0.3
},
"split_seeds": [
42,
52,
62,
72,
82
]
}