Update README.md

README.md

@@ -47,6 +47,8 @@ Here below find all the dataset's versions and descriptions.
 
   *Pre-processing*: The image augmentation techniques used in this process include various forms of Gaussian noise, implemented through IAAAdditiveGaussianNoise with a probability of 20% and mean zero, and standard deviation of 0.01 * 255 or 0.05 * 255. The GaussNoise technique was also employed with a mean of zero and default variance of (10.0, 50.0). General blurring was implemented through MotionBlur (p=.2), MedianBlur (blur_limit=3, p=0.1), Blur(blur_limit=3, p=0.1), and ShiftScaleRotate(shift_limit=0.0625, scale_limit=0.2, rotate_limit=45, p=0.2). Distortion techniques included OpticalDistortion(p=0.3), GridDistortion(p=.1), IAAPiecewiseAffine(p=0.3), and IAAAffine(scale=(0.8, 1.2), translate_percent=0.1, rotate=15, shear=10, p=0.2). Finally, brightness adjustments were made using CLAHE(clip_limit=2), IAASharpen(), IAAEmboss(), RandomBrightnessContrast(), and HueSaturationValue(p=0.3).
 
+* **Creating Cloud-Cloudless Paired Dataset**: This dataset, derived from imagery in five Colombian municipalities, consists of 1640 images (820 pairs), where each of the 164 images per municipality is paired with a previously identified optimal cloudless image. The Cloud2CloudlesDataset class organizes these pairs into a new folder (DATASET), with images renamed to indicate ground truth and cloud presence. The class, initialized with source and destination paths, includes tests for image count verification and folder existence confirmation.
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 ## Reading data
 
 The data can be read as (example):