Update README.md

README.md

@@ -46,6 +46,25 @@ 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).
 
+## Reading data
+
+The data can be read as (example): 
+
+```
+from datasets import load_dataset
+
+dataset = load_dataset("MITCriticalData/Unlabeled_top_10_cities_forward_backward_alg")
+
+```
+
+Alternatively, for ```datasets<1.11.0``` the lecture of `.tiff` and  `.json` files is not compatible. In such case we recommend to download the data  as:
+
+``` 
+wget path_to_data/images.zip unzip images.zip
+
+wget path_to_data/annotations.zip unzip annotations.zip
+```
+
 ## Sponsors
 
 *Project supported by ESA Network of Resources Initiative.