Update README.md

README.md

@@ -14,30 +14,11 @@ To generate synthetic data, we use the pipeline depicted below. We start with a
 
 ## Usage
 
-```python
-from datasets import load_dataset
+### Download this repository
+### Download the xView 1 dataset
+### Run the command below:
 
-# Define the dataset repo ID
-repo_id = "jquenum/GRES"
-
-# Download the dataset
-dataset = load_dataset(repo_id)
-
-# Show the dataset details
-print("Dataset loaded successfully!")
-print(dataset)
-
-# Access specific splits like train, validation, and test
-train_dataset = dataset['train']
-val_dataset = dataset['val']
-test_dataset = dataset['test']
-
-# Print the first example from the train split
-print("\nFirst example from the train dataset:", train_dataset[0])
-
-```
-
-run ```./extract_gres_images.sh /path/to/xview_train_images /path/to/xView_train.geojson .``` to get the gres image pool.
+```./extract_gres_images.sh /path/to/xview_train_images /path/to/xView_train.geojson .``` to get the gres image pool.
 
 
 ## LISAT GRES Dataset