Update README.md

README.md

@@ -26,8 +26,7 @@ A large-scale instance segmentation dataset of nearly 64k annotated spacecraft i
 The dataset contains over 63,917 annotated images with instance masks for varied spacecraft. It's structured for YOLO and segmentation applications, and chunked to stay within Hugging Face's per-folder file limits.
 
 
-## How to Use/Download
-### Directory Structure Note
+## Directory Structure Note
 
 Due to Hugging Face Hub's per-directory file limit (10,000 files), this dataset is chunked: each logical split (like `train/labels/`) is subdivided into folders (`000/`, `001/`, ...) containing no more than 5,000 files each.
 
@@ -55,8 +54,35 @@ If you're using models/tools like **YOLO** or others that expect a **flat direct
               └── imag_99.png
 
 ```
-      
 
+## How to Load
+
+You can stream the SWiM-SpacecraftWithMasks dataset directly using the HuggingFace datasets library without downloading it entirely. This is particularly useful when working with limited local storage. 
+
+Use the following code to load and iterate over the dataset efficiently:
+
+```
+
+from datasets import load_dataset
+
+dataset = load_dataset(
+    "JeffreyJsam/SWiM-SpacecraftWithMasks",
+    streaming=True
+)
+
+```
+
+Note: The directory/folder structure here obtained from HuggingFace's load_dataset API includes chunks(eg, 000, 001, etc). Hence, it does not support YOLO training. For YOLO training or CIFAR-10 based directory structure, kindly use utils/download_swim.py script.
+
+## How to Download
+
+For local use, if you'd like to either sample a small portion or download the entire dataset to your filesystem, we provide two utility scripts under the utils/ folder:
+
+ - sample_swim.py for quick sampling from a single chunk
+ - download_swim.py is used to download the full dataset, optionally flattening the directory structure.
+
+These scripts let you work offline or run faster experiments by controlling what and how much data you fetch. Furthermore, the download_swim.py helps download the data in a flattened YOLO/CIFAR-10 supported folder structure.
+      
 ### Utility Scripts
 
 The following scripts help you download this dataset. Due to the large nature of the data and the custom directory structure, it is recommended to use the following scripts to either sample or to download the entire dataset. Note, the scripts are in the utils subdirectory.
@@ -105,7 +131,7 @@ Features:
 - Optionally flattens the directory structure by removing the deepest chunk level
 - Saves each .png image with its corresponding .txt label
 
-You can use this script to download the complete dataset for model training or offline access.
+This script can download the complete dataset for model training or offline access.
 
 Usage:
     # Download all chunks (flattened/ YOLO format)