Update README.md

README.md

@@ -34,6 +34,26 @@ dataset_info:
   download_size: 90167475
   dataset_size: 90408406.0
 ---
-# Dataset Card for "road-detection"
+# About
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+This dataset is for detecting the drivable area and lane lines on the roads. Images are generated using stable diffusion model and images are annotated using labelme annotator.
+
+For more info on the project we worked see this git [repo](https://github.com/balnarendrasapa/road-detection)
+
+# Dataset
+
+The dataset is structured into three distinct partitions: Train, Test, and Validation. The Train split comprises 80% of the dataset, containing both the input images and their corresponding labels. Meanwhile, the Test and Validation splits each contain 10% of the data, with a similar structure, consisting of image data and label information. Within each of these splits, there are three folders:
+
+- Images: This folder contains the original images, serving as the raw input data for the task at hand.
+
+- Segments: Here, you can access the labels specifically designed for Drivable Area Segmentation, crucial for understanding road structure and drivable areas.
+
+- Lane: This folder contains labels dedicated to Lane Detection, assisting in identifying and marking lanes on the road.
+
+# Downloading the dataset
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("bnsapa/road-detection")
+```