Duplicate from bnsapa/road-detection

Co-authored-by: Bal Narendra Sapa <bnsapa@users.noreply.huggingface.co>

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+*.pcm filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: gpl-3.0
+size_categories:
+- n<1K
+task_categories:
+- image-to-image
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+  - split: test
+    path: data/test-*
+  - split: validation
+    path: data/validation-*
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: segment
+    dtype: image
+  - name: lane
+    dtype: image
+  splits:
+  - name: train
+    num_bytes: 72551321.0
+    num_examples: 160
+  - name: test
+    num_bytes: 8756556.0
+    num_examples: 20
+  - name: validation
+    num_bytes: 9100529.0
+    num_examples: 20
+  download_size: 90167475
+  dataset_size: 90408406.0
+---
+# About
+
+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")
+```

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