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--- |
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pretty_name: EuroRoads |
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license: cc-by-4.0 |
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task_categories: |
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- image-classification |
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- image-segmentation |
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size_categories: |
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- 10K<n<100K |
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language: |
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- en |
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tags: |
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- roads |
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- europe |
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- driving |
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- netherlands |
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- belgium |
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- germany |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: dataset/EuroRoads-13.7K.zip |
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--- |
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# 🛣️ EuroRoads, a free to use European road dataset |
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A high-resolution collection of **13.7 thousand road scene images** captured across the **Netherlands (Limburg)**, **Germany**, and **Belgium**. |
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The dataset focuses on realistic driving environments ranging from highways to small rural paths — designed for use in computer vision tasks such as segmentation, detection, or autonomous driving simulation. |
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*Three images side by side, below them an extreme 10x crop (for full res see assets folder)* |
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## 📦 Dataset Summary |
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| Property | Description | |
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| -------------------- | ---------------------------------------------------- | |
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| **Total Images** | 13,706 | |
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| **Resolution** | 3072 × 3072 | |
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| **Capture Device** | Xiaomi 14 Ultra / 15 Ultra (soon) | |
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| **Frame Interval** | 1 second | |
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| **Filtering** | Long traffic pauses removed | |
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| **Geographic Focus** | Mainly Netherlands (Limburg), also Germany & Belgium | |
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| **License** | CC-BY | |
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| **Status** | Work in progress | |
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| **Camera Mode** | Auto (may cause inconsistent motion blur) | |
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| **Camera Style** | Mainly Leica Authentic | |
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--- |
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## 🗺️ Description |
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This dataset provides **sharp and detailed** images captured in various European environments and weather conditions. |
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It covers a wide range of road types: |
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* 🚗 **Highways and intercity roads** |
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* 🚙 **Regular city and suburban roads** |
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* 🚜 **Narrow paths and village streets** |
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* 🌳 **Paved roads through nature** |
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All images were captured at **1-second intervals**, with **long idle pauses removed** (red lights). The result is a mostly unfiltered, time-consistent dataset. |
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All images have kept their original file names and metadata, although location information is excluded. |
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--- |
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## 🧭 Geographic Context |
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* **Primary Region:** Limburg, Netherlands |
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* **Additional Regions:** Adjacent areas in **Germany** and **Belgium** |
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* **Environment Mix:** Urban → rural → nature-paved roads |
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--- |
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## 📷 Image Characteristics |
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* Captured using **high-end mobile sensors** (Xiaomi 14/15 Ultra) |
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* **Auto mode** exposure and focus |
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* **1:1 aspect ratio** optimized for dataset uniformity |
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* Possible **inconsistencies in motion blur or lighting** due to automatic settings |
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* **No filtering or labeling** beyond removal of long idle periods |
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--- |
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## 🪪 License |
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**Creative Commons Attribution (CC BY 4.0)** |
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You are free to share and adapt the data, provided appropriate credit is given. |
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--- |
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## 🚧 Work in Progress |
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This dataset is **actively being expanded and refined**. |
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Future releases *may* include: |
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* Filtered subsets (e.g., motion blur score, weather condition, time of day) |
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* Semantic annotations or segmentation masks |
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--- |
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## 📬 Citation |
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If you use this dataset in your work, please cite it as: |
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``` |
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@dataset{road_scenes_limburg_de_be_2025, |
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title = {EuroRoads (Limburg–DE–BE) Dataset}, |
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author = {Randy Hübner}, |
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year = {2025}, |
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license = {CC-BY-4.0}, |
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url = {https://huggingface.co/datasets/Pikachu/EuroRoads} |
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} |
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``` |
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--- |
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license: cc-by-4.0 |
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--- |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: dataset/EuroRoads-13.7K.zip |
