| --- |
| license: mit |
| pretty_name: DrivingStereo |
| task_categories: |
| - depth-estimation |
| tags: |
| - stereo-matching |
| - autonomous-driving |
| - computer-vision |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| # DrivingStereo |
|
|
| This is a mirror of the original DrivingStereo download files, preserving the |
| original ZIP archives and camera calibration text files without recompression. |
| The original dataset was introduced at CVPR 2019 by Guorun Yang, Xiao Song, |
| Chaoqing Huang, Zhidong Deng, Jianping Shi, and Bolei Zhou. |
|
|
| - Official website: https://drivingstereo-dataset.github.io/ |
| - Paper: https://openaccess.thecvf.com/content_CVPR_2019/html/Yang_DrivingStereo_A_Large-Scale_Dataset_for_Stereo_Matching_in_Autonomous_Driving_CVPR_2019_paper.html |
| - Original license: https://github.com/drivingstereo-dataset/drivingstereo-dataset.github.io/blob/master/LICENSE |
| |
| ## Contents |
| |
| | Directory | Contents | |
| | --- | --- | |
| | `train/` | All 38 training sequences: half-resolution left/right images, disparity maps, and depth maps | |
| | `test/half-size/` | All four testing sequences at half resolution, with all four modalities | |
| | `test/full-size/` | All four testing sequences at full resolution, with all four modalities | |
| | `weather/` | Sunny, cloudy, foggy, and rainy subsets, with both released resolutions and all four modalities | |
| | `calibration/` | Training and testing camera calibration, for both resolutions | |
| |
| The inventory contains **300 source files** totaling |
| **202,346,258,264 bytes** (202.346 GB). |
| The early demonstration package is excluded; the released training, testing, |
| weather, and calibration directories are mirrored in full. |
| |
| ## Transfer status |
| |
| **Transfer in progress**. As of 2026-10-24T13:57:51+00:00, **224/300 files** |
| (96.840/202.346 GB) are verified on the Hub. |
| Status is refreshed after each batch. `transfer_status.json` contains the machine-readable status. |
|
|
| `source_manifest.json` records original Google Drive file IDs and URLs, official |
| Baidu share links, original paths, expected byte sizes, mirror paths, and the |
| approximately 50 GB batch plan. Files may be retrieved from either official |
| mirror; a Baidu file must match the original filename and exact byte size. |
| `SHA256SUMS` contains hashes for successfully uploaded files. Each ZIP is checked |
| for CRC errors before upload; uploaded file sizes and content hashes are checked |
| against Hub metadata before a local batch is removed. |
|
|
| ## Download |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download( |
| repo_id="kronecker0122/DrivingStereo", |
| repo_type="dataset", |
| local_dir="DrivingStereo", |
| allow_patterns=["train/left-image/*", "train/right-image/*", "train/disparity-map/*", "calibration/train/*"], |
| ) |
| ``` |
|
|
| Download all files by omitting `allow_patterns`. ZIP archives must be extracted |
| before using the original images and maps. Follow the official website for |
| calibration details and the different disparity encodings at each resolution. |
|
|
| ## License and citation |
|
|
| The official website releases the dataset under the MIT license. The original |
| copyright notice and license are included in `LICENSE`. Please cite the authors' |
| publication when using the dataset: |
|
|
| ```bibtex |
| @inproceedings{yang2019drivingstereo, |
| title={DrivingStereo: A Large-Scale Dataset for Stereo Matching in Autonomous Driving Scenarios}, |
| author={Yang, Guorun and Song, Xiao and Huang, Chaoqin and Deng, Zhidong and Shi, Jianping and Zhou, Bolei}, |
| booktitle={IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, |
| year={2019} |
| } |
| ``` |
|
|
