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 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+drivelm_carla_keyframes.txt filter=lfs diff=lfs merge=lfs -text
+v1_1_train_nus.json filter=lfs diff=lfs merge=lfs -text

README.md

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----
-license: mit
----
+---
+license: cc-by-nc-sa-4.0
+viewer: false
+---
+# **DriveLM:** Driving with **G**raph **V**isual **Q**uestion **A**nswering.
+
+We facilitate `Perception, Prediction, Planning, Behavior, Motion` tasks with human-written reasoning logic as a connection. We propose the task of GVQA to connect the QA pairs in a graph-style structure. To support this novel task, we provide the DriveLM-Data. 
+
+DriveLM-Data comprises two distinct components: DriveLM-nuScenes and DriveLM-CARLA. In the case of DriveLM-nuScenes, we construct our dataset based on the prevailing nuScenes dataset. As for DriveLM-CARLA, we collect data from the CARLA simulator.
+
+## Prepare DriveLM-nuScenes Dataset
+
+Our DriveLM-nuScenes contains a collection of questions and answers. The dataset is named `v1_0_train_nus.json`. We offer a subset of image data that includes all the images used in our DriveLM. You can also download the full nuScenes dataset [HERE](https://www.nuscenes.org/download). 
+
+## Usage
+
+1. Download nuScenes subset image data (or full nuScenes dataset) and `v1_0_train_nus.json`.
+
+2. Organize the data structure as follows:
+
+```
+DriveLM
+├── data/
+│   ├── QA_dataset_nus/
+│   │   ├── v1_0_train_nus.json
+│   ├── nuscenes/
+│   │   ├── samples/
+```
+
+## Prepare DriveLM-CARLA Dataset
+We provide a collection of questions and answers for DriveLM-CARLA. The dataset `drivelm_carla_vqas.zip` contains question-answer pairs for pre-determined keyframes listed in `drivelm_carla_keyframes.txt` for each scenario. You can download the full dataset using the provided [script](https://github.com/OpenDriveLab/DriveLM/blob/DriveLM-CARLA/vqa_dataset/download_pdm_lite_carla_lb2.py). All scripts for extracting keyframes and generating the question-answer dataset are available on [GitHub](https://github.com/OpenDriveLab/DriveLM/blob/DriveLM-CARLA/vqa_dataset). Additionally, we also provide instructions how to built your own dataset.
+
+## License and Citation
+
+This language dataset is licensed under [CC-BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). If you use this dataset, please cite our work: 
+
+
+```BibTeX
+@article{drivelm_paper2023,
+  title={DriveLM: Driving with Graph Visual Question Answering},
+  author={Sima, Chonghao and Renz, Katrin and Chitta, Kashyap and Chen, Li and Zhang, Hanxue and Xie, Chengen and Luo, Ping and Geiger, Andreas and Li, Hongyang},
+  journal={arXiv preprint arXiv:2312.14150},
+  year={2023}
+}
+```
+
+```BibTeX
+@misc{drivelm_repo2023,
+  title={DriveLM: Driving with Graph Visual Question Answering},
+  author={DriveLM contributors},
+  howpublished={\url{https://github.com/OpenDriveLab/DriveLM}},
+  year={2023}
+}
+```
+
+Paper dataset for ECCV 2024 [DriveLM: Driving with Graph Visual Question Answering](https://huggingface.co/papers/2312.14150)
+
+For more information and updates, please visit our [GitHub repository](https://github.com/OpenDriveLab/DriveLM).
+

drivelm_carla_keyframes.txt

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drivelm_nus_imgs_train.zip

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drivelm_nus_imgs_val.zip

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gitattributes

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+drivelm_nus_imgs.zip filter=lfs diff=lfs merge=lfs -text
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+drivelm_carla_vqas.zip filter=lfs diff=lfs merge=lfs -text
+keyframes_all_towns.txt filter=lfs diff=lfs merge=lfs -text
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