Ximeng0831/NaviDrive-Reasoning

--- license: apache-2.0 task_categories: - image-text-to-text - text-generation language: - en tags: - nuscenes - driving-reasoning configs: - config_name: gemini data_files: - split: train path: data/gemini_train.jsonl - split: validation path: data/gemini_val.jsonl - config_name: qwen_8b data_files: - split: train path: data/qwen_8b_train.jsonl - split: validation path: data/qwen_8b_val.jsonl - config_name: qwen_32b data_files: - split: train path: data/qwen_32b_train.jsonl - split: validation path: data/qwen_32b_val.jsonl - config_name: qwen_8b_mini data_files: - split: train path: data/mini_qwen_8b_train.jsonl - split: validation path: data/mini_qwen_8b_val.jsonl --- # NaviDrive-Reasoning [](https://arxiv.org/abs/2603.07901) [](https://huggingface.co/Ximeng0831/NaviDrive-Qwen3-VL-2B-SFT) [](https://huggingface.co/datasets/Ximeng0831/NaviDrive-Reasoning) [](https://github.com/TAMU-CVRL/NaviDrive) This dataset contains reasoning, perception, and action explanations generated for the NuScenes dataset using multiple LLMs. ## Dataset Summary - **Gemini**: Reasoning generated by the [Gemini-2.5-Flash model]((https://docs.cloud.google.com/vertex-ai/generative-ai/docs/models/gemini/2-5-flash)). - **Qwen-8B**: Reasoning generated by the [Qwen-8B model]((https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct)). - **Qwen-32B**: Reasoning generated by the [Qwen-32B model]((https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct)). - **Mini**: A subset specifically for the nuScenes-mini dataset. > **Qwen-32B** is the primary dataset used for model training. ## Data Structure Each `.jsonl` file follows a consistent schema. Key fields include: | Field | Description | | :--- | :--- | | `token` | Unique identifier for the nuScenes sample. | | `command` | High-level driving intent (e.g., `<Keep_Straight>`, `<Turn_Right>`). | | `wp_future` | A sequence of (x, y, \theta) future waypoints for the ego-vehicle. | | `reasons` | A list containing the **Perception**, **Action**, and **Reasoning** breakdown. | | `image_paths` | Relative paths to the corresponding nuScenes camera sensors. | > **Note** > Images are not included in the dataset—only relative image paths are provided. > To use image inputs, please download the [nuScenes Dataset](https://www.nuscenes.org/nuscenes#download) and specify the dataset root path to properly load the images. ## How to Load ```python from datasets import load_dataset # Example: Load the NaviDrive-Reasoning Dataset train_dataset = load_dataset("Ximeng0831/NaviDrive-Reasoning", "qwen_32b", split="train") val_dataset = load_dataset("Ximeng0831/NaviDrive-Reasoning", "qwen_32b", split="validation") # Access the first sample print(train_dataset[0]["reasons"]) ``` ## Acknowledgements This dataset is based on the [nuScenes dataset](https://www.nuscenes.org/).许可证：Apache-2.0 任务类别： - 图像-文本转文本 - 文本生成 语言： - 英语 标签： - nuScenes - 驾驶推理 配置项： - 配置名称：gemini 数据文件： - 拆分：训练集 路径：data/gemini_train.jsonl - 拆分：验证集 路径：data/gemini_val.jsonl - 配置名称：qwen_8b 数据文件： - 拆分：训练集 路径：data/qwen_8b_train.jsonl - 拆分：验证集 路径：data/qwen_8b_val.jsonl - 配置名称：qwen_32b 数据文件： - 拆分：训练集 路径：data/qwen_32b_train.jsonl - 拆分：验证集 路径：data/qwen_32b_val.jsonl - 配置名称：qwen_8b_mini 数据文件： - 拆分：训练集 路径：data/mini_qwen_8b_train.jsonl - 拆分：验证集 路径：data/mini_qwen_8b_val.jsonl # NaviDrive-Reasoning（导航驾驶推理） [](https://arxiv.org/abs/2603.07901) [](https://huggingface.co/Ximeng0831/NaviDrive-Qwen3-VL-2B-SFT) [](https://huggingface.co/datasets/Ximeng0831/NaviDrive-Reasoning) [](https://github.com/TAMU-CVRL/NaviDrive) 本数据集包含基于nuScenes数据集，由多款大语言模型生成的推理、感知与行为解释内容。 ## 数据集概览 - **Gemini**：由Gemini-2.5-Flash模型生成的推理内容。 - **Qwen-8B**：由Qwen-8B模型生成的推理内容。 - **Qwen-32B**：由Qwen-32B模型生成的推理内容。 - **Mini**：专为nuScenes-mini数据集打造的子集。 > **Qwen-32B** 是模型训练所用的主数据集。 ## 数据结构 每个`.jsonl`文件均遵循统一的格式规范，关键字段如下： | 字段名 | 说明 | | :--- | :--- | | `token` | nuScenes样本的唯一标识符。 | | `command` | 高阶驾驶意图（例如`<Keep_Straight>`、`<Turn_Right>`）。 | | `wp_future` | 自车的未来航点序列，格式为(x, y, θ)。 | | `reasons` | 包含**感知**、**行为**与**推理**拆解内容的列表。 | | `image_paths` | 对应nuScenes相机传感器图像的相对路径。 | > **注意** > 本数据集未包含原始图像，仅提供图像相对路径。若需使用图像作为输入，请下载[nuScenes数据集](https://www.nuscenes.org/nuscenes#download)并指定数据集根目录以正确加载图像。 ## 加载方式 python from datasets import load_dataset # 示例：加载NaviDrive-Reasoning数据集 train_dataset = load_dataset("Ximeng0831/NaviDrive-Reasoning", "qwen_32b", split="train") val_dataset = load_dataset("Ximeng0831/NaviDrive-Reasoning", "qwen_32b", split="validation") # 访问第一条样本 print(train_dataset[0]["reasons"]) ## 致谢 本数据集基于[nuScenes数据集](https://www.nuscenes.org/)构建。