Create README.md

README.md

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+# W-CODA2024 Track 2 Dataset
+
+## Dataset Description
+This dataset contains auxiliary data files for the W-CODA (Multimodal Perception and Comprehension of Corner Cases in Autonomous Driving) Track 2 workshop at ECCV 2024. The files provide metadata about the nuScenes validation set for evaluating video generation and detection/segmentation results.
+
+## Data Files
+
+1. `nuscenes_infos_temporal_val_3keyframes.pkl`
+   - Contains information about key frames from 150 scenes in the nuScenes validation set. 
+   - Each scene has 3 key frames extracted from the first 16 frames.
+   - Used for evaluating object detection and segmentation performance on the key frames.
+   - Format: Python pickle file, load with `mmcv.load()`.
+
+2. `nuscenes_infos_temporal_val_12hz.pkl` 
+   - Contains metadata for 150 scenes in the nuScenes validation set.
+   - Provides the first 16 frames (at 12Hz) for each scene.
+   - Paths to real video frames, used to calculate Fréchet Video Distance (FVD) between generated and real videos.
+   - Format: Python pickle file, load with `mmcv.load()`.
+
+```python
+data = mmcv.load("./data/nuscenes/nuscenes_infos_temporal_val_3keyframes.pkl")
+print(data.keys())
+# dict_keys(['infos', 'metadata'])
+```
+## Dataset Structure
+The loaded pickle files contain a list of dictionaries, one per frame, with 'scene_token', 'frame_idx', 'gt_boxes', 'gt_names', 'cams', etc. Their meanings are consistent with the original nus annotations.
+
+## Download
+Download the files from Hugging Face:
+- [nuscenes_infos_temporal_val_3keyframes.pkl](https://huggingface.co/datasets/pengxiang/W-CODA2024-Track2) 
+- [nuscenes_infos_temporal_val_12hz.pkl](https://huggingface.co/datasets/pengxiang/W-CODA2024-Track2)