---
license: cc-by-nc-sa-4.0
---

# OpenDV-YouTube

This is the dataset repository of `OpenDV-YouTube` language annotations, including `context` and `command`. For more details, please refer to <a href="https://arxiv.org/abs/2403.09630" target="_blank">GenAD</a> project and <a href="https://github.com/OpenDriveLab/DriveAGI#opendv-youtube" target="_blank">OpenDV-YouTube</a>.

## Usage

To use the annotations, you need to first download and prepare the data as instructed in <a href="https://github.com/OpenDriveLab/DriveAGI/tree/main/opendv" target="_blank">OpenDV-YouTube</a>.

You can use the following code to load in annotations respectively.

```python
import json

# for train
full_annos = []
for split_id in range(10):
  split = json.load(open("10hz_YouTube_train_split{}.json".format(str(split_id)), "r"))
  full_annos.extend(split)

# for val
val_annos = json.load(open("10hz_YouTube_val.json", "r"))
```

Annotations will be loaded in `full_annos` as a list where each element contains annotations for one video clip. All elements in the list are dictionaries of the following structure.

```
{
  "cmd": <int> -- command, i.e. the command of the ego vehicle in the video clip.
  "blip": <str> -- context, i.e. the BLIP description of the center frame in the video clip.
  "folder": <str> -- the relative path from the processed OpenDV-YouTube dataset root to the image folder of the video clip.
  "first_frame": <str> -- the filename of the first frame in the clip. Note that this file is included in the video clip.
  "last_frame": <str> -- the filename of the last frame in the clip. Note that this file is included in the video clip.
}
```