| | --- |
| | 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 full OpenDV-YouTube-Train and OpenDV-YouTube-Val 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 current video clip |
| | "blip": <str> -- context, i.e. the BLIP description of the center frame in the current video clip |
| | "folder": <str> -- the relative path from the processed OpenDV-YouTube dataset root to the image folder of the video |
| | "first_frame": <str> -- the filename of the first frame in the clip. The corresponding file is included in the current video clip. |
| | "last_frame": <str> -- the filename of the last frame in the clip. The corresponding file is included in the current video clip. |
| | } |
| | ``` |
