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license: cc-by-nc-sa-4.0 |
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# OpenDV-YouTube |
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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>. |
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## Usage |
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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>. |
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You can use the following code to load in annotations respectively. |
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```python |
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import json |
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# for train |
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full_annos = [] |
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for split_id in range(10): |
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split = json.load(open("10hz_YouTube_train_split{}.json".format(str(split_id)), "r")) |
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full_annos.extend(split) |
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# for val |
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val_annos = json.load(open("10hz_YouTube_val.json", "r")) |
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``` |
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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. |
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``` |
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{ |
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"cmd": <int> -- command, i.e. the command of the ego vehicle in the video clip. |
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"blip": <str> -- context, i.e. the BLIP description of the center frame in the video clip. |
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"folder": <str> -- the relative path from the processed OpenDV-YouTube dataset root to the image folder of the video clip. |
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"first_frame": <str> -- the filename of the first frame in the clip. Note that this file is included in the video clip. |
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"last_frame": <str> -- the filename of the last frame in the clip. Note that this file is included in the video clip. |
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} |
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``` |
