| --- |
| license: mit |
| task_categories: |
| - image-feature-extraction |
| - video-classification |
| language: |
| - en |
| --- |
| |
| # Generating_Video_Data |
|
|
| ``` |
| Hanzhe Liang |
| modified: 23 May |
| ``` |
|
|
| 😊 This library contains some common data for training video generation models. This is a library of summary datasets, with thanks to the original authors for their contributions. Regardless of which data you need, the following steps: |
| ```bash |
| mkdir data |
| cd data |
| ``` |
| Next, go to my cloud database link and download the data you want into the folder```data/```. |
| Once you've downloaded the data you need, we've found preprocessing steps from its official implementation, which you can follow to process the data. |
| For memory requirements, we provide the files as single zip files, you need to extract the file named data_name.rar with the unzip command: ```unrar x data_name.rar``` |
| |
| ---- |
| |
| ### Something Something V2 |
| Please check the data path. |
| ```bash |
| cd somethingv2 |
| python extract_frames.py |
| python process_somethingv2.py |
| ``` |
| You can check data list ```somethingv2/*.txt``` |
| |
| ### Human3.6M |
| I provided two datasets, both processed and unprocessed. |
| |
| Unprocessed |
| ```bash |
| cd human36m/human36m_unprocessed |
| python build_clip_dataset.py |
| python make_list.py |
| ``` |
| You can check data list ```human36m/human36m_unprocessed/*.txt``` |
| |
| or you can directly check the processed data in ```human36m/human36m_processed``` |
| |
| ### YouTubeDriving |
| ```bash |
| cd youtubedriving |
| python make_list.py |
| ``` |
| You can check data list ```youtubedriving/*.txt``` |
