This repository is for pix2pix style transfer between normal facial expression and ahegao.
The training set of aligned pairs is automatically created by mining ahegao videos from tiktok.
The python api client is used for download from tiktok.
Login identifiers must be reverse-engineered from tiktok, by capturing packets.
Specifically: device_id, iid, openudid.
If registered to tiktok without password, password needs to be set for successful registration via API.
Listing of videos by tags works when we have hashtag ID by method list_hashtag.
For textual hashtag, we can obtain its ID by searching hashtags using method search_hashtag.
Hashtag IDs are autoincrement, thus we can crawl all hashtags over ids.
The ahegao frame in video is detected by face emotion detector.
Around 5k of videos was uploaded to uloz.to and can be downloaded from these links as 6part zip that need to be unzipped at once.
- https://uloz.to/file/tMeGElZAP6R6/videos-zip-001
- https://uloz.to/file/YQiExzLOL1PF/videos-zip-002
- https://uloz.to/file/GfdjlmjdqQI6/videos-zip-003
- https://uloz.to/file/YfKNqQ2MePuz/videos-zip-004
- https://uloz.to/file/49M23rce92pE/videos-zip-005
- https://uloz.to/file/ZnJnefkIs38i/videos-zip-006
Hopefully more work will be added later.