Converts the model to TFLite and exports as a model bundle file.
Saves a model bundle file and metadata json file to hparams.export_dir. The
resulting model bundle file will contain necessary models for face
detection, face landmarks detection, and customized face stylization. Only
the model bundle file is needed for the downstream face stylization task.
The metadata.json file is saved only to interpret the contents of the model
bundle file. The face detection model and face landmarks detection model are
from https://storage.googleapis.com/mediapipe-assets/face_landmarker_v2.task
and the customized face stylization model is trained in this library.
Args
model_name
Face stylizer model bundle file name. The full export path is
{self._hparams.export_dir}/{model_name}.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-05-07 UTC."],[],[]]