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Running
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Zero
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# coding: utf-8
"""
config dataclass used for inference
"""
import os.path as osp
import cv2
from numpy import ndarray
from dataclasses import dataclass
from typing import Literal, Tuple
from .base_config import PrintableConfig, make_abs_path
@dataclass(repr=False) # use repr from PrintableConfig
class InferenceConfig(PrintableConfig):
models_config: str = make_abs_path('./models.yaml') # portrait animation config
checkpoint_F: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/appearance_feature_extractor.pth') # path to checkpoint
checkpoint_M: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/motion_extractor.pth') # path to checkpoint
checkpoint_G: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/spade_generator.pth') # path to checkpoint
checkpoint_W: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/warping_module.pth') # path to checkpoint
checkpoint_S: str = make_abs_path('../../pretrained_weights/liveportrait/retargeting_models/stitching_retargeting_module.pth') # path to checkpoint
flag_use_half_precision: bool = True # whether to use half precision
flag_lip_zero: bool = True # whether let the lip to close state before animation, only take effect when flag_eye_retargeting and flag_lip_retargeting is False
lip_zero_threshold: float = 0.03
flag_eye_retargeting: bool = False
flag_lip_retargeting: bool = False
flag_stitching: bool = True # we recommend setting it to True!
flag_relative: bool = True # whether to use relative motion
anchor_frame: int = 0 # set this value if find_best_frame is True
input_shape: Tuple[int, int] = (256, 256) # input shape
output_format: Literal['mp4', 'gif'] = 'mp4' # output video format
output_fps: int = 30 # fps for output video
crf: int = 15 # crf for output video
flag_write_result: bool = True # whether to write output video
flag_pasteback: bool = True # whether to paste-back/stitch the animated face cropping from the face-cropping space to the original image space
mask_crop: ndarray = cv2.imread(make_abs_path('../utils/resources/mask_template.png'), cv2.IMREAD_COLOR)
flag_write_gif: bool = False
size_gif: int = 256
ref_max_shape: int = 1280
ref_shape_n: int = 2
device_id: int = 0
flag_do_crop: bool = False # whether to crop the source portrait to the face-cropping space
flag_do_rot: bool = True # whether to conduct the rotation when flag_do_crop is True
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