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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):
# MODEL CONFIG, NOT EXPOERTED PARAMS
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 of F
checkpoint_M: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/motion_extractor.pth') # path to checkpoint pf M
checkpoint_G: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/spade_generator.pth') # path to checkpoint of G
checkpoint_W: str = make_abs_path('../../pretrained_weights/liveportrait/base_models/warping_module.pth') # path to checkpoint of W
checkpoint_S: str = make_abs_path('../../pretrained_weights/liveportrait/retargeting_models/stitching_retargeting_module.pth') # path to checkpoint to S and R_eyes, R_lip
# EXPOERTED PARAMS
flag_use_half_precision: bool = True
flag_crop_driving_video: bool = False
flag_crop_source_video: bool = False
device_id: int = 0
flag_lip_zero: bool = True
flag_eye_retargeting: bool = False
flag_lip_retargeting: bool = False
flag_stitching: bool = True
flag_relative_motion: bool = True
flag_pasteback: bool = True
flag_do_crop: bool = True
flag_do_rot: bool = True
flag_force_cpu: bool = False
# NOT EXPOERTED PARAMS
lip_zero_threshold: float = 0.03 # threshold for flag_lip_zero
anchor_frame: int = 0 # TO IMPLEMENT
input_shape: Tuple[int, int] = (256, 256) # input shape
output_format: Literal['mp4', 'gif'] = 'mp4' # output video format
crf: int = 15 # crf for output video
output_fps: int = 25 # default output fps
mask_crop: ndarray = cv2.imread(make_abs_path('../utils/resources/mask_template.png'), cv2.IMREAD_COLOR)
size_gif: int = 256 # default gif size, TO IMPLEMENT
source_max_dim: int = 1280 # the max dim of height and width of source image
source_division: int = 2 # make sure the height and width of source image can be divided by this number
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