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This commit is contained in:
harisreedhar 2024-11-05 21:29:43 +05:30
parent f0d6068307
commit fb62ee246c
1 changed files with 3 additions and 9 deletions
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12
facefusion/processors/modules/deep_swapper.py
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@ -3,7 +3,6 @@ from typing import List, Tuple
import cv2 import cv2
import numpy import numpy
from cv2.typing import Size
import facefusion.jobs.job_manager import facefusion.jobs.job_manager
import facefusion.jobs.job_store import facefusion.jobs.job_store
@ -44,6 +43,7 @@ MODEL_SET : ModelSet =\
} }
}, },
'template': 'arcface_128_v2', 'template': 'arcface_128_v2',
'size': (224, 224)
} }
} }
@ -64,12 +64,6 @@ def get_model_options() -> ModelOptions:
return MODEL_SET.get(deep_swapper_model) return MODEL_SET.get(deep_swapper_model)
def get_model_size() -> Size:
deep_swapper = get_inference_pool().get('deep_swapper')
model_size = deep_swapper.get_outputs()[-1].shape[1:3]
return model_size
def register_args(program : ArgumentParser) -> None: def register_args(program : ArgumentParser) -> None:
group_processors = find_argument_group(program, 'processors') group_processors = find_argument_group(program, 'processors')
if group_processors: if group_processors:
@ -117,7 +111,7 @@ def post_process() -> None:
def swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame: def swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
model_template = get_model_options().get('template') model_template = get_model_options().get('template')
model_size = get_model_size() model_size = get_model_options().get('size')
crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmark_set.get('5/68'), model_template, model_size) crop_vision_frame, affine_matrix = warp_face_by_face_landmark_5(temp_vision_frame, target_face.landmark_set.get('5/68'), model_template, model_size)
crop_vision_frame_raw = crop_vision_frame.copy() crop_vision_frame_raw = crop_vision_frame.copy()
box_mask = create_static_box_mask(crop_vision_frame.shape[:2][::-1], state_manager.get_item('face_mask_blur'), state_manager.get_item('face_mask_padding')) box_mask = create_static_box_mask(crop_vision_frame.shape[:2][::-1], state_manager.get_item('face_mask_blur'), state_manager.get_item('face_mask_padding'))
@ -171,7 +165,7 @@ def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
def prepare_crop_mask(crop_source_mask : Mask, crop_target_mask : Mask) -> Mask: def prepare_crop_mask(crop_source_mask : Mask, crop_target_mask : Mask) -> Mask:
model_size = get_model_size() model_size = get_model_options().get('size')
crop_mask = numpy.maximum.reduce([ crop_source_mask, crop_target_mask ]) crop_mask = numpy.maximum.reduce([ crop_source_mask, crop_target_mask ])
crop_mask = crop_mask.reshape(model_size).clip(0, 1) crop_mask = crop_mask.reshape(model_size).clip(0, 1)
crop_mask = cv2.erode(crop_mask, numpy.ones((5, 5), numpy.uint8), iterations = 1) crop_mask = cv2.erode(crop_mask, numpy.ones((5, 5), numpy.uint8), iterations = 1)