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remove model size requirement

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harisreedhar 2024-11-05 17:03:27 +05:30 committed by henryruhs
parent 9f0a6b747f
commit 82e2677649
1 changed files with 10 additions and 4 deletions
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14
facefusion/processors/modules/deep_swapper.py
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@ -3,6 +3,7 @@ from typing import List, Tuple
import cv2
import numpy
from cv2.typing import Size
import facefusion.jobs.job_manager
import facefusion.jobs.job_store
@ -43,7 +44,6 @@ MODEL_SET : ModelSet =\
}
},
'template': 'arcface_128_v2',
'size': (224, 224)
}
}
@ -64,6 +64,12 @@ def get_model_options() -> ModelOptions:
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:
group_processors = find_argument_group(program, 'processors')
if group_processors:
@ -111,7 +117,7 @@ def post_process() -> None:
def swap_face(target_face : Face, temp_vision_frame : VisionFrame) -> VisionFrame:
model_template = get_model_options().get('template')
model_size = get_model_options().get('size')
model_size = get_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()
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'))
@ -155,7 +161,7 @@ def forward(crop_vision_frame : VisionFrame) -> Tuple[VisionFrame, Mask, Mask]:
def prepare_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
crop_vision_frame = cv2.addWeighted(crop_vision_frame, 1.5, cv2.GaussianBlur(crop_vision_frame, (0, 0), 2), -0.5, 0)
crop_vision_frame = cv2.addWeighted(crop_vision_frame, 1.75, cv2.GaussianBlur(crop_vision_frame, (0, 0), 2), -0.75, 0)
crop_vision_frame = crop_vision_frame / 255.0
crop_vision_frame = numpy.expand_dims(crop_vision_frame, axis = 0).astype(numpy.float32)
return crop_vision_frame
@ -168,7 +174,7 @@ def normalize_crop_frame(crop_vision_frame : VisionFrame) -> VisionFrame:
def feather_crop_mask(crop_source_mask : Mask) -> Mask:
model_size = get_model_options().get('size')
model_size = get_model_size()
crop_mask = crop_source_mask.reshape(model_size).clip(0, 1)
crop_mask = cv2.erode(crop_mask, numpy.ones((5, 5), numpy.uint8), iterations = 1)
crop_mask = cv2.GaussianBlur(crop_mask, (7, 7), 0)