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Fix the paste back speed

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This commit is contained in:
henryruhs 2023-10-21 23:03:45 +02:00
parent d81371faea
commit 63bab0f84c
1 changed files with 14 additions and 14 deletions
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28
facefusion/face_helper.py
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@ -2,6 +2,7 @@ from typing import Tuple, Dict, Any
import cv2
import numpy
import numpy as np
from cv2.typing import Size
from facefusion.typing import Frame, Kps, Matrix, Template
@ -33,21 +34,20 @@ def warp_face(temp_frame : Frame, kps : Kps, template : Template, size : Size) -
return crop_frame, affine_matrix
def paste_back(temp_frame : Frame, crop_frame : Frame, affine_matrix : Matrix) -> Frame:
def paste_back(temp_frame: Frame, crop_frame: Frame, affine_matrix: Matrix) -> Frame:
inverse_affine_matrix = cv2.invertAffineTransform(affine_matrix)
temp_frame_height, temp_frame_width = temp_frame.shape[0:2]
crop_frame_height, crop_frame_width = crop_frame.shape[0:2]
inverse_crop_frame = cv2.warpAffine(crop_frame, inverse_affine_matrix, (temp_frame_width, temp_frame_height))
inverse_mask = numpy.ones((crop_frame_height, crop_frame_width, 3))
inverse_mask_frame = cv2.warpAffine(inverse_mask, inverse_affine_matrix, (temp_frame_width, temp_frame_height))
inverse_mask_frame = cv2.erode(inverse_mask_frame, numpy.ones((2, 2)))
inverse_mask_border = inverse_mask_frame * inverse_crop_frame
inverse_mask_area = numpy.sum(inverse_mask_frame) // 3
inverse_mask_edge = int(inverse_mask_area ** 0.5) // 20
inverse_mask_radius = inverse_mask_edge * 2
inverse_mask_center = cv2.erode(inverse_mask_frame, numpy.ones((inverse_mask_radius, inverse_mask_radius)))
inverse_mask_blur_size = inverse_mask_edge * 2 + 1
inverse_mask_blur_area = cv2.GaussianBlur(inverse_mask_center, (inverse_mask_blur_size, inverse_mask_blur_size), 0)
temp_frame = inverse_mask_blur_area * inverse_mask_border + (1 - inverse_mask_blur_area) * temp_frame
temp_frame = numpy.clip(temp_frame, 0, 255).astype(numpy.uint8)
inverse_mask = numpy.full((crop_frame_height, crop_frame_width), 255).astype(numpy.float32)
inverse_crop_frame = cv2.warpAffine(inverse_mask, inverse_affine_matrix, (temp_frame_width, temp_frame_height))
inverse_temp_frame = cv2.warpAffine(crop_frame, inverse_affine_matrix, (temp_frame_width, temp_frame_height))
inverse_mask_size = int(numpy.sqrt(numpy.sum(inverse_crop_frame == 255)))
kernel_size = max(inverse_mask_size // 10, 10)
inverse_crop_frame = cv2.erode(inverse_crop_frame, numpy.ones((kernel_size, kernel_size)))
kernel_size = max(inverse_mask_size // 20, 5)
blur_size = kernel_size * 2 + 1
inverse_blur_frame = cv2.GaussianBlur(inverse_crop_frame, (blur_size , blur_size), 0) / 255
inverse_blur_frame = numpy.reshape(inverse_blur_frame, [ temp_frame_height, temp_frame_width, 1 ])
temp_frame = inverse_blur_frame * inverse_temp_frame + (1 - inverse_blur_frame) * temp_frame
temp_frame = temp_frame.astype(numpy.uint8)
return temp_frame