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refactoring

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iperov 2019-03-26 11:09:44 +04:00
commit b03b147bae
18 changed files with 452 additions and 447 deletions
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1
converters/ConverterImage.py
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@ -4,7 +4,6 @@ from facelib import FaceType
import cv2
import numpy as np
from utils import image_utils
'''
predictor_func:

12
converters/ConverterMasked.py
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@ -5,7 +5,7 @@ from facelib import FaceType
from facelib import FANSegmentator
import cv2
import numpy as np
from utils import image_utils
import imagelib
from interact import interact as io
'''
default_mode = {1:'overlay',
@ -262,7 +262,7 @@ class ConverterMasked(Converter):
if debug:
debugs += [ np.clip( cv2.warpAffine( prd_face_bgr, face_output_mat, img_size, np.zeros(img_bgr.shape, dtype=np.float32), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT ), 0, 1.0) ]
prd_face_bgr = image_utils.reinhard_color_transfer ( np.clip( (prd_face_bgr*255).astype(np.uint8), 0, 255),
prd_face_bgr = imagelib.reinhard_color_transfer ( np.clip( (prd_face_bgr*255).astype(np.uint8), 0, 255),
np.clip( (dst_face_bgr*255).astype(np.uint8), 0, 255),
source_mask=prd_face_mask_a, target_mask=prd_face_mask_a)
prd_face_bgr = np.clip( prd_face_bgr.astype(np.float32) / 255.0, 0.0, 1.0)
@ -275,7 +275,7 @@ class ConverterMasked(Converter):
if debug:
debugs += [ np.clip( cv2.warpAffine( prd_face_bgr, face_output_mat, img_size, np.zeros(img_bgr.shape, dtype=np.float32), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT ), 0, 1.0) ]
prd_face_bgr = image_utils.linear_color_transfer (prd_face_bgr, dst_face_bgr)
prd_face_bgr = imagelib.linear_color_transfer (prd_face_bgr, dst_face_bgr)
prd_face_bgr = np.clip( prd_face_bgr, 0.0, 1.0)
if debug:
@ -300,7 +300,7 @@ class ConverterMasked(Converter):
hist_match_2 = dst_face_bgr*hist_mask_a + (1.0-hist_mask_a)* np.ones ( prd_face_bgr.shape[:2] + (1,) , dtype=np.float32)
hist_match_2[ hist_match_1 > 1.0 ] = 1.0
prd_face_bgr = image_utils.color_hist_match(hist_match_1, hist_match_2, self.hist_match_threshold )
prd_face_bgr = imagelib.color_hist_match(hist_match_1, hist_match_2, self.hist_match_threshold )
if self.mode == 'hist-match-bw':
prd_face_bgr = prd_face_bgr.astype(dtype=np.float32)
@ -334,14 +334,14 @@ class ConverterMasked(Converter):
if self.mode == 'seamless-hist-match':
out_face_bgr = cv2.warpAffine( out_img, face_mat, (self.output_size, self.output_size) )
new_out_face_bgr = image_utils.color_hist_match(out_face_bgr, dst_face_bgr, self.hist_match_threshold)
new_out_face_bgr = imagelib.color_hist_match(out_face_bgr, dst_face_bgr, self.hist_match_threshold)
new_out = cv2.warpAffine( new_out_face_bgr, face_mat, img_size, img_bgr.copy(), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
out_img = np.clip( img_bgr*(1-img_mask_blurry_aaa) + (new_out*img_mask_blurry_aaa) , 0, 1.0 )
if self.final_image_color_degrade_power != 0:
if debug:
debugs += [out_img.copy()]
out_img_reduced = image_utils.reduce_colors(out_img, 256)
out_img_reduced = imagelib.reduce_colors(out_img, 256)
if self.final_image_color_degrade_power == 100:
out_img = out_img_reduced
else: