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https://github.com/iperov/DeepFaceLab.git
synced 2025-07-11 07:37:03 -07:00
added option to converter --output-face-scale-modifier
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iperov
parent
2576a411a5
commit
64c3e57f1c
3 changed files with 29 additions and 19 deletions
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@ -36,7 +36,7 @@ landmarks_68_pt = { "mouth": (48,68),
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"nose": (27, 36), # missed one point
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"jaw": (0, 17) }
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def get_transform_mat (image_landmarks, output_size, face_type):
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def get_transform_mat (image_landmarks, output_size, face_type, scale=1.0):
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if not isinstance(image_landmarks, np.ndarray):
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image_landmarks = np.array (image_landmarks)
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@ -67,6 +67,8 @@ def get_transform_mat (image_landmarks, output_size, face_type):
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mat = umeyama(image_landmarks[17:], landmarks_2D, True)[0:2]
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mat = mat * (output_size - 2 * padding)
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mat[:,2] += padding
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mat *= (1 / scale)
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mat[:,2] += -output_size*( ( (1 / scale) - 1.0 ) / 2 )
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return mat
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8
main.py
8
main.py
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@ -137,6 +137,11 @@ if __name__ == "__main__":
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except:
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arguments.blur_mask_modifier = 0
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try:
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arguments.output_face_scale_modifier = int ( input ("Choose output face scale modifier [-50..50] (default 0) : ") )
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except:
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arguments.output_face_scale_modifier = 0
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try:
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arguments.alpha = bool ( {"1":True,"0":False}[input("Export png with alpha channel? [0..1] (default 0) : ").lower()] )
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except:
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@ -149,6 +154,7 @@ if __name__ == "__main__":
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arguments.erode_mask_modifier = np.clip ( int(arguments.erode_mask_modifier), -100, 100)
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arguments.blur_mask_modifier = np.clip ( int(arguments.blur_mask_modifier), -100, 200)
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arguments.output_face_scale_modifier = np.clip ( int(arguments.output_face_scale_modifier), -50, 50)
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from mainscripts import Converter
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Converter.main (
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@ -162,6 +168,7 @@ if __name__ == "__main__":
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masked_hist_match = arguments.masked_hist_match,
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erode_mask_modifier = arguments.erode_mask_modifier,
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blur_mask_modifier = arguments.blur_mask_modifier,
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output_face_scale_modifier = arguments.output_face_scale_modifier,
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force_best_gpu_idx = arguments.force_best_gpu_idx,
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alpha = arguments.alpha,
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transfercolor = arguments.transfercolor,
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@ -178,6 +185,7 @@ if __name__ == "__main__":
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convert_parser.add_argument('--masked-hist-match', type=str2bool, nargs='?', const=True, default=None, help="True or False. Excludes background for hist match. Default - model decide.")
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convert_parser.add_argument('--erode-mask-modifier', type=int, dest="erode_mask_modifier", default=0, help="Automatic erode mask modifier. Valid range [-100..100].")
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convert_parser.add_argument('--blur-mask-modifier', type=int, dest="blur_mask_modifier", default=0, help="Automatic blur mask modifier. Valid range [-100..200].")
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convert_parser.add_argument('--output-face-scale-modifier', type=int, dest="output_face_scale_modifier", default=0, help="Output face scale modifier. Valid range [-50..50].")
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convert_parser.add_argument('--debug', action="store_true", dest="debug", default=False, help="Debug converter.")
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convert_parser.add_argument('--alpha', action="store_true", dest="alpha", default=False, help="alpha channel.")
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convert_parser.add_argument('--transfercolor', action="store_true", dest="transfercolor", default=False, help="transfer color from dst to merged.")
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@ -5,11 +5,6 @@ import cv2
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import numpy as np
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from utils import image_utils
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'''
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predictor:
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input: [predictor_input_size, predictor_input_size, BGRA]
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output: [predictor_input_size, predictor_input_size, BGRA]
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'''
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class ConverterMasked(ConverterBase):
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@ -25,6 +20,7 @@ class ConverterMasked(ConverterBase):
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mode='seamless',
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erode_mask_modifier=0,
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blur_mask_modifier=0,
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output_face_scale_modifier=0.0,
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alpha=False,
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transfercolor=False,
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**in_options):
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@ -41,6 +37,7 @@ class ConverterMasked(ConverterBase):
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self.mode = mode
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self.erode_mask_modifier = erode_mask_modifier
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self.blur_mask_modifier = blur_mask_modifier
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self.output_face_scale = np.clip(1.0 + output_face_scale_modifier*0.01, 0.5, 1.0)
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self.alpha = alpha
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self.transfercolor = transfercolor
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@ -68,6 +65,8 @@ class ConverterMasked(ConverterBase):
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img_face_mask_a = LandmarksProcessor.get_image_hull_mask (img_bgr, img_face_landmarks)
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face_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, self.output_size, face_type=self.face_type)
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face_output_mat = LandmarksProcessor.get_transform_mat (img_face_landmarks, self.output_size, face_type=self.face_type, scale=self.output_face_scale)
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dst_face_bgr = cv2.warpAffine( img_bgr , face_mat, (self.output_size, self.output_size), flags=cv2.INTER_LANCZOS4 )
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dst_face_mask_a_0 = cv2.warpAffine( img_face_mask_a, face_mat, (self.output_size, self.output_size), flags=cv2.INTER_LANCZOS4 )
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@ -84,7 +83,7 @@ class ConverterMasked(ConverterBase):
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prd_face_mask_a = np.expand_dims (prd_face_mask_a_0, axis=-1)
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prd_face_mask_aaa = np.repeat (prd_face_mask_a, (3,), axis=-1)
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img_prd_face_mask_aaa = cv2.warpAffine( prd_face_mask_aaa, face_mat, img_size, np.zeros(img_bgr.shape, dtype=float), flags=cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4 )
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img_prd_face_mask_aaa = cv2.warpAffine( prd_face_mask_aaa, face_output_mat, img_size, np.zeros(img_bgr.shape, dtype=float), flags=cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4 )
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img_prd_face_mask_aaa = np.clip (img_prd_face_mask_aaa, 0.0, 1.0)
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img_face_mask_aaa = img_prd_face_mask_aaa
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@ -146,7 +145,7 @@ class ConverterMasked(ConverterBase):
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if self.mode == 'hist-match' or self.mode == 'hist-match-bw':
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if debug:
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debugs += [ cv2.warpAffine( prd_face_bgr, face_mat, img_size, np.zeros(img_bgr.shape, dtype=np.float32), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT ) ]
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debugs += [ 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 ) ]
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hist_mask_a = np.ones ( prd_face_bgr.shape[:2] + (1,) , dtype=prd_face_bgr.dtype)
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@ -160,7 +159,8 @@ class ConverterMasked(ConverterBase):
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if self.mode == 'hist-match-bw':
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prd_face_bgr = prd_face_bgr.astype(np.float32)
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out_img = cv2.warpAffine( prd_face_bgr, face_mat, img_size, out_img, cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
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out_img = cv2.warpAffine( prd_face_bgr, face_output_mat, img_size, out_img, cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
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if debug:
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debugs += [out_img.copy()]
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@ -177,7 +177,7 @@ class ConverterMasked(ConverterBase):
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debugs += [out_img.copy()]
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if self.clip_border_mask_per > 0:
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img_prd_border_rect_mask_a = cv2.warpAffine( prd_border_rect_mask_a, face_mat, img_size, np.zeros(img_bgr.shape, dtype=np.float32), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
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img_prd_border_rect_mask_a = cv2.warpAffine( prd_border_rect_mask_a, face_output_mat, img_size, np.zeros(img_bgr.shape, dtype=np.float32), cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
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img_prd_border_rect_mask_a = np.expand_dims (img_prd_border_rect_mask_a, -1)
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out_img = out_img * img_prd_border_rect_mask_a + img_bgr * (1.0 - img_prd_border_rect_mask_a)
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