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ConverterMasked: removed default transfercolor,

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added Apply color transfer to predicted face - modes rct / lct
This commit is contained in:
iperov 2019-02-13 16:27:57 +04:00
commit 2bd983703e
2 changed files with 174 additions and 16 deletions
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44
models/ConverterMasked.py
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@ -34,7 +34,6 @@ class ConverterMasked(ConverterBase):
self.output_size = output_size
self.face_type = face_type
self.clip_hborder_mask_per = clip_hborder_mask_per
self.TFLabConverter = None
mode = input_int ("Choose mode: (1) overlay, (2) hist match, (3) hist match bw, (4) seamless, (5) seamless hist match, (6) raw. Default - %d : " % (default_mode) , default_mode)
@ -72,9 +71,9 @@ class ConverterMasked(ConverterBase):
self.seamless_erode_mask_modifier = np.clip ( input_int ("Choose seamless erode mask modifier [-100..100] (skip:0) : ", 0), -100, 100)
self.output_face_scale = np.clip ( 1.0 + input_int ("Choose output face scale modifier [-50..50] (skip:0) : ", 0)*0.01, 0.5, 1.5)
self.color_transfer_mode = input_str ("Apply color transfer to predicted face? Choose mode ( rct/lct skip:None ) : ", None, ['rct','lct'])
if self.mode != 'raw':
self.transfercolor = input_bool("Transfer color from dst face to converted final face? (y/n skip:n) : ", False)
self.final_image_color_degrade_power = np.clip ( input_int ("Degrade color power of final image [0..100] (skip:0) : ", 0), 0, 100)
self.alpha = input_bool("Export png with alpha channel? (y/n skip:n) : ", False)
@ -215,6 +214,29 @@ class ConverterMasked(ConverterBase):
if debug:
debugs += [img_mask_blurry_aaa.copy()]
if self.color_transfer_mode is not None:
if self.color_transfer_mode == 'rct':
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),
np.clip( (dst_face_bgr*255).astype(np.uint8), 0, 255) )
prd_face_bgr = np.clip( prd_face_bgr.astype(np.float32) / 255.0, 0.0, 1.0)
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) ]
elif self.color_transfer_mode == 'lct':
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 = np.clip( prd_face_bgr, 0.0, 1.0)
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) ]
if self.mode == 'hist-match-bw':
prd_face_bgr = cv2.cvtColor(prd_face_bgr, cv2.COLOR_BGR2GRAY)
prd_face_bgr = np.repeat( np.expand_dims (prd_face_bgr, -1), (3,), -1 )
@ -238,9 +260,10 @@ class ConverterMasked(ConverterBase):
if self.mode == 'hist-match-bw':
prd_face_bgr = prd_face_bgr.astype(dtype=np.float32)
out_img = cv2.warpAffine( prd_face_bgr, face_output_mat, img_size, out_img, cv2.WARP_INVERSE_MAP | cv2.INTER_LANCZOS4, cv2.BORDER_TRANSPARENT )
out_img = np.clip(out_img, 0.0, 1.0)
if debug:
debugs += [out_img.copy()]
@ -265,16 +288,7 @@ class ConverterMasked(ConverterBase):
new_out_face_bgr = image_utils.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.transfercolor:
if self.TFLabConverter is None:
self.TFLabConverter = image_utils.TFLabConverter()
img_lab_l, img_lab_a, img_lab_b = np.split ( self.TFLabConverter.bgr2lab (img_bgr), 3, axis=-1 )
out_img_lab_l, out_img_lab_a, out_img_lab_b = np.split ( self.TFLabConverter.bgr2lab (out_img), 3, axis=-1 )
out_img = self.TFLabConverter.lab2bgr ( np.concatenate([out_img_lab_l, img_lab_a, img_lab_b], axis=-1) )
if self.final_image_color_degrade_power != 0:
if debug:
debugs += [out_img.copy()]