def process_convert(arguments):
from mainscripts import Converter
Converter.main(input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
aligned_dir=arguments.aligned_dir,
model_dir=arguments.model_dir,
model_name=arguments.model_name,
debug=arguments.debug,
force_gpu_idx=arguments.force_gpu_idx,
cpu_only=arguments.cpu_only)
def process_convert(arguments):
from mainscripts import Converter
Converter.main(input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
aligned_dir=arguments.aligned_dir,
model_dir=arguments.model_dir,
model_name=arguments.model_name,
debug=arguments.debug,
mode=arguments.mode,
mask_type=arguments.mask_type)
def process_convert(arguments):
args = {'input_dir' : arguments.input_dir,
'output_dir' : arguments.output_dir,
'aligned_dir' : arguments.aligned_dir,
'model_dir' : arguments.model_dir,
'model_name' : arguments.model_name,
'debug' : arguments.debug,
}
device_args = {'cpu_only' : arguments.cpu_only,
'force_gpu_idx' : arguments.force_gpu_idx,
}
from mainscripts import Converter
Converter.main (args, device_args)
def process_convert(arguments):
os_utils.set_process_lowest_prio()
args = {'training_data_src_dir' : arguments.training_data_src_dir,
'input_dir' : arguments.input_dir,
'output_dir' : arguments.output_dir,
'aligned_dir' : arguments.aligned_dir,
'model_dir' : arguments.model_dir,
'model_name' : arguments.model_name,
}
device_args = {'cpu_only' : arguments.cpu_only,
'force_gpu_idx' : arguments.force_gpu_idx,
}
from mainscripts import Converter
Converter.main (args, device_args)
def SPConvertLab(context):
args = context.args
convert_args = {
"input_dir": args.inputData,
"output_dir": args.outputData,
"aligned_dir": args.alignedDir,
"model_dir": args.modelDir,
"model_name": args.modelName,
}
device_args = {
"cpu_only": args.cpuOnly,
"force_gpu_idx": args.forceGpuIdx,
}
if not args.__edit:
os.environ["SP_FaceLab_Edit"] = "False"
from mainscripts import Converter
Converter.main(convert_args, device_args)
return args.outputData
def process_convert(arguments):
if arguments.ask_for_params:
try:
mode = int ( input ("Choose mode: (1) hist match, (2) hist match bw, (3) seamless (default), (4) seamless hist match : ") )
except:
mode = 3
if mode == 1:
arguments.mode = 'hist-match'
elif mode == 2:
arguments.mode = 'hist-match-bw'
elif mode == 3:
arguments.mode = 'seamless'
elif mode == 4:
arguments.mode = 'seamless-hist-match'
if arguments.mode == 'hist-match' or arguments.mode == 'hist-match-bw':
try:
arguments.masked_hist_match = bool ( {"1":True,"0":False}[input("Masked hist match? [0 or 1] (default 1) : ").lower()] )
except:
arguments.masked_hist_match = True
if arguments.mode == 'hist-match' or arguments.mode == 'hist-match-bw' or arguments.mode == 'seamless-hist-match':
try:
hist_match_threshold = int ( input ("Hist match threshold. [0..255] (default - 255) : ") )
arguments.hist_match_threshold = hist_match_threshold
except:
arguments.hist_match_threshold = 255
try:
arguments.use_predicted_mask = bool ( {"1":True,"0":False}[input("Use predicted mask? [0 or 1] (default 1) : ").lower()] )
except:
arguments.use_predicted_mask = False
try:
arguments.erode_mask_modifier = int ( input ("Choose erode mask modifier [-200..200] (default 0) : ") )
except:
arguments.erode_mask_modifier = 0
try:
arguments.blur_mask_modifier = int ( input ("Choose blur mask modifier [-200..200] (default 0) : ") )
except:
arguments.blur_mask_modifier = 0
if arguments.mode == 'seamless' or arguments.mode == 'seamless-hist-match':
try:
arguments.seamless_erode_mask_modifier = int ( input ("Choose seamless erode mask modifier [-100..100] (default 0) : ") )
except:
arguments.seamless_erode_mask_modifier = 0
try:
arguments.output_face_scale_modifier = int ( input ("Choose output face scale modifier [-50..50] (default 0) : ") )
except:
arguments.output_face_scale_modifier = 0
try:
arguments.transfercolor = bool ( {"1":True,"0":False}[input("Transfer color from dst face to converted final face? [0 or 1] (default 0) : ").lower()] )
except:
arguments.transfercolor = False
try:
arguments.final_image_color_degrade_power = int ( input ("Degrade color power of final image [0..100] (default 0) : ") )
except:
arguments.final_image_color_degrade_power = 0
try:
arguments.alpha = bool ( {"1":True,"0":False}[input("Export png with alpha channel? [0..1] (default 0) : ").lower()] )
except:
arguments.alpha = False
arguments.erode_mask_modifier = np.clip ( int(arguments.erode_mask_modifier), -200, 200)
arguments.blur_mask_modifier = np.clip ( int(arguments.blur_mask_modifier), -200, 200)
arguments.seamless_erode_mask_modifier = np.clip ( int(arguments.seamless_erode_mask_modifier), -100, 100)
arguments.output_face_scale_modifier = np.clip ( int(arguments.output_face_scale_modifier), -50, 50)
from mainscripts import Converter
Converter.main (
input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
aligned_dir=arguments.aligned_dir,
model_dir=arguments.model_dir,
model_name=arguments.model_name,
debug = arguments.debug,
mode = arguments.mode,
masked_hist_match = arguments.masked_hist_match,
hist_match_threshold = arguments.hist_match_threshold,
use_predicted_mask = arguments.use_predicted_mask,
erode_mask_modifier = arguments.erode_mask_modifier,
blur_mask_modifier = arguments.blur_mask_modifier,
seamless_erode_mask_modifier = arguments.seamless_erode_mask_modifier,
output_face_scale_modifier = arguments.output_face_scale_modifier,
final_image_color_degrade_power = arguments.final_image_color_degrade_power,
transfercolor = arguments.transfercolor,
alpha = arguments.alpha,
force_best_gpu_idx = arguments.force_best_gpu_idx,
cpu_only = arguments.cpu_only
)
def process_convert(arguments):
if arguments.ask_for_params:
try:
mode = int(
input(
"Choose mode: (1) hist match, (2) hist match bw, (3) seamless (default), (4) seamless hist match : "
))
except:
mode = 3
if mode == 1:
arguments.mode = 'hist-match'
elif mode == 2:
arguments.mode = 'hist-match-bw'
elif mode == 3:
arguments.mode = 'seamless'
elif mode == 4:
arguments.mode = 'seamless-hist-match'
if arguments.mode == 'hist-match' or arguments.mode == 'hist-match-bw':
try:
choice = int(
input(
"Masked hist match? [0..1] (default - model choice) : "
))
arguments.masked_hist_match = (choice != 0)
except:
arguments.masked_hist_match = None
try:
arguments.erode_mask_modifier = int(
input(
"Choose erode mask modifier [-100..100] (default 0) : "
))
except:
arguments.erode_mask_modifier = 0
try:
arguments.blur_mask_modifier = int(
input(
"Choose blur mask modifier [-100..200] (default 0) : ")
)
except:
arguments.blur_mask_modifier = 0
arguments.erode_mask_modifier = np.clip(
int(arguments.erode_mask_modifier), -100, 100)
arguments.blur_mask_modifier = np.clip(
int(arguments.blur_mask_modifier), -100, 200)
from mainscripts import Converter
Converter.main(input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
aligned_dir=arguments.aligned_dir,
model_dir=arguments.model_dir,
model_name=arguments.model_name,
debug=arguments.debug,
mode=arguments.mode,
masked_hist_match=arguments.masked_hist_match,
erode_mask_modifier=arguments.erode_mask_modifier,
blur_mask_modifier=arguments.blur_mask_modifier,
force_best_gpu_idx=arguments.force_best_gpu_idx)
def process_convert(arguments):
if arguments.ask_for_params:
try:
mode = int(
input(
"Choose mode: (1) hist match, (2) hist match bw, (3) seamless (default), (4) seamless hist match : "
))
except:
mode = 3
if mode == 1:
arguments.mode = 'hist-match'
elif mode == 2:
arguments.mode = 'hist-match-bw'
elif mode == 3:
arguments.mode = 'seamless'
elif mode == 4:
arguments.mode = 'seamless-hist-match'
if arguments.mode == 'hist-match' or arguments.mode == 'hist-match-bw':
try:
choice = int(
input(
"Masked hist match? [0..1] (default - model choice) : "
))
arguments.masked_hist_match = (choice != 0)
except:
arguments.masked_hist_match = None
try:
arguments.erode_mask_modifier = int(
input(
"Choose erode mask modifier [-100..100] (default 0) : "
))
except:
arguments.erode_mask_modifier = 0
try:
arguments.blur_mask_modifier = int(
input(
"Choose blur mask modifier [-100..200] (default 0) : ")
)
except:
arguments.blur_mask_modifier = 0
try:
arguments.output_face_scale_modifier = int(
input(
"Choose output face scale modifier [-50..50] (default 0) : "
))
except:
arguments.output_face_scale_modifier = 0
try:
arguments.transfercolor = bool({
"1": True,
"0": False
}[input(
"Transfer color from original DST image? [0..1] (default 0) : "
).lower()])
except:
arguments.transfercolor = False
try:
arguments.final_image_color_degrade_power = int(
input(
"Degrade color power of final image [0..100] (default 0) : "
))
except:
arguments.final_image_color_degrade_power = 0
try:
arguments.alpha = bool({
"1": True,
"0": False
}[input("Export png with alpha channel? [0..1] (default 0) : "
).lower()])
except:
arguments.alpha = False
arguments.erode_mask_modifier = np.clip(
int(arguments.erode_mask_modifier), -100, 100)
arguments.blur_mask_modifier = np.clip(
int(arguments.blur_mask_modifier), -100, 200)
arguments.output_face_scale_modifier = np.clip(
int(arguments.output_face_scale_modifier), -50, 50)
from mainscripts import Converter
Converter.main(
input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
aligned_dir=arguments.aligned_dir,
model_dir=arguments.model_dir,
model_name=arguments.model_name,
debug=arguments.debug,
mode=arguments.mode,
masked_hist_match=arguments.masked_hist_match,
erode_mask_modifier=arguments.erode_mask_modifier,
blur_mask_modifier=arguments.blur_mask_modifier,
output_face_scale_modifier=arguments.output_face_scale_modifier,
final_image_color_degrade_power=arguments.
final_image_color_degrade_power,
transfercolor=arguments.transfercolor,
alpha=arguments.alpha,
force_best_gpu_idx=arguments.force_best_gpu_idx)