def process_extract(arguments):
from mainscripts import Extractor
Extractor.main(input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
debug=arguments.debug,
detector=arguments.detector,
multi_gpu=arguments.multi_gpu,
manual_fix=arguments.manual_fix)
def process_extract(arguments):
from mainscripts import Extractor
Extractor.main(input_dir=arguments.input_dir,
output_dir=arguments.output_dir,
debug=arguments.debug,
face_type=arguments.face_type,
detector=arguments.detector,
multi_gpu=arguments.multi_gpu,
manual_fix=arguments.manual_fix,
manual_window_size=arguments.manual_window_size)
def refix(workspace):
dst = get_workspace_dst(workspace)
dst_aligned = os.path.join(dst, "aligned")
recover_filename_if_nessesary(dst_aligned)
extract_imgs = [
f if f.endswith(".jpg") or f.endswith(".png") else ""
for f in os.listdir(dst)
]
max_img_no = int(max(extract_imgs).split(".")[0])
ext = extract_imgs[0].split(".")[1]
aligned_imgs = list(
sorted(
filter(lambda x: x is not None, [
f if f.endswith(".jpg") or f.endswith(".png") else None
for f in os.listdir(dst_aligned)
])))
need_fix_no = []
i = 0 # 当前文件下标
j = 1 # 期望文件名
while i <= max_img_no and j <= max_img_no and i < len(aligned_imgs):
if aligned_imgs[i].startswith("%05d" % j):
i += 1
j += 1
else:
# print(aligned_imgs[i], j)
need_fix_no.append(j)
j += 1
for k in range(j, max_img_no + 1):
need_fix_no.append(k)
# print(k)
if len(need_fix_no) == 0:
return
fix_workspace = os.path.join(dst, "fix")
import shutil
if os.path.exists(fix_workspace):
shutil.rmtree(fix_workspace)
os.mkdir(fix_workspace)
for no in need_fix_no:
f = os.path.join(dst, "%05d.%s" % (no, ext))
io.log_info(f)
shutil.copy(f, fix_workspace)
fix_workspace_aligned = os.path.join(fix_workspace, "aligned")
from mainscripts import Extractor
Extractor.main(fix_workspace,
fix_workspace_aligned,
detector="manual",
manual_fix=False)
# Extractor.extract_fanseg(fix_workspace_aligned)
dfl.dfl_extract_fanseg(fix_workspace_aligned)
for f in os.listdir(fix_workspace_aligned):
f = os.path.join(fix_workspace_aligned, f)
io.log_info(f)
shutil.move(f, dst_aligned)
shutil.rmtree(fix_workspace)
def extract_dst_image(workspace):
import os
from mainscripts import Extractor
# 提取人脸
input_dir = os.path.join(workspace, "data_dst")
output_dir = os.path.join(workspace, "data_dst/aligned")
debug_dir = os.path.join(workspace, "data_dst/aligned_debug")
Extractor.main(input_dir, output_dir, debug_dir, "s3fd", manual_fix=True)
# fanseg
Extractor.extract_fanseg(output_dir)
def prepare(workspace, detector="s3fd", manual_fix=False):
import os
import shutil
from mainscripts import Extractor
from mainscripts import VideoEd
for f in os.listdir(workspace):
ext = os.path.splitext(f)[-1]
if ext not in ['.mp4', '.avi']:
continue
if f.startswith("result"):
continue
# 获取所有的data_dst文件
tmp_dir = os.path.join(workspace, "_tmp")
tmp_aligned = os.path.join(tmp_dir, "aligned")
tmp_video_dir = os.path.join(tmp_dir, "video")
if os.path.exists(tmp_dir):
shutil.rmtree(tmp_dir)
if not os.path.exists(tmp_dir):
os.mkdir(tmp_dir)
os.mkdir(tmp_video_dir)
video = os.path.join(workspace, f)
# 提取帧
VideoEd.extract_video(video, tmp_dir, "png", 0)
# 提取人脸
if detector == "manual":
import winsound
winsound.Beep(300, 500)
Extractor.main(tmp_dir,
tmp_aligned,
detector=detector,
manual_fix=manual_fix)
# fanseg
Extractor.extract_fanseg(tmp_aligned)
if detector != "manual":
# # 两组人脸匹配
# skip_by_pitch(os.path.join(workspace, "data_src", "aligned"), os.path.join(tmp_dir, "aligned"))
# 排序
dfl.dfl_sort_by_hist(tmp_aligned)
# 保存video
shutil.copy(video, tmp_video_dir)
# 重命名
fname = f.replace(ext, "")
dst_dir = os.path.join(workspace,
"data_dst_%s_%s" % (get_time_str(), fname))
shutil.move(tmp_dir, dst_dir)
# 移动video
data_trash = os.path.join(workspace, "../trash_workspace")
if not os.path.exists(data_trash):
os.mkdir(data_trash)
shutil.move(video, data_trash)
import winsound
winsound.Beep(300, 500)
def process_extract(arguments):
from mainscripts import Extractor
Extractor.main( arguments.input_dir,
arguments.output_dir,
arguments.debug,
arguments.detector,
arguments.manual_fix,
arguments.manual_output_debug_fix,
arguments.manual_window_size,
face_type=arguments.face_type,
device_args={'cpu_only' : arguments.cpu_only,
'multi_gpu' : arguments.multi_gpu,
}
)
def process_extract(arguments):
osex.set_process_lowest_prio()
from mainscripts import Extractor
Extractor.main( detector = arguments.detector,
input_path = Path(arguments.input_dir),
output_path = Path(arguments.output_dir),
output_debug = arguments.output_debug,
manual_fix = arguments.manual_fix,
manual_output_debug_fix = arguments.manual_output_debug_fix,
manual_window_size = arguments.manual_window_size,
face_type = arguments.face_type,
cpu_only = arguments.cpu_only,
force_gpu_idxs = [ int(x) for x in arguments.force_gpu_idxs.split(',') ] if arguments.force_gpu_idxs is not None else None,
)
def process_extract(arguments):
os_utils.set_process_lowest_prio()
from mainscripts import Extractor
Extractor.main(arguments.input_dir,
arguments.output_dir,
arguments.debug_dir,
arguments.detector,
arguments.manual_fix,
arguments.manual_output_debug_fix,
arguments.manual_window_size,
face_type=arguments.face_type,
device_args={
'cpu_only': arguments.cpu_only,
'multi_gpu': arguments.multi_gpu,
},
min_pixel=arguments.min_pixel)
def SPExtractFaceLab(context):
args = context.args
Extractor.main(
args.inputData,
args.outputData,
debug_dir=None,
detector=args.detector,
manual_fix=False,
manual_output_debug_fix=False,
manual_window_size=1368,
image_size=256,
face_type=args.faceType,
device_args={
"cpu_only": args.cpuOnly,
"multi_gpu": args.multiGpu
},
)
return args.outputData
def extract():
import os
import shutil
from mainscripts import VideoEd
from mainscripts import Extractor
from interact import interact as io
root_dir = get_root_path()
extract_workspace = os.path.join(root_dir, "extract_workspace")
target_dir = os.path.join(extract_workspace, "aligned_")
valid_exts = [".mp4", ".avi", ".wmv", ".mkv"]
fps = io.input_int(
"Enter FPS ( ?:help skip:fullfps ) : ",
0,
help_message=
"How many frames of every second of the video will be extracted.")
min_pixel = io.input_int("Enter Min Pixel ( ?:help skip: 512) : ",
512,
help_message="Min Pixel")
def file_filter(file):
if os.path.isdir(os.path.join(extract_workspace, file)):
return False
ext = os.path.splitext(file)[-1]
if ext not in valid_exts:
return False
return True
files = list(filter(file_filter, os.listdir(extract_workspace)))
files.sort()
pos = 0
for file in files:
pos += 1
io.log_info("@@@@@ Start Process %s, %d / %d" %
(file, pos, len(files)))
# 提取图片
input_file = os.path.join(extract_workspace, file)
output_dir = os.path.join(extract_workspace, "extract_images")
if not os.path.exists(output_dir):
os.mkdir(output_dir)
for f in os.listdir(output_dir):
os.remove(os.path.join(output_dir, f))
VideoEd.extract_video(input_file,
output_dir,
output_ext="png",
fps=fps)
io.log_info("@@@@@ Start Extract %s, %d / %d" %
(file, pos, len(files)))
# 提取人脸
input_dir = output_dir
output_dir = os.path.join(extract_workspace, "_current")
debug_dir = os.path.join(extract_workspace, "debug")
Extractor.main(input_dir,
output_dir,
debug_dir,
"s3fd",
min_pixel=min_pixel)
# fanseg
io.log_info("@@@@@ Start FanSeg %s, %d / %d" %
(file, pos, len(files)))
Extractor.extract_fanseg(output_dir)
# 复制到结果集
io.log_info("@@@@@ Start Move %s, %d / %d" % (file, pos, len(files)))
if not os.path.exists(target_dir):
os.mkdir(target_dir)
ts = get_time_str()
for f in os.listdir(output_dir):
src = os.path.join(output_dir, f)
dst = os.path.join(target_dir, "%s_%s" % (ts, f))
shutil.move(src, dst)
# 全部做完，删除该文件
io.log_info("@@@@@ Finish %s, %d / %d" % (file, pos, len(files)))
os.remove(os.path.join(extract_workspace, file))
os.rmdir(output_dir)
