# coding=utf-8
from __future__ import absolute_import, print_function
import os
from suanpan.app.arguments import Folder, String, Int, Float
from suanpan.app import app
from lib import cli
@app.input(Folder(key="inputData"))
@app.param(String(key="detector", default="cv2-dnn",
help="cv2-dnn mtcnn s3fd"))
@app.param(String(key="aligner", default="cv2-dnn", help="cv2-dnn fan"))
@app.param(
String(key="normalization", default="none", help="none clahe hist mean"))
@app.param(Int(key="minSize", default=0, help="(0, 1080)"))
@app.param(Float(key="blurThreshold", default=0.0, help="(0.0, 100.0)"))
@app.output(Folder(key="outputData1"))
@app.output(Folder(key="outputData2"))
def SPExtractFace(context):
args = context.args
PARSER = cli.FullHelpArgumentParser()
EXTRACT = cli.ExtractArgs(PARSER, "extract",
"Extract the faces from pictures")
ARGUMENTS = PARSER.parse_args([
"--input-dir",
args.inputData,
"--output-dir",
args.outputData1,
import suanpan
from suanpan.app import app
from suanpan.app.arguments import String
@app.input(String(key="inputData1", alias="name", default="Suanpan"))
@app.output(String(key="outputData1", alias="result"))
def hello_world(context):
args = context.args
return f"Hello World, {args.name}!"
if __name__ == "__main__":
suanpan.run(app)
# coding=utf-8
from __future__ import absolute_import, print_function
from suanpan.app.arguments import Folder, String, Int
from suanpan.app import app
from mainscripts import VideoEd
@app.input(Folder(key="inputData"))
@app.param(String(key="ext", default="png"))
@app.param(Int(key="factor", default=5))
@app.output(Folder(key="outputData"))
def SPDenoise(context):
args = context.args
VideoEd.denoise_image_sequence(args.inputData,
args.outputData,
ext=args.ext,
factor=args.factor)
return args.outputData
if __name__ == "__main__":
SPDenoise()
# coding=utf-8
from __future__ import absolute_import, print_function
import os
from suanpan.app.arguments import String
from suanpan.app import app
from suanpan.storage import storage
@app.output(String(key="modelDir"))
def SPTrainSync(context):
args = context.args
path = os.path.split(str(args.modelDir))[0]
storage.upload(path.replace("/sp_data/", ""), path)
return "Model Saved..."
if __name__ == "__main__":
SPTrainSync()
# coding=utf-8
from __future__ import absolute_import, print_function
from suanpan.app.arguments import Folder, String, Float, Int
from suanpan.app import app
from tools import cli
from lib.cli import FullHelpArgumentParser
@app.input(Folder(key="inputData"))
@app.param(
String(
key="sortBy",
default="face",
help=
"blur, face, face-cnn, face-cnn-dissim, face-yaw, hist, hist-dissim",
))
@app.param(
Float(
key="refThreshold",
default=-1.0,
help="(-1.0, 10.0) Defaults: face-cnn 7.2, hist 0.3",
))
@app.param(String(key="finalProcess", default="rename",
help="folders, rename"))
@app.param(
String(key="groupBy",
default="hist",
help="blur, face-cnn, face-yaw, hist"))
@app.param(Int(key="bins", default=5, help="(1, 100)"))
@app.output(Folder(key="outputData"))
# coding=utf-8
from __future__ import absolute_import, print_function
from pm4py.algo.discovery.dfg import factory as dfg_miner
from pm4py.objects.conversion.log.factory import apply as df_to_log
from suanpan.app import app
from suanpan.app.arguments import Json, Csv, String, Bool
from utils.csv import convert_df_pm_format
from utils.dfg import dfg_vis, find_start_end
@app.input(Csv(key="inputData1", alias="inputData"))
@app.param(
String(key="param1",
alias="measure",
default="performance",
help="performance, frequency"))
@app.param(Bool(key="param2", alias="hideStartEndNode", default=False))
@app.output(Json(key="outputData1", alias="outputData"))
def SPDFG(context):
args = context.args
df = convert_df_pm_format(args.inputData)
log = df_to_log(df)
dfg = dfg_miner.apply(log, variant=args.measure)
params = {}
if not args.hideStartEndNode:
start, end = find_start_end(dfg)
params = {"start_activities": start, "end_activities": end}
outputData = dfg_vis(dfg, log=log, parameters=params, measure=args.measure)
return outputData
annot = data["metadata"]
names = pd.read_csv(csv_path, header=None)
for key in annot.keys():
x, y, w, h = annot[key]['xy'][1:]
for i in names[0]: # 无列头 用0
new_txt = i
pt1 = (x, y)
pt2 = (x + w, y + h)
text_edit(image_path, pt1, pt2, new_txt, color)
@app.input(Folder(key="inputData1"))
@app.input(Folder(key="inputData2"))
@app.input(Folder(key="inputData3"))
@app.param(String(key="param1"))
@app.param(String(key="param2"))
@app.output(Folder(key="outputData1"))
def image_edit(context):
args = context.args
print("*" * 20)
print(args.inputData1)
dir_name = args.inputData1
global color
color = colors[args.param1]
print(color)
global font
font = fonts[args.param2]
print(font)
image_path = glob("%s/*.jpg" % args.inputData2)[0]
# coding=utf-8
from __future__ import absolute_import, print_function
import os
from suanpan.app.arguments import Folder, String, Int, Bool
from suanpan.app import app
@app.input(Folder(key="inputData"))
@app.input(Folder(key="alignedDir"))
@app.input(Folder(key="modelDir"))
@app.param(Bool(key="__edit", default=False))
@app.param(
String(
key="modelName",
default="SAE",
help="AVATAR, DF, H64, H128, LIAEF128, SAE, DEV_FANSEG",
))
@app.param(Int(key="forceGpuIdx", default=-1))
@app.param(Bool(key="cpuOnly", default=False))
@app.output(Folder(key="outputData"))
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,
}
# coding=utf-8
from __future__ import absolute_import, print_function
from suanpan.app.arguments import Folder, String, Int
from suanpan.app import app
from mainscripts import VideoEd
from utils import get_all_files
@app.input(Folder(key="inputData"))
@app.param(String(key="fromTime", default="00:00:00.000"))
@app.param(String(key="toTime", default="00:00:01.000"))
@app.param(Int(key="audioTrackId", default=0))
@app.param(Int(key="bitrate", default=25))
@app.output(Folder(key="outputData"))
def SPCutVideo(context):
args = context.args
fileList = get_all_files(args.inputData)
VideoEd.cut_video(
fileList[0],
args.outputData,
args.fromTime,
args.toTime,
args.audioTrackId,
args.bitrate,
)
return args.outputData
# coding=utf-8
from __future__ import absolute_import, print_function
import os
from suanpan.app.arguments import Folder, String, Int, Bool
from suanpan.app import app
from mainscripts import VideoEd
from utils import get_all_files
@app.input(Folder(key="inputData"))
@app.input(Folder(key="referenceFolder"))
@app.param(String(key="fileName", default="media.mp4"))
@app.param(String(key="ext", default="png", help="jpg png"))
@app.param(Int(key="fps", default=25))
@app.param(Int(key="bitrate", default=16))
@app.param(Bool(key="lossless", default=False))
@app.output(Folder(key="outputData"))
def SPVideoFromSequence(context):
args = context.args
if args.referenceFolder:
referenceFile = get_all_files(args.referenceFolder)
VideoEd.video_from_sequence(
args.inputData,
os.path.join(args.outputData, args.fileName),
referenceFile[0],
args.ext,
args.fps,
args.bitrate,
args.lossless,
# coding=utf-8
from __future__ import absolute_import, print_function
from suanpan.app.arguments import Folder, String, Bool
from suanpan.app import app
from mainscripts import Extractor
@app.input(Folder(key="inputData"))
@app.param(
String(
key="faceType",
default="full_face",
help=
"['half_face', 'full_face', 'head', 'full_face_no_align', 'mark_only']",
))
@app.param(String(key="detector", default="s3fd", help="['dlib','mt','s3fd']"))
@app.param(Bool(key="multiGpu", default=False))
@app.param(Bool(key="cpuOnly", default=False))
@app.output(Folder(key="outputData"))
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,
import os
from suanpan.app.arguments import Folder, Int, String, Bool
from suanpan.app import app
from lib import cli
@app.input(Folder(key="inputData1"))
@app.input(Folder(key="alignments1"))
@app.input(Folder(key="inputData2"))
@app.input(Folder(key="alignments2"))
@app.param(Int(key="batchSize", default=4, help="64 (2, 256)"))
@app.param(
String(
key="trainer",
default="original",
help=
"original dfaker dfl-h128 dfl-sae iae lightweight realface unbalanced villain",
))
@app.param(Int(key="iterations", default=10000, help="1000000 (0, 5000000)"))
@app.param(Int(key="__gpu", default=0))
@app.param(Bool(key="allowGrowth", default=False))
@app.param(Bool(key="warpToLandmarks", default=False))
@app.param(Bool(key="noFlip", default=False))
@app.param(Bool(key="noAugmentColor", default=False))
@app.output(Folder(key="outputModel"))
def SPTrain(context):
args = context.args
PARSER = cli.FullHelpArgumentParser()
TRAIN = cli.TrainArgs(
PARSER, "train",
from __future__ import absolute_import, print_function
import os
from suanpan.app.arguments import Folder, String, Int
from suanpan.app import app
from lib import cli
from utils import get_all_files
@app.input(Folder(key="inputData1"))
@app.input(Folder(key="inputData2"))
@app.input(Folder(key="inputModel"))
@app.param(
String(
key="colorAdjustment",
default="avg-color",
help=
"avg-color color-transfer manual-balance match-hist seamless-clone none",
))
@app.param(Int(key="__gpu", default=0))
@app.param(
String(
key="maskType",
default="predicted",
help="components dfl_full extended facehull predicted none",
))
@app.param(String(key="scaling", default="none", help="sharpen none"))
@app.output(Folder(key="outputData"))
def SPConvert(context):
args = context.args
video = get_all_files(args.refVideo)[0] if args.refVideo else args.refVideo
# coding=utf-8
from __future__ import absolute_import, print_function
from suanpan.app.arguments import Folder, String
from suanpan.app import app
from mainscripts import Sorter
@app.input(Folder(key="inputData"))
@app.param(
String(
key="sortByMethod",
default="blur",
help=
'("blur", "face", "face-dissim", "face-yaw", "face-pitch", "hist", "hist-dissim", "brightness", "hue", "black", "origname", "oneface", "final", "final-no-blur", "test")',
))
@app.output(Folder(key="outputData"))
def SPSortLab(context):
args = context.args
Sorter.main(input_path=args.inputData, sort_by_method=args.sortByMethod)
return args.inputData
if __name__ == "__main__":
SPSortLab()
# coding=utf-8
from __future__ import absolute_import, print_function
import os
from suanpan.app.arguments import String
from suanpan.app import app
from suanpan.storage import storage
@app.output(String(key="outputData"))
def SPConvertSync(context):
args = context.args
path = os.path.split(str(args.outputData))[0]
storage.upload(path.replace("/sp_data/", ""), path)
return "Images Saved..."
if __name__ == "__main__":
SPConvertSync()
# coding=utf-8
from __future__ import absolute_import, print_function
from suanpan.app.arguments import Folder, String, Int
from suanpan.app import app
from mainscripts import VideoEd
from utils import get_all_files
@app.input(Folder(key="inputData"))
@app.param(String(key="outputExt", default="png", help="jpg png"))
@app.param(Int(key="fps", default=0))
@app.output(Folder(key="outputData"))
def SPExtractVideo(context):
args = context.args
inputFile = get_all_files(args.inputData)
VideoEd.extract_video(inputFile[0], args.outputData, args.outputExt,
args.fps)
return args.outputData
if __name__ == "__main__":
SPExtractVideo()
