def imgTranslation(oriImg: str,
oriLabel: str,
flag=True,
labelFile='',
factor=0.5):
"""
image translation
factor : Translation factor
"""
if isinstance(oriImg, str):
if os.path.exists(oriImg):
img = io.imread(oriImg)
else:
raise FileNotFoundError('Original image not found')
elif isinstance(oriImg, np.ndarray):
img = oriImg
else:
logger.error('input {} type error'.format(imgFlip))
return
imgShape = img.shape
if isinstance(oriLabel, str):
if os.path.exists(labelFile):
mask = processorWithLabel(oriLabel, labelFile, flag=True)
else:
mask = processor(oriLabel, flag=True)
elif isinstance(oriLabel, np.ndarray):
mask = oriLabel
else:
raise TypeError(
"input parameter 'oriLabel' type {} is not supported".format(
type(oriLabel)))
trans_h = random.randint(0, int(factor * imgShape[1]))
trans_v = random.randint(0, int(factor * imgShape[0]))
trans_mat = np.float32([[1, 0, trans_h], [0, 1, trans_v]])
transImg = cv2.warpAffine(img, trans_mat, (imgShape[1], imgShape[0]))
transMask = cv2.warpAffine(mask, trans_mat, (imgShape[1], imgShape[0]))
if flag:
parent_path = os.path.dirname(oriLabel)
if os.path.exists(parent_path + os.sep + 'jsons_'):
pass
else:
os.makedirs(parent_path + os.sep + 'jsons_')
fileName = oriLabel.split(os.sep)[-1].replace('.json', '')
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_translation.jpg', transImg)
transMask_j = getMultiShapes(parent_path + os.sep + 'jsons_' + os.sep +
fileName + '_translation.jpg',
transMask,
flag=True,
labelYamlPath='')
saveJsonPath = parent_path + os.sep + 'jsons_' + os.sep + fileName + '_translation.json'
if transMask_j is not None:
with open(saveJsonPath, 'w') as f:
f.write(transMask_j)
else:
pass
else:
d = dict()
d['trans'] = Ori_Pro(transImg, transMask)
return d
def script():
arguments = docopt(__doc__)
if arguments.get('--version') or arguments.get('-v'):
print(__version__)
elif arguments.get('m2j'):
logger.info("Masks to jsons")
print("<==== please input origin image path ====>")
inputOriimgPath = input()
print("<==== please input mask path ====>")
inputMaskPath = input()
if not os.path.exists(inputMaskPath):
raise FileNotFoundError('mask folder is not exist')
savePath = inputMaskPath
print("<==== please input yaml path (can be blank,better dont) ====>")
inputYamlPath = input()
getJsons(inputOriimgPath,inputMaskPath,savePath,inputYamlPath)
print("Done!")
elif arguments.get('m2x'):
logger.info("Masks to xmls")
print("<==== please input origin image path ====>")
inputOriimgPath = input()
print("<==== please input mask path ====>")
inputMaskPath = input()
if not os.path.exists(inputMaskPath):
raise FileNotFoundError('mask folder is not exist')
savePath = inputMaskPath
getXmls(inputOriimgPath,inputMaskPath,savePath)
print("Done!")
elif arguments.get('j2m'):
logger.info("Jsons to masks")
print("<==== please input json files path ====>")
inputJsonPath = input()
processor(inputJsonPath)
print('Done!')
elif arguments.get('j2x'):
logger.info("Json to xml (single file supported if version<=0.3)")
print("<==== please input json file path ====>")
inputJsonPath = input()
j2xConvert(inputJsonPath)
print('Done!')
elif arguments.get('aug'):
# logger.info("Image augmentation (single file supported if version<=0.3)")
if not arguments.get('--nolabel'):
print("<==== please input image file path ====>")
inputFilePath = input()
print("<==== please input json file path ====>")
inputJsonPath = input()
imgAug_withLabels(inputFilePath,inputJsonPath)
else:
print("<==== please input image file path ====>")
inputFilePath = input()
imgAug_withoutLabels(inputFilePath)
def imgRotation(oriImg: str,
oriLabel: str,
angle=30,
scale=1,
flag=True,
labelFile=''):
"""
旋转
"""
logger.warning(
'rotation may cause salt-and-pepper noise. in order to solve this issue, small objects may be missing!'
)
if isinstance(oriImg, str):
if os.path.exists(oriImg):
img = io.imread(oriImg)
else:
raise FileNotFoundError('Original image not found')
elif isinstance(oriImg, np.ndarray):
img = oriImg
else:
logger.error('input {} type error'.format(imgFlip))
return
imgShape = img.shape
if isinstance(oriLabel, str):
if os.path.exists(labelFile):
mask = processorWithLabel(oriLabel, labelFile, flag=True)
else:
mask = processor(oriLabel, flag=True)
elif isinstance(oriLabel, np.ndarray):
mask = oriLabel
else:
raise TypeError(
"input parameter 'oriLabel' type {} is not supported".format(
type(oriLabel)))
center = (0.5 * imgShape[1], 0.5 * imgShape[0])
mat = cv2.getRotationMatrix2D(center, angle, scale)
affedImg = cv2.warpAffine(img, mat, (imgShape[1], imgShape[0]))
affedMask = cv2.warpAffine(mask, mat, (imgShape[1], imgShape[0]))
if flag:
parent_path = os.path.dirname(oriLabel)
if os.path.exists(parent_path + os.sep + 'jsons_'):
pass
else:
os.makedirs(parent_path + os.sep + 'jsons_')
fileName = oriLabel.split(os.sep)[-1].replace('.json', '')
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_rotation.jpg', affedImg)
affedMask_j = getMultiShapes(parent_path + os.sep + 'jsons_' + os.sep +
fileName + '_rotation.jpg',
affedMask,
flag=True,
labelYamlPath='')
saveJsonPath = parent_path + os.sep + 'jsons_' + os.sep + fileName + '_rotation.json'
if affedMask_j is not None:
with open(saveJsonPath, 'w') as f:
f.write(affedMask_j)
else:
pass
else:
d = dict()
d['rotation'] = Ori_Pro(affedImg, affedMask)
return d
def imgNoise(oriImg: str, oriLabel: str, flag=True, labelFile=''):
"""
see skimage.util.random_noise
"""
noise_type = ['gaussian', 'poisson', 's&p', 'speckle']
l = np.random.randint(2, size=len(noise_type)).tolist()
# print(l)
p = list(zip(noise_type, l))
if isinstance(oriImg, str):
if os.path.exists(oriImg):
img = io.imread(oriImg)
else:
raise FileNotFoundError('Original image not found')
elif isinstance(oriImg, np.ndarray):
img = oriImg
else:
logger.error('input type error')
return
for i in p:
if i[1] != 0:
img = snoise.random_noise(img, mode=i[0])
img = np.array(img * 255).astype(np.uint8)
if flag:
# parent_path = os.path.dirname(oriImg)
(parent_path, file_path) = os.path.split(oriImg)
if os.path.exists(parent_path + os.sep + 'jsons_'):
pass
else:
os.makedirs(parent_path + os.sep + 'jsons_')
# fileName = oriImg.split(os.sep)[-1].replace('.json', '')
fileName = os.path.splitext(file_path)[0]
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName + '_noise.jpg',
img)
try:
if isinstance(oriLabel, str):
shutil.copyfile(
oriLabel, parent_path + os.sep + 'jsons_' + os.sep +
fileName + '_noise.json')
base64code = imgEncode(parent_path + os.sep + 'jsons_' +
os.sep + fileName + '_noise.jpg')
with open(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_noise.json', 'r') as f:
load_dict = json.load(f)
load_dict['imageData'] = base64code
with open(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_noise.json', 'w') as f:
# json.dump(load_dict,parent_path+os.sep+'jsons_'+os.sep+fileName+'_noise.json')
f.write(json.dumps(load_dict))
elif isinstance(oriLabel, np.ndarray):
"""
labeled file can be an Image
"""
noisedMask_j = getMultiShapes(parent_path + os.sep + 'jsons_' +
os.sep + fileName + '_noise.jpg',
oriLabel,
flag=True,
labelYamlPath=labelFile)
with open(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_noise.json', 'w') as f:
f.write(json.dumps(noisedMask_j))
except Exception:
print(traceback.format_exc())
else:
d = dict()
# mask = processor(oriLabel,flag=True)
if isinstance(oriLabel, str):
if os.path.exists(labelFile):
mask = processorWithLabel(oriLabel, labelFile, flag=True)
else:
mask = processor(oriLabel, flag=True)
elif isinstance(oriLabel, np.ndarray):
mask = oriLabel
else:
raise TypeError(
"input parameter 'oriLabel' type {} is not supported".format(
type(oriLabel)))
# print('======================')
# print(np.max(mask))
# print('======================')
d['noise'] = Ori_Pro(img, mask)
return d
def imgFlip(oriImg: str,
oriLabel: str,
flip_list=[1, 0, -1],
flag=True,
labelFile=''):
"""
flipList: flip type. see cv2.flip :
1: 水平翻转 \n
0: 垂直翻转 \n
-1: 同时翻转 \n
>>> import cv2
>>> help(cv2.flip)
"""
if isinstance(oriImg, str):
if os.path.exists(oriImg):
img = io.imread(oriImg)
else:
raise FileNotFoundError('Original image not found')
elif isinstance(oriImg, np.ndarray):
img = oriImg
else:
logger.error('input {} type error'.format(imgFlip))
return
try:
if len(flip_list) > 1 and (1 in flip_list or 0 in flip_list
or -1 in flip_list):
if isinstance(oriLabel, str):
if os.path.exists(labelFile):
mask = processorWithLabel(oriLabel, labelFile, flag=True)
else:
mask = processor(oriLabel, flag=True)
elif isinstance(oriLabel, np.ndarray):
mask = oriLabel
else:
raise TypeError(
"input parameter 'oriLabel' type is not supported")
# print(type(mask))
h_ori = cv2.flip(img, 1)
v_ori = cv2.flip(img, 0)
h_v_ori = cv2.flip(img, -1)
h_mask = cv2.flip(mask, 1) if 1 in flip_list else None
v_mask = cv2.flip(mask, 0) if 0 in flip_list else None
h_v_mask = cv2.flip(mask, -1) if -1 in flip_list else None
"""
maybe dict or zip is better :)
"""
if flag:
parent_path = os.path.dirname(oriLabel)
if os.path.exists(parent_path + os.sep + 'jsons_'):
pass
else:
os.makedirs(parent_path + os.sep + 'jsons_')
fileName = oriLabel.split(os.sep)[-1].replace('.json', '')
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_h.jpg', h_ori) if 1 in flip_list else do_nothing()
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_v.jpg', v_ori) if 0 in flip_list else do_nothing()
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_h_v.jpg', h_v_ori) if -1 in flip_list else do_nothing()
h_j = getMultiShapes(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_h.jpg',
h_mask,
flag=True,
labelYamlPath='') if h_mask is not None else None
# h_j = getMultiShapes(parent_path+os.sep+'jsons_'+os.sep+fileName+'_h.jpg',h_mask,flag=True,labelYamlPath='D:\\testALg\\mask2json\\mask2json\\multi_objs_json\\info.yaml')
v_j = getMultiShapes(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_v.jpg',
v_mask,
flag=True,
labelYamlPath='') if v_mask is not None else None
h_v_j = getMultiShapes(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_h_v.jpg',
h_v_mask,
flag=True,
labelYamlPath='') if h_v_mask is not None else None
for saveJsonPath in [
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_h.json', parent_path + os.sep + 'jsons_' + os.sep +
fileName + '_v.json', parent_path + os.sep + 'jsons_' +
os.sep + fileName + '_H_V.json'
]:
# if saveJsonPath is not None:
# print(saveJsonPath)
if saveJsonPath.endswith('_h.json'):
if h_j is not None:
with open(saveJsonPath, 'w') as f:
f.write(h_j)
else:
pass
elif saveJsonPath.endswith('_v.json'):
if v_j is not None:
with open(saveJsonPath, 'w') as f:
f.write(v_j)
else:
pass
elif saveJsonPath.endswith('_H_V.json'):
if h_v_j is not None:
with open(saveJsonPath, 'w') as f:
f.write(h_v_j)
else:
pass
rmQ.rm(saveJsonPath) if os.path.exists(
saveJsonPath) else do_nothing()
return ""
else:
d = dict()
d['h'] = Ori_Pro(h_ori, h_mask)
d['v'] = Ori_Pro(v_ori, v_mask)
d['h_v'] = Ori_Pro(h_v_ori, h_v_mask)
return d
else:
logger.warning("<===== param:flip_list is not valid =====>")
except Exception:
# print(e)
print(traceback.format_exc())
def imgZoom(oriImg: str,
oriLabel: str,
size: float = 0,
flag=True,
labelFile=''):
"""
size : The zoom factor along the axes, default 0.8~1.8
"""
# pass
if isinstance(oriImg, str):
if os.path.exists(oriImg):
img = io.imread(oriImg)
else:
raise FileNotFoundError('Original image not found')
elif isinstance(oriImg, np.ndarray):
img = oriImg
else:
logger.error('input {} type {} error'.format('oriImg', type(oriImg)))
return
try:
size = float(size)
# if size == 0.0:
# raise ValueError('zoom factor cannot be zero')
except:
logger.warning('input {} type error ,got {}.'.format(
'size', type(size)))
size = random.uniform(0.8, 1.8)
size = round(size, 2)
if size <= 0 or size == 1:
size = random.uniform(0.8, 1.8)
size = round(size, 2)
resOri = _getZoomedImg(img, size)
if isinstance(oriLabel, str):
if os.path.exists(labelFile):
# print(True)
mask = processorWithLabel(oriLabel, labelFile, flag=True)
else:
mask = processor(oriLabel, flag=True)
elif isinstance(oriLabel, np.ndarray):
mask = oriLabel
else:
raise TypeError(
"input parameter 'oriLabel' type {} is not supported".format(
type(oriLabel)))
maskImgs = _splitImg(mask)
# print('========='+str(len(maskImgs)))
resMask = np.zeros((resOri.shape[0], resOri.shape[1]))
if len(maskImgs) > 0:
for m in maskImgs:
# print(np.max(m.img))
res = _getZoomedImg(m.img, size)
res[res > 0] = m.clasId
res[res != m.clasId] = 0
resMask += res
# io.imsave('D:\\testALg\\mask2json\\mask2json\\static\\jsons_\\{}.png'.format(np.max(m.img)),resMask*255)
resMask = resMask.astype(np.uint8)
# io.imsave('D:\\testALg\\mask2json\\mask2json\\static\\jsons_\\12.png',resMask*255)
# print(np.max(resMask))
if np.max(resMask) == 0:
logger.warning(
'After zoom,none ROIs detected! Zoomfactor={} maybe too large.'.
format(size))
# return
if flag:
parent_path = os.path.dirname(oriLabel)
if os.path.exists(parent_path + os.sep + 'jsons_'):
pass
else:
os.makedirs(parent_path + os.sep + 'jsons_')
fileName = oriLabel.split(os.sep)[-1].replace('.json', '')
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName + '_zoom.jpg',
resOri)
zoomedMask_j = getMultiShapes(parent_path + os.sep + 'jsons_' +
os.sep + fileName + '_zoom.jpg',
resMask,
flag=True,
labelYamlPath=labelFile)
saveJsonPath = parent_path + os.sep + 'jsons_' + os.sep + fileName + '_zoom.json'
if zoomedMask_j is not None:
with open(saveJsonPath, 'w') as f:
f.write(zoomedMask_j)
logger.info('Done! See {} .'.format(
saveJsonPath)) if LOGFlag == 'True' else entity.do_nothing()
else:
pass
else:
d = dict()
# print(resOri.shape)
# io.imsave('D:\\testALg\\mask2json\\mask2json\\static\\jsons_\\13.png',resMask*255)
d['zoom'] = Ori_Pro(resOri, resMask)
return d
def script():
"""
eg. argList = [('-l', '--labels', 'label files path','store_true')]
"""
argList = [
('-n', '--nolabel', 'image augmentation without labels'),
('-H', '--HELP',
'show specific help informaton about supported method'),
('-X', '--labelImg',
'image augmentation for labelImg, default labelme. "X" for xml'),
# ('--number', 'image augmentation numbers, default 1'),
{
'shortName': '-N',
'fullName': '--number',
'type': int,
'help': 'image augmentation numbers, default 1'
},
('-L', '--nolog', 'remove "annoying" logs'),
{
'shortName':
'-c',
'fullName':
'--classfilepath',
'type':
str,
'help':
'class-information-path(for labelme is a *.yaml file,for labelImg is a *.txt file. without this file, this script has some errors when generate mask files and image augumentation.)'
}
]
p = Parser(argList, __appname__)
parser = p.get_parser()
args = vars(parser.parse_args())
# print(args)
if args['version']:
# print(1)
from convertmask import __version__
print(__version__)
del __version__
return
if not args['method'] and not args['version']:
parser.print_help()
return
if args['method'] and not args['input'] and not args['HELP']:
logger.error('<=== INPUT FOLDER/FILE MUST NOT BE NULL ===>')
return
if args['nolog']:
ccfg.setConfigParam(ccfg.cfp, 'log', 'show', 'False')
if args['method'] not in __support_methods__ and args[
'method'] not in supported_simplified_methods:
# print(args['method'])
kvs = getKV(__support_methods_simplified__)
logger.warning(' only ==>{} are supported'.format('\n==>'.join(kvs)))
lis = difflib.get_close_matches(args['method'], __support_methods__)
# print(lis)
if len(lis) > 0:
logger.info('do you mean: {} ?'.format(' OR '.join(lis)))
del lis
return
if args['method'] == 'mask2json' or args[
'method'] == __support_methods_simplified__['mask2json']:
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(
' origin-image-path(necessary), mask-image-path(necessary), yaml-file-path(can be blank,better dont)'
)
print(
' origin images are used to generate base64 code. mask images are used to generate polygons. yaml file saves classes information'
)
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 2:
raise MethodInputException('Not enough input parameters')
elif len(params) == 2:
inputOriimgPath = params[0]
inputMaskPath = params[1]
savePath = os.path.dirname(inputMaskPath)
inputYamlPath = ''
elif len(params) == 3:
inputOriimgPath = params[0]
inputMaskPath = params[1]
savePath = os.path.dirname(inputMaskPath)
inputYamlPath = params[2]
else:
raise MethodInputException('Too much input parameters')
getJsons(inputOriimgPath, inputMaskPath, savePath, inputYamlPath)
print('Done!')
if args['method'] == 'mask2xml' or args[
'method'] == __support_methods_simplified__['mask2xml']:
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(
' origin-image-path(necessary), mask-image-path(necessary)')
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 2:
raise MethodInputException('Not enough input parameters')
elif len(params) == 2:
inputOriimgPath = params[0]
inputMaskPath = params[1]
savePath = os.path.dirname(inputMaskPath)
else:
raise MethodInputException('Too much input parameters')
getXmls(inputOriimgPath, inputMaskPath, savePath)
print('Done!')
if args['method'] == 'json2xml' or args[
'method'] == __support_methods_simplified__['json2xml']:
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(' json-file-path(necessary)')
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 1:
raise MethodInputException('Not enough input parameters')
elif len(params) == 1:
inputJsonPath = params[0]
else:
raise MethodInputException('Too much input parameters')
j2xConvert(inputJsonPath)
print('Done!')
if args['method'] == 'json2mask' or args[
'method'] == __support_methods_simplified__['json2mask']:
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(' json-file-path(necessary)')
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 1:
raise MethodInputException('Not enough input parameters')
elif len(params) == 1:
inputJsonPath = params[0]
else:
raise MethodInputException('Too much input parameters')
processor(inputJsonPath)
print('Done!')
if args['method'] == 'augmentation' or args[
'method'] == __support_methods_simplified__['augmentation']:
if not args['number']:
number = 1
else:
number = args['number']
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(
' origin-image-path(necessary), label-file-path(alternative).'
)
print(' --nolabel can be added to just augment images.')
print(
' --labelImg can be added to augment xmls, default jsons.')
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if args['classfilepath']:
classFilePath = args['classfilepath']
else:
classFilePath = ''
if len(params) < 1:
raise MethodInputException('Not enough input parameters')
elif len(params) == 1 and args['nolabel']:
inputFilePath = params[0]
imgAug_withoutLabels(inputFilePath, number)
print('Done!')
elif len(params) == 2:
inputFilePath = params[0]
inputJsonPath = params[1]
if not args['labelImg']:
imgAug_withLabels(inputFilePath,
inputJsonPath,
number,
yamlFilePath=classFilePath)
else:
imgAug_LabelImg(inputFilePath, inputJsonPath, number)
print('Done!')
else:
raise MethodInputException('There must be some errors.')
if args['method'] == 'xml2json' or args[
'method'] == __support_methods_simplified__['xml2json']:
logger.info('<=== This is a test function. ===>')
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(' xml-file-path(necessary), origin-image-path(necessary)')
print(' currently, only single file conversion supported.')
print(
' --labelImg can be added which means xmls are generated by labelImg.'
)
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 2:
raise MethodInputException('Not enough input parameters')
elif len(params) == 2:
inputFilePath = params[0]
inputJsonPath = params[1]
if not args['labelImg']:
x2jConvert(inputFilePath, inputJsonPath)
else:
x2jConvert_pascal(inputFilePath, inputJsonPath)
print('Done!')
else:
raise MethodInputException('Too much input parameters')
if args['method'] == 'yolo2xml' or args[
'method'] == __support_methods_simplified__['yolo2xml']:
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(
' txt-file-path(necessary), origin-image-path(necessary), class-file-path(necessary'
)
print(' currently, only single file conversion supported.')
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 3:
raise MethodInputException('Not enough input parameters')
elif len(params) == 3:
txtpath = params[0]
imgpath = params[1]
labelPath = params[2]
else:
raise MethodInputException('Too much input parameters')
y2xConvert(txtPath=txtpath, imgPath=imgpath, labelPath=labelPath)
print('Done!')
if args['method'] == 'xml2yolo' or args[
'method'] == __support_methods_simplified__['xml2yolo']:
if args['HELP']:
print('\n')
print("<==== {} detailed information ====>".format(args['method']))
print('\n')
print('This method parameter list should follow this order.')
print(' xml-file-path(necessary), class-file-path(alternative)')
print(
' class-file is a txt file saves class information. without this file, a txt file will be generated automaticly, which may be in different orders'
)
print('\n')
print('<==== The End ====>')
print('\n')
else:
params = args['input']
if len(params) < 1:
raise MethodInputException('Not enough input parameters')
elif len(params) == 1:
xmlpath = params[0]
x2yConvert(xmlpath)
print('Done!')
elif len(params) == 2:
xmlpath = params[0]
labelpath = params[1]
x2yConvert(xmlpath, labelpath)
print('Done!')
else:
raise MethodInputException('Too much input parameters')