def zoom_img(src, zoomfactor):
oriImgShape = src.shape
w = oriImgShape[1] # width
h = oriImgShape[0] # height
resW = int(w * zoomfactor)
resH = int(h * zoomfactor)
zoomImg = cv2.resize(src, (resW, resH), cv2.INTER_AREA)
zoomImgShape = zoomImg.shape
if zoomfactor > 1:
vDis = zoomImgShape[0] - oriImgShape[0]
hDis = zoomImgShape[1] - oriImgShape[1]
vDisHalf = int(vDis * 0.5)
hDisHalf = int(hDis * 0.5)
res = zoomImg[vDisHalf:zoomImgShape[0] + vDisHalf - vDis,
hDisHalf:zoomImgShape[1] + hDisHalf - hDis]
elif zoomfactor < 1:
vDis = abs(zoomImgShape[0] - oriImgShape[0])
hDis = abs(zoomImgShape[1] - oriImgShape[1])
vDisHalf = int(vDis * 0.5)
hDisHalf = int(hDis * 0.5)
res = cv2.copyMakeBorder(
zoomImg,
vDisHalf,
vDis - vDisHalf,
hDisHalf,
hDis - hDisHalf,
cv2.BORDER_CONSTANT,
)
else:
logger.warning('zoomfactor is 1')
res = src
return res
def imgAug_LabelImg(imgPath, xmlpath, number=1):
"""
number : file number you want to generate.
"""
logger.info("currently, only *.jpg supported")
oriImgs = glob.glob(imgPath + os.sep +
'*.jpg') if os.path.isdir(imgPath) else [imgPath]
xmlFiles = glob.glob(xmlpath + os.sep +
'*.xml') if os.path.isdir(xmlpath) else [xmlpath]
if type(number) != int:
logger.error('Augumentation times error.Using 1 as default')
number = 1
else:
if number < 1:
logger.warning(
'Augumentation times {} is less than 1.Using 1 as default'.
format(number))
number = 1
pool = Pool(__CPUS__ - 1)
pool_list = []
for i in oriImgs:
for num in tqdm(range(0, number)):
resultspool = pool.apply_async(proc_xml,
(i, imgPath, xmlpath, num))
pool_list.append(resultspool)
logger.info('successfully create {} tasks'.format(len(pool_list)))
for pr in tqdm(pool_list):
re_list = pr.get()
def convertImgSplit(oriImg: str,
mask_or_xml: str,
labelpath='',
yamlPath: str = '',
bias=2000):
imgName = oriImg.split(os.sep)[-1][:-4]
logger.warning("there is a issue related to Image Binarization")
# logger.warning("this version is not convenient.it convert mask to json first because i \n have no idea how to modify getMultiShapes.py(getMultiObjs_voc)")
if mask_or_xml.endswith('xml'):
_, maskPath = x2m.x2mConvert(mask_or_xml, labelpath, yamlPath)
maskImg = io.imread(maskPath)
else:
maskImg = mask_or_xml
splitMaskImgList = splitImg_dengbili(reshape_dengbili(maskImg),
bias=bias,
savefile=False)
splitMaskOriList = splitImg_dengbili(reshape_dengbili(io.imread(oriImg)),
bias=bias,
savefile=False)
for i in range(0, len(splitMaskImgList)):
tmpPath = save_ori_dir + os.sep + imgName + '_{}.jpg'.format(i)
io.imsave(tmpPath, splitMaskOriList[i])
getMultiObjs_voc_withYaml(tmpPath,
splitMaskImgList[i],
yamlPath=yamlPath)
def getJsons(imgPath, maskPath, savePath, yamlPath=''):
"""
imgPath: origin image path \n
maskPath : mask image path \n
savePath : json file save path \n
>>> getJsons(path-to-your-imgs,path-to-your-maskimgs,path-to-your-jsonfiles)
"""
logger.info("currently, only *.jpg supported")
if os.path.isfile(imgPath):
getMultiShapes.getMultiShapes(imgPath, maskPath, savePath, yamlPath)
elif os.path.isdir(imgPath):
oriImgs = glob.glob(imgPath + os.sep + '*.jpg')
maskImgs = glob.glob(maskPath + os.sep + '*.jpg')
for i in tqdm(oriImgs):
i_mask = i.replace(imgPath, maskPath)
if os.path.exists(i_mask):
# print(i)
getMultiShapes.getMultiShapes(i, i_mask, savePath, yamlPath)
else:
logger.warning('corresponding mask image not found!')
continue
else:
logger.error(
'input error. got [{},{},{},{}]. file maybe missing.'.format(
imgPath, maskPath, savePath, yamlPath))
logger.info('Done! See here. {}'.format(savePath))
def imgAug_withLabels(imgPath, labelPath, number=1, yamlFilePath=''):
"""
number : file number you want to generate.
"""
logger.info("currently, only *.jpg supported")
oriImgs = glob.glob(imgPath + os.sep +
'*.jpg') if os.path.isdir(imgPath) else [imgPath]
jsonFiles = glob.glob(labelPath + os.sep +
'*.json') if os.path.isdir(labelPath) else [
labelPath
]
if type(number) != int:
logger.error('Augumentation times error.Using 1 as default')
number = 1
else:
if number < 1:
logger.warning(
'Augumentation times {} is less than 1.Using 1 as default'.
format(number))
number = 1
for num in range(0, number):
for i in tqdm(oriImgs):
i_json = i.replace(
imgPath, labelPath) if os.path.isdir(labelPath) else labelPath
i_json = i_json.replace('.jpg', '.json')
imgAug.aug_labelme(i, i_json, num=num, yamlFilePath=yamlFilePath)
def get_parser(self):
self.parser.add_argument(
'method',
metavar='PROCESS_METHOD',
type=str,
nargs='?',
help='the method to be processed. currently, {} are supported.'.
format(','.join(__support_methods__)))
self.parser.add_argument('-v',
'--version',
help='show current version',
action='store_true')
self.parser.add_argument('-i',
'--input',
type=str,
nargs='*',
help='input files')
if len(self.args) > 0:
for i in self.args:
self.add_parser(i)
else:
logger.warning('args list is null')
return self.parser
def getMultiObjs_voc(oriImgPath, labelPath, savePath):
# pass
labelImg = io.imread(labelPath)
# print(labelImg.shape)
(_, fileName) = os.path.split(labelPath)
# print(fileName)
# fileName = labelPath.split(os.sep)[-1]
imgShape = labelImg.shape
imgHeight = imgShape[0]
imgWidth = imgShape[1]
imgPath = oriImgPath
logger.warning("auto detecting class numbers")
if len(imgShape) == 3:
labelImg = labelImg[:, :, 0]
labelImg[labelImg > 0] = 255
_, labels, stats, centroids = cv2.connectedComponentsWithStats(
labelImg.astype(np.uint8))
statsShape = stats.shape
objs = []
for i in range(1, statsShape[0]):
st = stats[i, :]
width = st[2]
height = st[3]
xmin = st[0]
ymin = st[1]
xmax = xmin + width
ymax = ymin + height
ob = {}
ob['name'] = 'class{}'.format(i)
ob['difficult'] = 0
# ob['name'] = 'weld'
bndbox = {}
bndbox['xmin'] = xmin
bndbox['ymin'] = ymin
bndbox['xmax'] = xmax
bndbox['ymax'] = ymax
ob['bndbox'] = bndbox
objs.append(ob)
saveXmlPath = savePath + os.sep + fileName[:-4] + '.xml'
img2xml_multiobj(saveXmlPath, saveXmlPath, "TEST", fileName, imgPath,
imgWidth, imgHeight, objs)
def imgZoom(oriImg, size, flag=True):
"""
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'))
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 flag:
parent_path = os.path.dirname(oriImg)
if os.path.exists(parent_path + os.sep + 'augimgs_'):
pass
else:
os.makedirs(parent_path + os.sep + 'augimgs_')
tmp = os.path.splitext(oriImg)[0]
fileName = tmp.split(os.sep)[-1]
io.imsave(
parent_path + os.sep + 'augimgs_' + os.sep + fileName +
'_zoom.jpg', resOri)
else:
d = dict()
d['zoom'] = Ori_Pro(resOri, None)
return d
def __init__(self,
img,
heightFactor: float = 0.5,
widthFactor: float = 0.5,
getXmls: bool = False,
xmls: list = [],
savePath: str = ''):
logger.warning(
'This script is not suitable for single image augumentation.')
self.img = img
self.heightFactor = heightFactor
self.widthFactor = widthFactor
self.getXmls = getXmls
self.xmls = xmls
self.savePath = savePath
def imgAug_withoutLabels(imgPath, number=1):
logger.info("currently, only *.jpg supported")
oriImgs = glob.glob(imgPath + os.sep +
'*.jpg') if os.path.isdir(imgPath) else [imgPath]
if type(number) != int:
logger.error('Augumentation times error.Using 1 as default')
number = 1
else:
if number < 1:
logger.warning(
'Augumentation times {} is less than 1.Using 1 as default'.
format(number))
number = 1
for num in range(0, number):
for i in tqdm(oriImgs):
imgAug_nolabel.aug(i, num=num)
def getXmls(imgPath, maskPath, savePath):
logger.info("currently, only *.jpg supported")
if os.path.isfile(imgPath):
getMultiShapes.getMultiObjs_voc(imgPath, maskPath, savePath)
elif os.path.isdir(imgPath):
oriImgs = glob.glob(imgPath + os.sep + '*.jpg')
maskImgs = glob.glob(maskPath + os.sep + '*.jpg')
for i in tqdm(oriImgs):
i_mask = i.replace(imgPath, maskPath)
# print(i)
if os.path.exists(i_mask):
getMultiShapes.getMultiObjs_voc(i, i_mask, savePath)
else:
logger.warning('corresponding mask image not found!')
continue
else:
logger.error('input error. got [{},{},{}]. file maybe missing.'.format(
imgPath, maskPath, savePath))
logger.info('Done! See here. {}'.format(savePath))
def x2yConvert(xmlpath, labelPath=''):
labels = readLabels(labelPath)
parent_path = os.path.dirname(xmlpath)
if not os.path.exists(xmlpath):
raise FileNotFoundError('file not found')
else:
if os.path.isfile(xmlpath):
# pass
logger.info('single file found')
labels = readXmlSaveTxt(xmlpath, parent_path, labels)
if len(labels) > 0:
logger.warning('generate label file automaticly')
with open(parent_path + os.sep + 'labels_.txt', 'w') as f:
for i in labels:
f.write(i + '\n')
print('Done!')
print("see here {}".format(parent_path))
else:
xmls = glob.glob(xmlpath + os.sep + "*.xml")
if not os.path.exists(parent_path + os.sep + 'txts_'):
os.mkdir(parent_path + os.sep + 'txts_')
logger.info('exists {} xml files'.format(len(xmls)))
for xml in tqdm(xmls):
labels = readXmlSaveTxt(xml, parent_path + os.sep + 'txts_',
labels)
if len(labels) > 0:
logger.warning('generate label file automaticly')
with open(
parent_path + os.sep + 'txts_' + os.sep +
'labels_.txt', 'w') as f:
for i in labels:
f.write(i + '\n')
logger.info('Done!')
logger.info("see here {}".format(parent_path + os.sep + 'txts_'))
def writeXml(imgname, objlist, savepath, folder, name,oriImgPath=''):
# imgname = lines[start].split('/')[-1]
xmlname = imgname.replace('.jpg', '.xml').replace('\n', '')
tmpPath = savepath + xmlname
path = imgname
if oriImgPath == '':
logger.warning('Origin image needed!')
width = 0
height = 0
else:
oriImg = io.imread(oriImgPath+os.sep+imgname)
width = oriImg.shape[1]
height = oriImg.shape[0]
del oriImg
objs = []
# objlist = lines[start + 2:end]
for ob in objlist:
# print(ob)
if len(ob) > 20:
tmp = ob.split(' ')
xmin = tmp[0]
ymin = tmp[1]
w = tmp[2]
h = tmp[3]
xmax = int(xmin) + int(w)
ymax = int(ymin) + int(h)
obj = dict()
obj['name'] = name
obj['diffcult'] = 0
bndbox = dict()
bndbox['xmin'] = xmin
bndbox['ymin'] = ymin
bndbox['xmax'] = xmax
bndbox['ymax'] = ymax
obj['bndbox'] = bndbox
objs.append(obj)
img2xml_multiobj(tmpPath, tmpPath, folder, imgname, path, width, height,
objs)
def aug_labelimg(filepath, xmlpath, augs=None, num=0, labelpath=''):
default_augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
if augs is None:
augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
# elif not isinstance(augs,list):
else:
if not isinstance(augs, list):
try:
augs = list(str(augs))
except:
raise ValueError(
"parameter:aug's type is wrong. expect a string or list,got {}"
.format(str(type(augs))))
# else:
augs = list(set(augs).intersection(set(default_augs)))
if len(augs) > 0 and augs is not None:
pass
else:
logger.warning(
'augumentation method is not supported.using default augumentation method.'
)
augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
# l = np.random.randint(2,size=len(augs)).tolist()
if 'flip' in augs:
augs.remove('flip')
augs.append('flip')
l = np.random.randint(2, size=len(augs))
if np.sum(l) == 0:
l[0] = 1
l[l != 1] = 1
l = l.tolist()
# print(l)
p = list(zip(augs, l))
img = filepath
# processedImg = xmlpath
jsonpath = x2jConvert_pascal(xmlpath, filepath)
# processedImg = processorWithLabel(jsonpath, labelpath, flag=True)
if os.path.exists(labelpath):
processedImg = processorWithLabel(jsonpath, labelpath, flag=True)
else:
processedImg = jsonpath
# os.remove(jsonpath)
for i in p:
if i[1] == 1:
if i[0] == 'noise':
n = imgNoise(img, processedImg, flag=False)
tmp = n['noise']
img, processedImg = tmp.oriImg, tmp.processedImg
del n, tmp
if i[0] == 'rotation':
angle = random.randint(-10, 10)
r = imgRotation(img, processedImg, flag=False, angle=angle)
tmp = r['rotation']
img, processedImg = tmp.oriImg, tmp.processedImg
del r, tmp
elif i[0] == 'trans':
t = imgTranslation(img, processedImg, flag=False, factor=0.1)
tmp = t['trans']
img, processedImg = tmp.oriImg, tmp.processedImg
del t, tmp
elif i[0] == 'zoom':
zoomFactor = random.uniform(0.8, 1.8)
z = imgZoom(img, processedImg, zoomFactor, flag=False)
tmp = z['zoom']
img, processedImg = tmp.oriImg, tmp.processedImg
del z, tmp
elif i[0] == 'flip':
imgList = []
processedImgList = []
f = imgFlip(img, processedImg, flag=False)
tmp = f['h_v']
imgList.append(tmp.oriImg)
processedImgList.append(tmp.processedImg)
tmp = f['h']
imgList.append(tmp.oriImg)
processedImgList.append(tmp.processedImg)
tmp = f['v']
imgList.append(tmp.oriImg)
processedImgList.append(tmp.processedImg)
img, processedImg = imgList, processedImgList
del tmp, f, imgList, processedImgList
parent_path = os.path.dirname(filepath)
if os.path.exists(parent_path + os.sep + 'xmls_'):
pass
else:
os.makedirs(parent_path + os.sep + 'xmls_')
# fileName = jsonpath.split(os.sep)[-1].replace(".json", '')
(_, fileName) = os.path.split(jsonpath)
fileName = fileName.replace(".json", '')
if isinstance(img, np.ndarray):
io.imsave(
parent_path + os.sep + 'xmls_' + os.sep + fileName +
'_{}_assumble.jpg'.format(num), img)
assumbleJson = getMultiShapes(parent_path + os.sep + 'xmls_' + os.sep +
fileName +
'_{}_assumble.jpg'.format(num),
processedImg,
flag=True,
labelYamlPath=labelpath)
saveJsonPath = parent_path + os.sep + 'xmls_' + os.sep + fileName + '_{}_assumble.json'.format(
num)
with open(saveJsonPath, 'w') as f:
f.write(assumbleJson)
j2xConvert(saveJsonPath)
# os.remove(saveJsonPath)
print("Done!")
print("see here {}".format(parent_path + os.sep + 'xmls_'))
# print("see here {}".format(saveJsonPath))
elif isinstance(img, list):
for i in range(0, len(img)):
io.imsave(
parent_path + os.sep + 'xmls_' + os.sep + fileName +
'_{}_assumble{}.jpg'.format(num, i), img[i])
assumbleJson = getMultiShapes(parent_path + os.sep + 'xmls_' +
os.sep + fileName +
'_{}_assumble{}.jpg'.format(num, i),
processedImg[i],
flag=True,
labelYamlPath=labelpath)
saveJsonPath = parent_path + os.sep + 'xmls_' + os.sep + fileName + '_{}_assumble{}.json'.format(
num, i)
with open(saveJsonPath, 'w') as f:
f.write(assumbleJson)
j2xConvert(saveJsonPath)
os.remove(saveJsonPath)
print("Done!")
print("see here {}".format(parent_path + os.sep + 'xmls_'))
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 aug_labelimg(filepath, xmlpath, augs=None, num=0):
default_augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
if augs is None:
augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
else:
if not isinstance(augs, list):
try:
augs = list(str(augs))
except:
raise ValueError(
"parameter:aug's type is wrong. expect a string or list,got {}"
.format(str(type(augs))))
augs = list(set(augs).intersection(set(default_augs)))
if len(augs) > 0 and augs is not None:
pass
else:
logger.warning(
'augumentation method is not supported.using default augumentation method.'
)
augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
if 'flip' in augs:
augs.remove('flip')
augs.append('flip')
l = np.random.randint(2, size=len(augs))
if np.sum(l) == 0:
l[0] = 1
# l[l != 1] = 1 ## For test
l = l.tolist()
p = list(zip(augs, l))
parent_path, file_name = os.path.split(filepath)
filename, ext = os.path.splitext(file_name)
if not os.path.exists(parent_path + os.sep + 'tmps_'):
os.mkdir(parent_path + os.sep + 'tmps_')
if not os.path.exists(parent_path + os.sep + 'augxmls_'):
os.mkdir(parent_path + os.sep + 'augxmls_')
labelPath = parent_path + os.sep + 'tmps_' + os.sep + filename + '_tmps.xml'
shutil.copyfile(xmlpath, labelPath)
img = io.imread(filepath)
for i in p:
if i[1] == 1:
# if i[0] == 'test':
# pass
if i[0] == 'rotation':
angle = random.randint(-10, 10)
r = rotate(img, labelPath, angle)
img, labelPath = r.oriImg, r.processedImg
del r
elif i[0] == 'trans':
t = translation(img, labelPath)
img, labelPath = t.oriImg, t.processedImg
del t
elif i[0] == 'zoom':
z = zoom(img, labelPath)
img, labelPath = z.oriImg, z.processedImg
del z
elif i[0] == 'noise':
n = noise(img, labelPath)
img, labelPath = n.oriImg, n.processedImg
del n
elif i[0] == 'flip':
f = flip(img, labelPath)
# img,labelPath =
img = []
labelPath = []
for i in f:
img.append(i.oriImg)
labelPath.append(i.processedImg)
del f
if not isinstance(img, list):
resXmlPath = parent_path + os.sep + 'augxmls_' + os.sep + filename + '_assumbel.xml'
resImgPath = parent_path + os.sep + 'augxmls_' + os.sep + filename + '_assumbel.jpg'
tree = ET.parse(labelPath)
root = tree.getroot()
root.find('folder').text = str(resImgPath.split(os.sep)[-1] if \
resImgPath.split(os.sep)[-1] != "" else resImgPath.split(os.sep)[-2] )
root.find('filename').text = filename + '_assumbel.jpg'
root.find('path').text = resImgPath
tree.write(resXmlPath)
io.imsave(resImgPath, img)
else:
for i in range(0, len(img)):
resXmlPath = parent_path + os.sep + 'augxmls_' + os.sep + filename + '_assumbel_{}.xml'.format(
i)
resImgPath = parent_path + os.sep + 'augxmls_' + os.sep + filename + '_assumbel_{}.jpg'.format(
i)
tree = ET.parse(labelPath[i])
root = tree.getroot()
root.find('folder').text = str(resImgPath.split(os.sep)[-1] if \
resImgPath.split(os.sep)[-1] != "" else resImgPath.split(os.sep)[-2] )
root.find(
'filename').text = filename + '_assumbel_{}.jpg'.format(i)
root.find('path').text = resImgPath
tree.write(resXmlPath)
io.imsave(resImgPath, img[i])
logger.info('Done! See {}.'.format(parent_path + os.sep + 'augxmls_'))
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())
sys.path.append('..')
from docopt import docopt
from convertmask import __version__, baseDecorate
from convertmask.utils.backup.cpFile import fileExist
from convertmask.utils.imgAug_script import (imgAug_withLabels,
imgAug_withoutLabels)
from convertmask.utils.json2mask.convert import processor
from convertmask.utils.json2xml.json2xml import j2xConvert
from convertmask.utils.mask2json_script import getJsons, getXmls
from convertmask.utils.methods.logger import logger
if not fileExist():
logger.warning("connot find draw.py in labelme folder,which may cause some errors on labelme 4.2.9 (and maybe later). You can add it follow this step:https://github.com/guchengxi1994/mask2json#how-to-use")
class MethodNotSupportException(Exception):
pass
@baseDecorate()
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 ====>")
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 aug_labelme(filepath, jsonpath, augs=None, num=0, yamlFilePath=''):
"""
augs: ['flip','noise','affine','rotate','...']
"""
default_augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
if augs is None:
augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
# elif not isinstance(augs,list):
else:
if not isinstance(augs, list):
try:
augs = list(str(augs))
except:
raise ValueError(
"parameter:aug's type is wrong. expect a string or list,got {}"
.format(str(type(augs))))
# else:
augs = list(set(augs).intersection(set(default_augs)))
if len(augs) > 0 and augs is not None:
pass
else:
logger.warning(
'augumentation method is not supported.using default augumentation method.'
)
augs = ['noise', 'rotation', 'trans', 'flip', 'zoom']
# l = np.random.randint(2,size=len(augs)).tolist()
if 'flip' in augs:
augs.remove('flip')
augs.append('flip')
l = np.random.randint(2, size=len(augs))
if np.sum(l) == 0:
l[0] = 1
l[l != 1] = 1
l = l.tolist()
# l = [0, 0, 0, 1, 0] # for test
p = list(zip(augs, l))
img = filepath
# processedImg = jsonpath
if os.path.exists(yamlFilePath):
processedImg = processorWithLabel(jsonpath, yamlFilePath, flag=True)
else:
processedImg = jsonpath
# print("======================={}".format(np.max(processedImg)))
for i in p:
# if i[0]!='flip':
if i[1] == 1:
if i[0] == 'noise':
n = imgNoise(img,
processedImg,
flag=False,
labelFile=yamlFilePath)
tmp = n['noise']
img, processedImg = tmp.oriImg, tmp.processedImg
del n, tmp
elif i[0] == 'rotation':
angle = random.randint(-45, 45)
r = imgRotation(img,
processedImg,
flag=False,
angle=angle,
labelFile=yamlFilePath)
tmp = r['rotation']
img, processedImg = tmp.oriImg, tmp.processedImg
del r, tmp
elif i[0] == 'trans':
t = imgTranslation(img,
processedImg,
flag=False,
labelFile=yamlFilePath)
tmp = t['trans']
img, processedImg = tmp.oriImg, tmp.processedImg
del t, tmp
elif i[0] == 'zoom':
zoomFactor = random.uniform(0.8, 1.8)
# print("==========2============={}".format(np.max(processedImg)))
z = imgZoom(img,
processedImg,
zoomFactor,
flag=False,
labelFile='')
# print(type(z))
tmp = z['zoom']
img, processedImg = tmp.oriImg, tmp.processedImg
del z, tmp
elif i[0] == 'flip':
imgList = []
processedImgList = []
f = imgFlip(img,
processedImg,
flag=False,
labelFile=yamlFilePath)
tmp = f['h_v']
imgList.append(tmp.oriImg)
processedImgList.append(tmp.processedImg)
tmp = f['h']
imgList.append(tmp.oriImg)
processedImgList.append(tmp.processedImg)
tmp = f['v']
imgList.append(tmp.oriImg)
processedImgList.append(tmp.processedImg)
img, processedImg = imgList, processedImgList
del tmp, f, imgList, processedImgList
parent_path = os.path.dirname(filepath)
if os.path.exists(parent_path + os.sep + 'jsons_'):
pass
else:
os.makedirs(parent_path + os.sep + 'jsons_')
# fileName = jsonpath.split(os.sep)[-1].replace(".json", '')
(_, fileName) = os.path.split(jsonpath)
fileName = fileName.replace(".json", '')
# io.imsave('D:\\testALg\\mask2json\\mask2json\\static\\jsons_\\12.png',processedImg*255)
if isinstance(img, np.ndarray):
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_{}_assumble.jpg'.format(num), img)
assumbleJson = getMultiShapes(parent_path + os.sep + 'jsons_' +
os.sep + fileName +
'_{}_assumble.jpg'.format(num),
processedImg,
flag=True,
labelYamlPath=yamlFilePath)
saveJsonPath = parent_path + os.sep + 'jsons_' + os.sep + fileName + '_{}_assumble.json'.format(
num)
with open(saveJsonPath, 'w') as f:
f.write(assumbleJson)
print("Done!")
print("see here {}".format(parent_path + os.sep + 'jsons_'))
elif isinstance(img, list):
for i in range(0, len(img)):
io.imsave(
parent_path + os.sep + 'jsons_' + os.sep + fileName +
'_{}_assumble{}.jpg'.format(num, i), img[i])
assumbleJson = getMultiShapes(parent_path + os.sep + 'jsons_' +
os.sep + fileName +
'_{}_assumble{}.jpg'.format(num, i),
processedImg[i],
flag=True,
labelYamlPath=yamlFilePath)
saveJsonPath = parent_path + os.sep + 'jsons_' + os.sep + fileName + '_{}_assumble{}.json'.format(
num, i)
with open(saveJsonPath, 'w') as f:
f.write(assumbleJson)
print("Done!")
print("see here {}".format(parent_path + os.sep + 'jsons_'))
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')
