def __init__(self, root_dir,shape_data,img_transofrm=None,label_transform=None,nameImageFile="images",nameMasksFile="masks"):
self.shape_data=shape_data
self.root_dir=root_dir
self.img_transofrm = img_transofrm
self.label_transform = label_transform
self.nameImageFile=nameImageFile
self.nameMasksFile=nameMasksFile
self.files = list()
self.files=os.listdir(self.root_dir)
####Augmentation###
self.TrChannels=trs.TransformColorChannels()
self.TrFlip=trs.TransformFlip()
self.colorJitter=trs.TransformsColorJitter(0.65,0.8,0.8,0.09)
self.TrNoisy=trs.TransformNoisyNormal((128,128,128),(128,128,128),0.98,0.02)
self.TrBlur=trs.TransformBlur(3)
###################
print("Found files: ",len(self.files))
def __init__ (self,rootData,shapeData,imgTransforms=None, labelTransforms=None):
self.rootData=rootData
self.shapeData=shapeData
self.imgTransforms=imgTransforms
self.labelTransforms=labelTransforms
self.filesDataset=list()
####Augmentation###
self.TrChannels=trs.TransformColorChannels()
self.TrFlip=trs.TransformFlip()
self.colorJitter=trs.TransformsColorJitter(0.65,0.8,0.8,0.09)
self.TrNoisy=trs.TransformNoisyNormal((128,128,128),(128,128,128),0.9,0.1)
self.TrBlur=trs.TransformBlur(5)
###################
rootFiles1=os.listdir(rootData)
for fileName in rootFiles1:
cropped_train=os.path.join(rootData,fileName,"cropped_train")
instrument_datasets=os.listdir(cropped_train)
for instrument_dataset in instrument_datasets:
imagesPath=os.path.join(cropped_train,instrument_dataset,"images")
masksPath=os.path.join(cropped_train,instrument_dataset,"binary_masks")
images=os.listdir(imagesPath)
masks=os.listdir(masksPath)
lenImgs=len(images)
lenMasks=len(masks)
if lenImgs!=lenMasks:
strError = "error of the dimension of the list of images (" + str(lenIms) + ") and masks (" + str(lenMsks) + ")"
raise IOError(strError)
for i in range(lenImgs):
img_file = os.path.join(imagesPath,images[i])
msk_file = os.path.join(masksPath,masks[i])
self.filesDataset.append({
"image":img_file,
"label":msk_file
})
