This is the first time I define my own dataset
I want to define a dataset, each entry of which is one image associated with a value.
When I define the dataset, should I define the self.samples as an array of:
one string containing the image disk path, and one floating value
or
the real image RGB value matrix and one floating value
?
When you call the dataset use the following syntax:
train_data=torchvision.datasets.MYDATA('../mydata', train=True, download=True,
transform=torchvision.transforms.Compose([
torchvision.transforms.Resize((h_image, w_image)),
torchvision.transforms.ToTensor()
]))
or
train_data=MYDATA('../mydata', train=True, download=True,
transform=torchvision.transforms.Compose([
torchvision.transforms.Resize((h_image, w_image)),
torchvision.transforms.ToTensor()
]))
What conditions do you need to meet to use the transforms utilities? like: rotate and flip?
Hope I described my question clearly.
Thanks.