I have some images which are segmented in several classes.
Instead of having complex zones, all of them are rectangles. So my dataset consists of:
[
image,
GT:[
{
x0:
y0:
x1:
y1:
label:
}
]
I would like to use a pre-trained (on VOC_2012) Deeplab model and train it on my data.
Knowing that the shapes are simple rectangles, am I still obliged to create a png mask for each image, or can I keep the data as is, and then create the mask on the fly ?
Would it be relevant/worth it ? (the dataset is consisting in 500K images, approximating 50GB in total)
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