Comments (7)
Hi,
I could push update to allow non square input size. There are no pretrained weights for it, so you'll have to train from scratch.
But in your particular case - I'm not sure if this kind of resolution will work with Edge TPU. I gave it a quick try and compiler failed to create a model.
from coral-deeplab.
Sure, I will do experiments
Maybe 800x800 is good solution Than I will divide picture into 2 parts
from coral-deeplab.
I had closer look at this and it seems like edgetpu_compiler
is not particularly happy about non square inputs for this model (regardless of shape). Since I want to be sure that people using pretrained and finetuned keras model have no problem compiling it to the device, check for square inputs will not be removed.
from coral-deeplab.
Got it. It is very interesting why...
from coral-deeplab.
Dear @xadrianzetx I noticed before that deeplab recognize some objects better when input is larger. Could you advice how to change from 513x513 to 800x800?
from coral-deeplab.
You can create new instance of keras model with input shape you want like so:
import coral_deeplab as cdl
model = cdl.applications.CoralDeepLabV3(input_shape=(800, 800, 3))
As I said earlier, there are no pretrained weights for this shape, so you have to train this model yourself. I think you can use scripts you posted in other issue to do so.
from coral-deeplab.
FYI: 800x800 trainubg with Nvidia 1080Ti failed, I have switched to try train 512x512
from coral-deeplab.
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from coral-deeplab.