Hello,
I would like to use CNTK for pixelwise classification of images (like SegNet). I haven't found a ready-to-use network architecture in the examples folder to do such a task. I have used AlexNet's model for binary classification of images successfully but I am not sure where to start to make this kind of network evolve to generate a pixelwise output.
Could anyone point me in the right direction ?
Is it a good idea to start from AlexNet for this ?
In case it is relevant, I am currently only doing binary classification, but I would be interested in a solution with also (potentially) supports multi-class.
Also, from what I could understand, to generate the pixelwise output I'll need to feed the ground truth (which I don't have right now) of the same size as my training images in input. Creating the ground truth of 10k+ images is a huge task, is there a way to produce pixelwise output without a pixelwise ground truth as input ?
If the ground truth images are compulsory, for a start I could do some tests using the CamVid or KITTI datasets but I would be happy if I wouldn't have to produce all those ground truth images...
Thanks !
We are preparing examples for pixelwise classification (segmentation), please stay tuned.
@cha-zhang Thanks a lot ! Is there any timeframe, 1 week, 1 month ?
No firm timeframe yet, but definitely longer than 1 week. We need to prepare a few other examples before moving to the segmentation task.
@cha-zhang Any update on this? :)
Not yet. It’s holiday season and everything moves slowly…
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@cha-zhang Can CNTK do pixelwise classification of images like SegNet now? Is there any examples? Thank you )
The key components should have already been there. We are still working on the examples.
An example like SegNet would be cool :)
Any update?
Anything now?
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@cha-zhang Can CNTK do pixelwise classification of images like SegNet now? Is there any examples? Thank you )