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Keypoint regression example #221

Merged
merged 7 commits into from
Apr 27, 2022
Merged

Keypoint regression example #221

merged 7 commits into from
Apr 27, 2022

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itan1
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@itan1 itan1 commented Apr 27, 2022

Running these steps in my REPL worked but only gave me the following problem

  • the FastAI.decodeypred(task, Training(), y) check does not have the same coordinates as the original keypoint k

Running it in a local notebook gives me the following problems

  • The first image plotted with DataAugmentation.showitems looks like this
    Screenshot 2022-04-27 at 09 27 02
  • The kernel dies every time I try to run showbatch(task, (xs, ys))

Can someone try to reproduce this? I'm not sure whether these are environments problems (running with julia 1.7.2 and the mac M1 arm architecture is not fully supported yet).

@lorenzoh
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Thanks for taking a look at this!

The first image plotted with DataAugmentation.showitems looks like this

I think this should be solved by a an using ImageShow import

the FastAI.decodeypred(task, Training(), y) check does not have the same coordinates as the original keypoint k

It does not give the same keypoint since the image is cropped to 128x128. Important part is that the decoded keypoint is within those bounds 👍

The kernel dies every time I try to run showbatch(task, (xs, ys))

Cannot reproduce this, may be a problem with Makie.jl on ARM :/ . Have you tried updating packages in your environment?

@lorenzoh
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Changes look good to me, merging!

@lorenzoh lorenzoh merged commit dfc4df7 into FluxML:master Apr 27, 2022
@itan1 itan1 deleted the keypoint-regression-example branch April 27, 2022 09:59
@itan1
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itan1 commented Apr 27, 2022

Great thank you too! This package is helping me a lot 🙌

the FastAI.decodeypred(task, Training(), y) check does not have the same coordinates as the original keypoint k

It does not give the same keypoint since the image is cropped to 128x128. Important part is that the decoded keypoint is within those bounds 👍

Ok thanks for the clarification, I think I got it. The decode function only reverses the coordinate normalization, not the cropping. Is that correct?

@lorenzoh
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Exactly, since the cropping is a destructive operation

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2 participants