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Detecting hornets #10

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klorydryk opened this issue Oct 2, 2018 · 5 comments
Open

Detecting hornets #10

klorydryk opened this issue Oct 2, 2018 · 5 comments

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@klorydryk
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Hi,

I applied this process to an image sequence from a video of hornet attacking my hives. But in the end, nothing is detected in the "predict_example" series:
frelon3304 png
I can give a link to the training files I used:
https://rogerlambda.info/nextcloud/index.php/s/oH7Ck8CGBDojg78
and the test files :
https://rogerlambda.info/nextcloud/index.php/s/KKWZxBeYS8LMGAP

What do you think? Too few hornets in the image (one or 2 visible in the same time) ? Bad background? Too few images (70 and 90) labelled?

Thanks!

@matpalm
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matpalm commented Oct 2, 2018

one thing that i normally do just to make sure things are generally wired ok is to use just a single image as the training and test set. it should be the case that the model gets it perfect; and if it doesn't there is something going on. do you want to give that a go? (a single image should also be the fastest to converge)

i have a run_sample_training_pipeline.sh script that does a real quick sanity check, but i should port that to one that does full convergence on a single image... TODO! :)

@klorydryk
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This way seems to work.
frelon3114 png

@squeakus
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squeakus commented Oct 15, 2018 via email

@matpalm
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matpalm commented Oct 15, 2018

i've also committed 9969ead which includes a --pos-weight flag for weighting the +ve case (a hornet) higher than the negative case (no hornet). i've added this to help with the class imbalance problem (a lot fewer hornets than not). for my bee case --pos-weight 5 really speeds up convergence. you might like to try 5 or 10 even too. cc @squeakus

@klorydryk
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klorydryk commented Oct 16, 2018

New set of images, I hope better to find hornet because of the blue sky. Trying with only one picture :
image
Result of predict with train.py --pos-weight 5:
yt2_65 jpeg

Is it the result I should be waiting for?

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