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cannot get the output segmentation in the paper with the provided weight file #6

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opnumten opened this issue May 15, 2017 · 6 comments

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@opnumten
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Hi,

with the provided weight file, I cannot get the output images shown in your PLOS paper. The prediction accuracy is pretty low.

Thanks

@vanvalen
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vanvalen commented May 16, 2017 via email

@xinrzhsh24
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Hi, Valen~
I can get the pretty segmentation results using your trained model ( '2016-07-12_nuclei_all_61x61_bn_feature_net_61x61_'). But the model trained by using your code of 'training_template', the result is too bad. I also used your data (nulei_all_6161) and the model bn_feature_net_61*61. I noticed your trained model is 1.9M, while mine is 3.8M. What is the problems?

@hftsai
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hftsai commented Jun 20, 2017

I'm seeing similar..i'm using just the trained network provided and the validation data provided (HeLa)
The Jaccard index and dice index provided in the original jupyter notebook suggest:
Jaccard index is 0.84462 +/- 0.0107597496164
Dice index is 0.914696973088 +/- 0.00655002244584

But when i run it on the docker i pulled
the indexes are only:
Jaccard index is 0.700539 +/- 0.144342
Dice index is 0.814186574197 +/- 0.115389352237b

does anyone know why this would happen?

@vanvalen
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vanvalen commented Jun 21, 2017 via email

@hftsai
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hftsai commented Jun 21, 2017

Hi Dave, Thank you so much for your time! I'm sure it'll be extremely useful for my work if we can take a ride on your platform.

@vanvalen
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vanvalen commented Jun 21, 2017 via email

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