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GilLevi avatar GilLevi commented on May 24, 2024

Hello @Xu-Yao ,

Thank you for your interest in our work. The accuracy reported is on the test set following the AdienceFaces protocol.

I am not familiar with the ffhq dataset, does it have age labels? what is the accuracy you received?

Gil

from agegenderdeeplearning.

Nomia avatar Nomia commented on May 24, 2024

the accuracy is very low when I convert it to coreml model and test it on Xcode

image

image

as u can see ,the second image is the same image u tested in you demo python notebook

image

from agegenderdeeplearning.

Nomia avatar Nomia commented on May 24, 2024

Here is the convert code

import coremltools

# model
# prototxt
# labels: ['(0, 2)','(4, 6)','(8, 12)','(15, 20)','(25, 32)','(38, 43)','(48, 53)','(60, 100)']
coreml_model = coremltools.converters.caffe.convert(('age_net.caffemodel', 'deploy_age.prototxt'), image_input_names='data', class_labels='age_net_labels.txt')

print(coreml_model)

coreml_model.save('age_net_caffe.mlmodel')

age_net_labels.txt content below:

(0, 2)
(4, 6)
(8, 12)
(15, 20)
(25, 32)
(38, 43)
(48, 53)
(60, 100)

@GilLevi

from agegenderdeeplearning.

Nomia avatar Nomia commented on May 24, 2024

After test on Xcode, I thought it might be the problem of the conversion. so I tried to test it on Colab with python exact the same way as u did in your demo python notebook, but I got this error(issue link), so.....I cannot verify if it's the problem of conversion

from agegenderdeeplearning.

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