somethng about the dataset about frontalization HOT 17 OPEN

Hi,
Yes, each subfolder contains one or more profile images of a person, and the target for them is a frontal image of the same person.

And ,how could you make the dataset like 001 001.jpg , i can only make it 001 002 .... 001.jpg
will it influence the result?

Hmmm I am not sure what you mean.

from frontalization.

from frontalization.

i guess i should read the code more carefully . i just want to know whether the sequence of files could influence the result or not？
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Still not sure what you mean by sequence of files. Do you mean the alphanumerical order of file names and subfolder names?

from frontalization.

from frontalization.

@haha1958 I think you may have tried to attach some images (?) to your response, but they did not go through.

What I mean is the following: in your dataset folder, you have images and subfolders (which also contain images). Lets say your images are named 001.jpg, 002.jpg and 137.jpg. Your subfolders are named 001, 137 and 49. (I am only using digits inside these names for simplicity, could be letters as well.) Then the correspondence between frontal images and subfolders with profile images will be the following:
001.jpg - 001
002.jpg - 137
137.jpg - 49

Does that clear it up?

from frontalization.

Thank you very much , I get it !! first image and first subfolder are same people , second image and second subfolder are same people....Is it right? and i show you my result :

from frontalization.

Thank you very much , I get it !! first image and first subfolder are same people , second image and second subfolder are same people....Is it right?

Exactly :)

and i show you my result

Hmm, this is very strange. Looks like either the images and/or subfolders don't get sorted for some reason, or their ordering ends up being different than what was used on my machine. If you are using the same convention as mine for your training dataset ("first image and first subfolder are same people , second image and second subfolder are same people" etc), I would recommend going inside the ExternalInputIterator class in data.py to make sure that self.frontals, self.frontal_indices and self.profiles contain the filenames and the indices that they should (the meanings of these should be clear enough from the code, if not, don't hesitate to ask questions!)

A quick check: what happens if you turn off the shuffling for the training set? Do inputs and "reals" correspond to the same people?

from frontalization.

@haha1958 Could you tell me the pytorch version you using in the project?

from frontalization.

@haha1958 Could you tell me the pytorch version you using in the project?

0.4.1

from frontalization.

Just a comment, seems like your model doesn't work well for unseen data. Or maybe because of distribution of faces(w.r.t. countries and regions) it can severly impact the performance.

from frontalization.

@haha1958 @Laviyy
Hello, did you re-train the network or test the given pre-trained model?
My pytorch version is 0.4.1, but I can't load the given model generator_v0.pt

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@hangon666 I find a picture named test.jpg in my computer , which generated by load re-trained model 'netG_49.pt' . I am not sure which pytorch version i was use, maybe still 0.4.1. but I try load it again use pytorch 1.1.0 today , it caused runtimeerror.

from frontalization.

@haha1958 ，thanks for your reply, if convinient, could you share the re-trained model?

from frontalization.

@hangon666 It hadnot get an excellent result, but you can use it just for test https://pan.baidu.com/s/1OKnZKbL8M5uGhj1qe77CyQ

from frontalization.

hello, thanks you for your work. I am working on this project recently, and i want to know if there any other dataset can instand of CMU dataset? Another question is the re-trained model you shared before have been repired, can you please share it again?

from frontalization.

I get this error

--> 108 self.decode = ops.ImageDecoder(device = 'mixed', output_type = types.RGB)

AttributeError: module 'nvidia.dali.ops' has no attribute 'nvJPEGDecoder'

any help? please

from frontalization.

please i need to run this code @haha1958

from frontalization.