How to train my own dlib_face_recognition_resnet_model_v1.dat

[74981]

How to train my own dlib_face_recognition_resnet_model_v1.dat. Please help and if possible share the python api for the same.

[nicolaerosia]

@davisking I'm also interested if you're willing to release the dataset. In any case, I understand that it involved a lot of work.

[davisking]

You can use the trillion faces or ms celeb datasets. They are already available and very large.

[pdstanley]

Davis, is there a python API for training your own model? Thank you, sir! Dlib is amazing.

[davisking]

No

[shenjackson]

@davisking , I don't know how to train my dlib_face_recognition_resnet_model_v1 model, can you give me some methods!

[davisking]

This example program goes into the details: http://dlib.net/dnn_metric_learning_on_images_ex.cpp.html

[csaftoiu]

@davisking Just to be sure, is that C++ code the one used to train this model? I'd like to transfer learn on my own dataset and want to be sure I'm starting from the right place

[csaftoiu]

Also we’re rhe input images aligned centered cropped etc or just resized to 150x150 with a crop from a face finding model? Also be helpful to know this just in terms of using the base model - I see the sample code that uses it does this so I presume it was trained that way As well

[davisking]

The notes on how this model was trained are in the example program that shows how to use it: http://dlib.net/dnn_face_recognition_ex.cpp.html

[csaftoiu]

Ah thanks for that! Very helpful.

I managed to get it to train a few steps on some images of my own. However I couldn’t load it into a net_type because the saved weights have the affine layers while the net_type has batchnorm layers. Though I see it auto converts from batchnorm to affine when saving, I wasn’t able to get it to auto convert from affine to batchnorm to keep training. So I have been training the anet_type directly.

Is there a way to retrieve the net_type from the saved weights on the repo? Or are part of the batchnorm parameters lost when saving the model meaning I can’t transfer learn it?

On Thu, Oct 31, 2019 at 12:02 AM Davis E. King [email protected] wrote:

The notes on how this model was trained are in the example program that shows how to use it: http://dlib.net/dnn_face_recognition_ex.cpp.html

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[davisking]

Some things are lost when converting from batch norm to affine. Save in batch norm form when doing training.

On Thu, Oct 31, 2019 at 9:17 AM Claudiu [email protected] wrote:

Ah thanks for that! Very helpful.

I managed to get it to train a few steps on some images of my own. However I couldn’t load it into a net_type because the saved weights have the affine layers while the net_type has batchnorm layers. Though I see it auto converts from batchnorm to affine when saving, I wasn’t able to get it to auto convert from affine to batchnorm to keep training. So I have been training the anet_type directly.

Is there a way to retrieve the net_type from the saved weights on the repo? Or are part of the batchnorm parameters lost when saving the model meaning I can’t transfer learn it?

On Thu, Oct 31, 2019 at 12:02 AM Davis E. King [email protected] wrote:

The notes on how this model was trained are in the example program that shows how to use it: http://dlib.net/dnn_face_recognition_ex.cpp.html

— You are receiving this because you commented. Reply to this email directly, view it on GitHub < https://github.com/davisking/dlib-models/issues/11?email_source=notifications&email_token=AAAKQ2OQY3ISUSKPO7BLFTDQRIOC5A5CNFSM4GMJTZUKYY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOECWEUAY#issuecomment-548162051 , or unsubscribe < https://github.com/notifications/unsubscribe-auth/AAAKQ2IQAVDMXCVBUR3ZWQLQRIOC5ANCNFSM4GMJTZUA

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[csaftoiu]

Is there any way to get the batch norm form of the model on the repo? Or is this reserved for secret sauce not for public consumption? :). I understand if it’s the latter.

If it’s not available I suppose we can’t transfer learn it as-is. If we load weights and swap out the affine for a random batch norm it seems that’d lose all the learning in first few steps. Best option seems to be to keep the affine as-is. Let me know what you think.

On Thu, Oct 31, 2019 at 11:52 PM Davis E. King [email protected] wrote:

Some things are lost when converting from batch norm to affine. Save in batch norm form when doing training.

On Thu, Oct 31, 2019 at 9:17 AM Claudiu [email protected] wrote:

Ah thanks for that! Very helpful.

I managed to get it to train a few steps on some images of my own. However I couldn’t load it into a net_type because the saved weights have the affine layers while the net_type has batchnorm layers. Though I see it auto converts from batchnorm to affine when saving, I wasn’t able to get it to auto convert from affine to batchnorm to keep training. So I have been training the anet_type directly.

Is there a way to retrieve the net_type from the saved weights on the repo? Or are part of the batchnorm parameters lost when saving the model meaning I can’t transfer learn it?

On Thu, Oct 31, 2019 at 12:02 AM Davis E. King <[email protected]

wrote:

The notes on how this model was trained are in the example program that shows how to use it: http://dlib.net/dnn_face_recognition_ex.cpp.html

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, or unsubscribe <

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[davisking]

You could copy the layer parameters into a network with batch norm layers and go in and manually fill in the missing batch norm parameters with something reasonable.

[ismailpolas]

Does anyone build the dlib_face_recognition_resnet_model_v1.dat with custom dataset? If Yes, Please share the method. Thanks in Advance.

[davisking]

http://dlib.net/dnn_face_recognition_ex.cpp.html and http://dlib.net/dnn_metric_learning_on_images_ex.cpp.html explain all that.

On Wed, Sep 9, 2020 at 6:06 AM ismailpolas [email protected] wrote:

Does anyone build the dlib_face_recognition_resnet_model_v1.dat with custom dataset? If Yes, Please share the method. Thanks in Advance.

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[aishaandatt]

I tried Loading a custom dataset and successfully made the resnet .dat file but I'm getting this error. ERROR: Unexpected version found while deserializing dlib::input_rgb_image_sized. Please refer to the issue link given below for more detials on this error. https://github.com/davisking/dlib/issues/2598