How can I use importKerasNetwork function to Import a pretrained VGGFace Keras network and weights?

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How can I use importKerasNetwork function to Import a pretrained VGGFace Keras network and weights and use it for transfer learning?

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Maria Duarte Rosa
Maria Duarte Rosa el 5 de Jul. de 2019
Hi Ibrahim,
layers = importKerasLayers(modelfile) imports the architecture and weights of Keras models saved as .h5 files. These files have to be generated from Keras.
After importing the layers, these can be modified for transfer learning as described here:
I hope this helps,
Maria
  2 comentarios
Ibrahim Mohammed
Ibrahim Mohammed el 6 de Jul. de 2019
Thanks Maria for the quick response,
I couldn't find the keras version of VGGFace in the official keras library, but I found one on github at this link: https://github.com/rcmalli/keras-vggface. Is there any way to access this model using importKerasLayers function so that I can use it for transfer learning?
Thanks.
Runnan Cao
Runnan Cao el 10 de En. de 2020
Hi lbrahim,
Is there any chance that you could share the vgg-face.h5 files with me?
Many thanks!!!
Runnan

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Más respuestas (1)

Maria Duarte Rosa
Maria Duarte Rosa el 9 de Jul. de 2019
Hi Ibrahim, you first need to install and run the python package as described in the GitHub page to obtain the model (including weights), then save this model as .h5 file. Once you have the model saved in .h5 you can use importKerasLayers to load the model into MATLAB.
  4 comentarios
Alex Zai
Alex Zai el 2 de Dic. de 2020
Hello dears,
i have a few question. I want to use pretrained facenet model in guthub site, in the following link: https://github.com/nyoki-mtl/keras-facenet.
In this link already had trained model (facenet.h5) file. How can i import to Matlab it, please?
I tried to used any suggestion like that : importKerasNetwork, importKerasLayers and downloaded and saved in matlab location, then tried read (h5info). But i can't imported which i wanted that (facenet_keras.h5) to Matlab.
If any suggestion or someone can help me, please...
Thank you very much.

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