Not work in Windows 10 with "bad marshal data" about gender-age-classification HOT 9 OPEN

I used Keras 2.0.4 and Tensorflow 1.1.0.

I tried to reproduce your problem without success. It seems that the problem might come from Keras itself. The model version doesn't match with the Keras version you use.

Please, try this:

pip install --upgrade tensorflow
pip install --upgrade keras

After, can you post a comment to confirm (or not) that this solution worked fine (in order to help others that might encounter the same problem in the futur) ?

If you like you like this project, feel free to leave a star. (it is my only reward ^^)

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@OValery16
Currently I use following versions. It is latest version. hmm, I will try same versions that you mentioned.

Keras                     2.1.3                     <pip>
tensorflow-gpu            1.5.0                     <pip>

Python version is 3.x?

I gave a star. :)

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I encounter the same problem with windows 7

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I am gonna check that, and I will come back to you (I did all my work on Ubuntu ^^)

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same problem with windows 10

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I upgraded to tensorflow-gpu 1.8.0 on Windows 10 and still am getting this error.

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It work with python 2.7 in ubuntu, it cannot work in python 3.x

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It just a modal to reg face in image, you can use another CNN (dlib, ....) or use open_cv instead of it.

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Sorry for the late reply. I got really busy recently.

Thanks AlexBlack2202 for your comments. I will react with few points:

1. As AlexBlack2202 mentioned it, the project was implemented on Ubuntu with python 2.7. I used Keras 2.0.4 and Tensorflow 1.1.0. I am not quite sure, but it seems that there is a version incompatibility. Please check:
   https://stackoverflow.com/questions/45624414/python-keras-compatibility-between-windows-and-linux

2. In this project we stack two CNN: (1) for the face recognition, (2) for the age/gender identification. For the first part (as AlexBlack2202 mentioned it) you can also us other computer vision library such as OpenCV (OpenCV implementation is based on HOG). However if you want to do face recognition in real time (for example in a video), you cannot use these approaches which would be slow. Instead you can use YOLO model (used in this project), which is much fast.

If you like you like this project, feel free to leave a star. (it is my only reward ^^)

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