PyTorch module to use OpenFace's nn4.small2.v1.t7 model

Related tags

Deep Learning pytorch openface
Overview

OpenFace for Pytorch

  • Disclaimer: This codes require the input face-images that are aligned and cropped in the same way of the original OpenFace. *

I made a dirty code to use OpenFace in PyTorch. I converted 'nn4.small2.v1.t7' to a .hdf5 file using 'torch-hdf5'. Then I read layer informations from .hdf5 file, which can be displayed as follows:

nn.Sequential {
  [input -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> (7) -> (8) -> (9) -> (10) -> (11) -> (12) -> (13) -> (14) -> (15) -> (16) -> (17) -> (18) -> (19) -> (20) -> (21) -> (22) -> (23) -> (24) -> (25) -> (26) -> output]
  (1): nn.SpatialConvolutionMM(3 -> 64, 7x7, 2,2, 3,3)
  (2): nn.SpatialBatchNormalization (4D) (64)
  (3): nn.ReLU
  (4): nn.SpatialMaxPooling(3x3, 2,2, 1,1)
  (5): nn.SpatialCrossMapLRN
...

Then I manually coded layers in PyTorch (see loadOpenFace.py) with some tentative layers code which may be supported by PyTorch officially laters (SpatialCrossMapLRN_temp.py, adopted from PyTorch's nn.legacy). The final model is 'openface.pth' (which may need to be renamed to 'openface_nn4_small2_v1.pth'), which can be loaded by codes in loadOpenFace.py.

Please see main section of loadOpenFace.py for how-to-use. Simply,

net = prepareOpenFace(useCuda=True, gpuDevice=0, useMultiGPU=False).eval()
feature = net(input_tensor)    # input_tensor should be (batch_size, 3, 96, 96)
  • License
    This is released under Apache 2.0 license.
Comments
  • Is input size (batchseize,3,96,96) right?

    Is input size (batchseize,3,96,96) right?

    When I'm trying outputs_128, outputs_726 = face_net(imgs_tensor) (imgs_tensor is [3,3,96,96]) , I got an error : ValueError: Expected more than 1 value per channel when training, got input size [1, 96, 1, 1]. can you solve that?

    opened by CXMANDTXW 2
  • AttributeError: 'tuple' object has no attribute 'size'

    AttributeError: 'tuple' object has no attribute 'size'

    I see that f is a tuple, consisting of (x, x_736), the result of the forward() method in the netOpenFace class. I am getting AttributeError: 'tuple' object has no attribute 'size' when I run your code as is.

    Is this expected?

    The following code is from the last few lines in loadOpenFace.py.

    for i in range(f.size(0) - 1):
        for j in range(i + 1, f.size(0)):
            df = f[i] - f[j]
            print(img_paths[i].split('/')[-1], img_paths[j].split('/')[-1], torch.dot(df, df))
    opened by surfertas 2
  • How to run your codes with multiple GPU?

    How to run your codes with multiple GPU?

    Hi, thnkim!

    I'm using your codes to fine tune our face recognition network in pytorch, it works well when using single GPU (gpuDevice=0), I want to know how to run it with multiple GPU?

    thanks!

    opened by bluer555 1
  • How about 'openface_server.lua'

    How about 'openface_server.lua'

    Hello, thnkim! The code of openface for pytorch is help me. I am trying to run it but didn't work at last step, it's the problem of the file of 'openface_server.lua'.I'm not family with Torch and appreciate you can transform this file to pytorch !

    opened by Jacktofine 1
  • Question: which pth-model is the recommended?

    Question: which pth-model is the recommended?

    As the subject says: you provide openface.pth and openface_20180119.pth where the first one is referenced in your source code while the second one is newer.

    Which model is the recommended one and yields best results?

    Thanks in advance.

    opened by domcross 0
  • Lenon with glasses is closer to clapton with glasses than to lennon without glasses.

    Lenon with glasses is closer to clapton with glasses than to lennon without glasses.

    Thanks for the code. I have learned a lot.

    But when I run the example I got that lennon with glasses was closer to clapton with glasses than to lennon without glasses. I think this is completely wrong.

    I get the same exact resulto with both: openface_20180119.pth and openface.pth

    Thanks.

    opened by educob 0
  • bbox detection and face align

    bbox detection and face align

    Hey, I'm new to face detection. It seems the codes replace the network part of the torch version openface. But the face box detection and face align API in openface is not contained. Is there easy way to do that without install the torch version openface？

    opened by zhangyuygss 0
Owner
Pete Tae-hoon Kim
Deeping Source Inc.
Pete Tae-hoon Kim
GitHub
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