Generation AU Problem about ganimation HOT 11 CLOSED

@shliang0603 adding -aus to your command line. For linux platform, my command line is:
./FaceLandmarkImg -fdir path_to_images -out_dir path_for_generated_files -aus

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I think it is FaceLandmarkImg rather than FeatureExtraction that you should use.

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@XiangyuWu You are right. BTW, is there something wrong with the content[2:19] in prepare_au_annotations.py? why not content[1:18]?

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@xiaoiker I don't know how does your question come. In my csv file, content[0] is face, content[1] is confidence, and form content[2] to content[18] is exactly the value of action unit.

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@XiangyuWu Sorry, my fault. Thanks very much for pointing out.

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@XiangyuWu Hi，Xiangyu Wu,Can you send me your the command line of generation AU(action unit).
In my file, generation AU is between 679 column and 696 column

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@XiangyuWu Thanks for your answering, I will try again

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Hi Xiangyu, did you find the detected AU results from OpenFace are different from the labels provided in aus_openface.pkl in the sample dataset?

For example, for N_0000000356_00190.jpg, the labels provided by aus_openface.pkl are:
[2.86, 2.27, 1.45, 1.1 , 0. , 0.65, 0.05, 0. , 0.75, 1.65, 0.6 , 0. , 1.86, 0. , 0.62, 0.25, 0. ],
while the detected results from OpenFace are:
[0.48, 0. , 0. , 1.47, 0.23, 0.06, 0. , 0.72, 0.48, 1.36, 0.3 , 0. , 1.76, 0. , 0.44, 0.78, 0. ].

I used the command: ./bin/FaceLandmarkImg -fdir GANimation/sample_dataset/imgs -out_dir GANimation/sample_dataset/features -aus

Thank you very much! @XiangyuWu

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@ilovecv I didn't pay attention to it, and I tested it just now, the same problem happened to me. I don't know why such differences exist.

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@ilovecv Unfortunately, it is really difficult to ensure the same exact numerical results when using different compilers (e.g. see https://stackoverflow.com/questions/16395615/is-there-any-way-to-make-sure-the-floating-point-arithmetic-result-the-same-in-b), the differences will come from compilers optimizing code differently and possibly different versions of libraries used with different optimization settings (e.g. OpenCV)

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Closed for inactivity

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