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If the datasets have no miss mask and all mask, then how I should deal with miss mask and all mask? #4

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xiangweifeng opened this issue Sep 18, 2017 · 2 comments

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@xiangweifeng
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Let them all '1'?

@michalfaber
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miss mask and all mask are required only for training - I work on that

@Marcovaldong
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I want to transfer this model to a new dataset which has 14 keypoints for one person, I need to train the model on the new dataset, so how I should deal with miss mask and all mask

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3 participants