StyleGAN2の学習済みモデルは、任意の顔画像を生成する潜在変数を簡単に見つけられます。ということは何か編集したい顔画像があるとき、StyleGAN2を使ってその顔画像を生成する潜在変数を見つけて、その潜在変数を操作すれば画像編集が可能になるはずです。 微调StyleGAN2模型(使用Google Colab) 智障球: 多谢大佬您的指导。我先让它跑着吧,每次保存模型也要8min,10次保存一次也挺好^_^现在最怕的就是它跑的断断续续,不像您那样每个tick时间都差不多。之前长时间跑其他程序也没出现过. 微调StyleGAN2模型(使用Google Colab)

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    程序员欢乐送:StyleGAN2、文言文编程语言、EfficientDet、VIBE、RDSNet、深度梯度泄漏 2019年12月20日 338 °C 4 阅读全文 程序生活

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    It could be the case that your GPU cannot manage the full model (Mask RCNN) with batch sizes like 8 or 16. I would suggest trying with batch size 1 to see if the model can run, then slowly increase to find the point where it breaks. But you can achieve it with Colab Notebook (in my article above). A silly dream of a Pygmalion. Still, it were just animated static images. But I’d love to see such features in an original video. Recently in my timeline popped up series of LipSync footages, done on StyleGAN2 transitions (which are already original videos in my conception).

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