是否有1张图像深度学习方法的多图像？ （pix2pix？）
我正在尝试建立视频稳定深度学习模型。
我想使模型预测框架应如何稳定，具体取决于
我尝试过的 pix2pix 的最后10帧，这是图像的图像，但我没有得到很好的结果
因此，我想要与pix2pix相同的，但多图像到1图像 有没有方法，还是可以使用Pix2Pix进行操作？
I'm trying to build a video stabilization deep learning model.
I want to make the model predict how the frame should be stabilized depending on the last 10 frames
I have tried pix2pix, which is image to image, but I didn't get a good result
so, I want the same as pix2pix but multi images to 1 image
is there a method or can I do it using pix2pix?
如果你对这篇内容有疑问，欢迎到本站社区发帖提问 参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱，如果其他用户或者作者回复了您的评论，将不能在第一时间通知您！
发布评论
评论（1）
因此，我不知道您是否真的需要使用深度学习来构建此视频稳定，或者您是否只想在现场解决方案上进行稳定。
对于“固定解决方案”，您可以查看具有内置的令人敬畏的稳定系统的Vidgear： https://abhitronix.github.io/vidgear/latest/gears/gears/stabiliers/stabilizer/overview/
如果您想要更高级的解决方案和架构，则可以看一下他的线程用代码： https://paperswithcode.com/task/task/task/video-stabilization
给予当前PIX2PIX的体系结构，我看不出多图像将如何提供一些稳定化，因为正如您所说，Pix2Pix不考虑其先前的输出，也不考虑图像流以生成其预测。
我希望它有帮助^^
So, I do not know if you actually need to build this video stabilization using deep learning or if you just want on off-the-shelves solution.
For the on-the-shelves solution, you can look into vidgear that has an awesome stabilisation system built-in: https://abhitronix.github.io/vidgear/latest/gears/stabilizer/overview/
If you want a more advanced solution and architecture, you could take a look at his thread of paper with code: https://paperswithcode.com/task/video-stabilization
Given the current architecture of pix2pix, I do not see how multi-images will provide some stabilisation since, it is just as you said, pix2pix does not consider its previous output nor the flow of images to generate its prediction.
I hope that it helps ^^