urmit.space

> Well, it is possible to run the model on mobile (iOS at least) but needs some optimisation. I was able to get 2 sec per frame on iPhone X...

> Some time ago I [ported this architecture to Tensorflow](https://github.com/lshug/first-order-model-tf). The resultant model is compatible with @AliaksandrSiarohin's checkpoints, and supports Tensorflow Lite. It can be used to generate tf lite...

> > We should check if **Coremltools** are capable to convert your **tflite** model to a native **mlmodel**. @HashedViking we can't convert tflite to mlmodel. right process flow for better...

@lshug, which intermediate model you had used? means your point that your save model directories have an intermediate model which can convert to mlmodel, am I correct?

@HashedViking, I think we should change some layer which is supported by coremltools and onnx. and maybe fps is between 5-12. yes we can use tflite but hope all layer...

Anyone can put the mobile device port model. I get an error in ONNX conversion, in avgpool. I want to convert in coreml. anyone has an idea please do help.

> This is rather complicated, need to write code for frame detection and back Inpainting. yes, it takes more time like 4-5 min to create a face-swapping. but get a...

OK let me try it. in this, we have to first detect the face in the video. divided video in chunks where a face appeared then crop the face portion....

Ok, let me try once. then get to know what challenges are made from my side. will update on this soon.

I get success in this now all things work. here I attach a video. greatee bro!! https://user-images.githubusercontent.com/68328018/105016113-44111180-5a68-11eb-91ce-558f94d9404b.mp4 but two things I want to change. how can make all these things...