This service uses faceswap to perform face swapping on videos.
It is part of our third party DNN Model Services.
The service receives 2 videos URL as an input to train the model.
It returns a link (with an UID that can be used to make future requests to keep training/improving the same model).
With this link, users can check the progress of their requests in a dashboard.
The service extracts frames from input videos (A and B) and use these frames to train a face swapping model.
With the trained model, the service converts the video A with a face from video B, generating a new video.
The user must provide the following inputs in order to start the service and get a response:
Inputs:
gRPC method: faceswap.uid: To keep training the same model (optional)video_a: URL to Video A (30 FPS, max size 20Mb).video_b: URL to Video B (30 FPS, max size 20Mb).model_url: URL to a pre-trained model (max: 320Mb, optional).
Note: Each call will train the model with 3000 iterations.
You can use this service from SingularityNET DApp.
You can also call the service from SingularityNET CLI (snet).
Assuming that you have an open channel to this service:
$ snet client call snet deepfakes-faceswap default_group faceswap '{"video_a": "http://snet-models.s3.amazonaws.com/bh/Deepfakes/ben.mp4", "video_b": "http://snet-models.s3.amazonaws.com/bh/Deepfakes/musk.mp4"}'
uid: "http://52.38.111.172:7006/dashboard?uid=c5b28d375b53e6107f05"
Input Video A:
Input Video B:
Response:
Model trained with 100 iterations:
Model trained with 3k iterations:
Model trained with 200k iterations:
