Play with different program settings, try different lighting in the room, a different camera angle. It depends on how much your face fits the shape of the celebrity's face. It depends on how big the face in the frame, as well as the resolution of the model. The public models have a resolution of 224x224 to work on most PC configurations. For high face resolution, you need to train your own model. Public models are suitable for game streamers that have their face in a small window in the corner of the screen. Play with different program settings. Any module put on the CPU will consume a lot of CPU time, which is not enough to run a game, for example. If the motherboard allows, you can install additional video cards and distribute the load on them. depends on final quality of your picture. Flickering face, abruptly clipping face mask, irregular color will increase chance to detect the fake. deepware.ai detects no fakes in the example video of the fake Margot Robbie. No you don't. There are public face models that can swap any face without training. | |
Depends on microsoft/onnxruntime library developers. AMD cards are supported through DirectML execution provider, which is currently raw and slow. | |
I want to have more control when changing faces in a video. Will the new functionality be implemented?No. DeepFaceLive is designed for face swapping in streams. The ability to change faces in the videos - only for test purposes. | |
This is the normal deepfake training process, where src faceset is the celebrity and dst faceset is your faceset. Train the deepfake model as usual with DeepFaceLab, then export the model in .dfm format for use in DeepFaceLive. You can also try ordering a deepfake model from someone in Discord or forum. | |
If you are familiar with DeepFaceLab, then this tutorial will help you: Src faceset is celebrity. Must be diverse enough in yaw, light and shadow conditions. Src faceset should be xseg'ed and applied. You can apply Generic XSeg to src faceset. Dst faceset is RTM WF faceset from the torrent. Make a backup before every stage !
res:224, WF, ae_dims:256, e_dims:64, d_dims:64, d_mask_dims 22, eyes_mouth_prio:Y, batch more is better. Others are default. Assuming 1kk iters with batch 8. If the batch is higher, iters is possible less.
You can reuse this model to train new src faceset. In this case you must delete the file inter_AB.npy from the model folder, and train from stage 3.
-- coming soon -- |