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iperov 2021-08-14 08:57:50 +04:00
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@ -36,7 +36,8 @@ This is the normal deepfake training process, where src faceset is the celebrity
If you are familiar with DeepFaceLab, then this tutorial will help you:
Src faceset is celebrity. Must be diverse enough.
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.
@ -44,7 +45,10 @@ Make a backup before every stage !
> Using SAEHD model.
res:224, WF, ae_dims:256, e_dims:64, d_dims:64, d_mask_dims 22, eyes_mouth_prio:Y, batch 8. Others are default.
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.
1) enable pretrain mode. Train to 1kk
2) disable pretrain mode. Train to 1kk
3) lrd:N uniform_yaw:True, color_transfer:lct, train +500..800k
@ -56,12 +60,20 @@ You can reuse this model to train new src faceset. In this case you should to de
> Using AMP model.
res:224, WF, ae_dims:256, inter_dims:1024, e_dims:64, d_dims:64, d_mask_dims:22, morph factor:0.5, batch 8. Others are default.
Do not mix different ages of people in the src dataset, otherwise the model will approximate age and make the celebrity older/younger depending on the input person.
res:224, WF, ae_dims:256, inter_dims:1024, e_dims:64, d_dims:64, d_mask_dims:22, morph factor:0.5, batch more is better. Others by default.
Make a backup before every stage !
Assuming 1kk iters with batch 8. If the batch is higher, iters is possible less.
1) lrd:Y, train src-src for 1kk iters
2) delete inter_dst, lrd:N, color_transfer:lct, train +1kk
3) lrd:Y, train +1kk
4) enable gan 0.1 gan_dims:32, train +100..300k iters
2) delete inter_dst, lrd:N, uniform_yaw:True, color_transfer:lct, train +500..1kk
3) color_transfer:none, lrd:Y, train +500..1kk
4) random_warp:False, train +500..1kk
5) enable gan 0.1 gan_dims:32, train +100..300k iters
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