github/DeepFaceLive
1
0
Fork 0
mirror of https://github.com/iperov/DeepFaceLive synced 2025-08-20 13:33:25 -07:00
Code Issues Projects Releases Packages Wiki Activity Actions

added 1-day-3090 training instruction

Browse source
This commit is contained in:
iperov 2022-09-04 20:40:46 +04:00
commit 60552a85db
1 changed files with 24 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

24
doc/user_faq/user_faq.md
View file

@ -156,6 +156,30 @@ Models that are trained before random_warp:OFF, can be reused. In this case you
</td></tr>
<tr><td colspan=2 align="left">
## Is there any way to train a model faster?
You can train a model in 1 day on RTX 3090, sacrificing quality.
> 1-day-3090 training. Using pretrained "RTT model 224 V2.zip" from public storage (see above)
1. place RTM WF Faceset V2 from public storage (see above) to workspace/data_dst/aligned
2. place your celeb to workspace/data_src/aligned
3. place model folder to workspace/model
4. do not change settings, train +25.000 iters
5. delete inter_AB.npy (save, delete, continue run)
6. train +30.000 iters
7. random_warp OFF, GAN 0.1 power, patch size 28, gan_dims:32.
8. Turn off after 24 hours
</td></tr>
<tr><td colspan=2 align="left">
## I want to change some code and test the result on my local machine. What I need to do?
There is ready-to-use VSCode editor inside DeepFaceLive folder located in