Commit graph

12 commits

Author SHA1 Message Date
iperov
33ff0be722 _ 2021-09-29 16:41:43 +04:00
iperov
b256b07e03 fix gaussian_blur 2021-08-20 17:06:11 +04:00
iperov
e52b53f87c AMP fix 2021-05-30 09:24:23 +04:00
iperov
e6e2ee7466 pixel_norm op 2021-05-25 14:26:48 +04:00
iperov
241d1a9c35 leras ops: pixelnorm, total_variation_mse 2020-12-30 14:32:07 +04:00
iperov
b9c9e7cffd fix depth_to_space for tf2.4.0. Removing compute_output_shape in leras, because it uses CPU device, which does not support all ops. 2020-12-11 11:28:33 +04:00
Colombo
0eb7e06ac1 upgrade to tf 2.4.0rc1 2020-11-13 17:00:07 +04:00
Colombo
5a40f537cc . 2020-07-04 07:58:53 +04:00
Colombo
9a540e644c upd leras ops 2020-07-03 19:32:14 +04:00
Colombo
0c2e1c3944 SAEHD:
Maximum resolution is increased to 640.

‘hd’ archi is removed. ‘hd’ was experimental archi created to remove subpixel shake, but ‘lr_dropout’ and ‘disable random warping’ do that better.

‘uhd’ is renamed to ‘-u’
dfuhd and liaeuhd will be automatically renamed to df-u and liae-u in existing models.

Added new experimental archi (key -d) which doubles the resolution using the same computation cost.
It is mean same configs will be x2 faster, or for example you can set 448 resolution and it will train as 224.
Strongly recommended not to train from scratch and use pretrained models.

New archi naming:
'df' keeps more identity-preserved face.
'liae' can fix overly different face shapes.
'-u' increased likeness of the face.
'-d' (experimental) doubling the resolution using the same computation cost
Examples: df, liae, df-d, df-ud, liae-ud, ...

Improved GAN training (GAN_power option).  It was used for dst model, but actually we don’t need it for dst.
Instead, a second src GAN model with x2 smaller patch size was added, so the overall quality for hi-res models should be higher.

Added option ‘Uniform yaw distribution of samples (y/n)’:
	Helps to fix blurry side faces due to small amount of them in the faceset.

Quick96:
	Now based on df-ud archi and 20% faster.

XSeg trainer:
	Improved sample generator.
Now it randomly adds the background from other samples.
Result is reduced chance of random mask noise on the area outside the face.
Now you can specify ‘batch_size’ in range 2-16.

Reduced size of samples with applied XSeg mask. Thus size of packed samples with applied xseg mask is also reduced.
2020-06-19 09:45:55 +04:00
Colombo
4c24f9d41c _ 2020-03-19 13:29:33 +04:00
Colombo
61472cdaf7 global refactoring and fixes,
removed support of extracted(aligned) PNG faces. Use old builds to convert from PNG to JPG.

fanseg model file in facelib/ is renamed
2020-03-13 08:09:00 +04:00