iperov
b03b147bae
refactoring
2019-03-26 11:09:44 +04:00
iperov
131b2b5c79
after save loss string now shows averaged value since last save
2019-03-25 18:14:04 +04:00
iperov
aa58d9e563
SAE: removed lightweight encoder
2019-03-25 10:05:30 +04:00
iperov
54239f8edf
sae: optimizer mode now can be overrided
2019-03-24 16:25:30 +04:00
iperov
37505d88e3
old SAE model will not work with this update.
...
Fixed bug when SAE can be collapsed during a time.
SAE: removed CA weights and encoder/decoder dims.
added new options:
Encoder dims per channel (21-85 ?:help skip:%d)
More encoder dims help to recognize more facial features, but require more VRAM. You can fine-tune model size to fit your GPU.
Decoder dims per channel (11-85 ?:help skip:%d)
More decoder dims help to get better details, but require more VRAM. You can fine-tune model size to fit your GPU.
Add residual blocks to decoder? (y/n, ?:help skip:n) :
These blocks help to get better details, but require more computing time.
Remove gray border? (y/n, ?:help skip:n) :
Removes gray border of predicted face, but requires more computing resources.
2019-03-24 15:35:02 +04:00
iperov
cbe2ebca7f
SAE: removed random normal initialization
2019-03-23 14:57:30 +04:00
iperov
97008291b8
fix
2019-03-20 14:43:02 +04:00
iperov
6169e6ba8a
fix fanseg
2019-03-20 09:08:42 +04:00
iperov
a3df04999c
removing trailing spaces
2019-03-19 23:53:27 +04:00
iperov
fa4e579b95
fix fanseg
2019-03-19 23:49:41 +04:00
iperov
034ad3cce5
upd fan segmentator
2019-03-19 19:44:14 +04:00
iperov
d71a310fd7
SAE: forgot to remove normalizing from tanh
2019-03-17 13:03:49 +04:00
iperov
1c8845d558
model fansegmentator for developing purposes
2019-03-16 20:57:51 +04:00
iperov
d6a45763a2
SAE: added option "Use CA weights":
...
Initialize network with 'Convolution Aware' weights. This may help to achieve a higher accuracy model, but consumes time at first run.
2019-03-16 12:54:36 +04:00
iperov
5076feb90f
SAE: revert back to sigmoid. Trainings must be restarted.
2019-03-16 09:01:11 +04:00
iperov
8da47fec13
fix ModelBase, nnlib
2019-03-13 20:53:59 +04:00
iperov
3375088669
SAE: optimizer_mode option now cannot be overridden by restart
2019-03-13 20:00:16 +04:00
iperov
a9026ccb67
fix ModelBase, nnlib
2019-03-13 19:50:16 +04:00
iperov
58763756f5
SAE: removed simple_optimizer . Added optimizer mode for tensorflow only (NVIDIA cards), allows to train x2-x3 bigger networks with normal Adam optimizer, consuming VRAM and CPU power.
2019-03-13 11:54:17 +04:00
iperov
3c6775bae7
fix ModelBase.py
2019-03-12 23:22:58 +04:00
iperov
97b6fabaab
change 'epoch' to 'iter',
...
added timestamp prefix to training string
2019-03-12 19:23:52 +04:00
iperov
46ff33bf89
SAE: dssim kernel size now depends on resolution
2019-03-12 09:49:40 +04:00
iperov
fd3b9add2f
SAE: added option "simple optimizer" allows to train bigger networks on same VRAM
...
nnlib: added DFLOptimizer is my own optimizer
2019-03-12 09:32:35 +04:00
iperov
3bad8dd8ec
fix
2019-03-11 21:53:28 +04:00
iperov
ee8dbcbc35
revert back Adam
2019-03-11 21:52:36 +04:00
iperov
e4637336ef
added ability to save optimizers states which work with K.function,
...
added custom Adam that can save 'iterations' param
2019-03-11 18:23:01 +04:00
iperov
714d4f0fca
small fix
2019-03-03 16:42:13 +04:00
iperov
31c2298b5f
Converter: added option for seamless to supress jittering,
...
Lenx,leny region now averaged by grayscale gradients,
now uses all CPU.
SAE: multiscale_decoder option default = False
update readme and manual_ru.pdf
2019-03-03 15:33:52 +04:00
iperov
438213e97c
manual extractor: increased FPS,
...
sort by final : now you can specify target number of images,
converter: fix seamless mask and exception,
huge refactoring
2019-02-28 11:56:31 +04:00
iperov
65752e044b
SAE: added support 64-256 resolution multiple of 16
2019-02-21 20:44:55 +04:00
iperov
a858732b1d
refactoring
2019-02-21 20:06:04 +04:00
iperov
97685ce0ae
added saving model_summary.txt
2019-02-21 19:55:44 +04:00
iperov
f0a20b46d3
SAE: added new archi 'vg'
2019-02-21 17:53:59 +04:00
iperov
72ba6b103c
added support of AMD videocards
...
added Intel's plaidML backend to use OpenCL engine. Check new requirements.
smart choosing of backend in device.py
env var 'force_plaidML' can be choosed to forced using plaidML
all tf functions transferred to pure keras
MTCNN transferred to pure keras, but it works slow on plaidML (forced to CPU in this case)
default batch size for all models and VRAMs now 4, feel free to adjust it on your own
SAE: default style options now ZERO, because there are no best values for all scenes, set them on your own.
SAE: return back option pixel_loss, feel free to enable it on your own.
SAE: added option multiscale_decoder default is true, but you can disable it to get 100% same as H,DF,LIAEF model behaviour.
fix converter output to .png
added linux fork reference to doc/doc_build_and_repository_info.md
2019-02-19 17:33:12 +04:00
iperov
3a9d450281
little fix
2019-02-16 21:14:15 +04:00
iperov
75eb7468ee
ConverterMasked: better lct
2019-02-14 18:43:24 +04:00
iperov
2bd983703e
ConverterMasked: removed default transfercolor,
...
added Apply color transfer to predicted face - modes rct / lct
2019-02-13 16:27:57 +04:00
iperov
535041f7bb
upd
2019-02-12 10:55:41 +04:00
iperov
429e7e6aee
upd nnlib.py
2019-02-12 09:30:38 +04:00
iperov
6c944d8989
upd readme
2019-02-11 21:26:51 +04:00
iperov
4ffb74fb79
upd some help in models
2019-02-11 17:20:13 +04:00
iperov
470fb9287a
SAE: remove rare sample booster. DSSIM->MSE transition now between 5-20k epochs.
2019-02-11 17:18:01 +04:00
iperov
f8e63970d2
H64, H128, DF, LIAEF128: added pixel loss option.
2019-02-11 12:05:54 +04:00
iperov
af3dd59f67
SAE: remove multiscale decoder option, default - true
2019-02-11 10:36:02 +04:00
iperov
854ab11de3
fix bug with samples that were not clipped after tanh-untanh transformations, upd README.md
2019-02-10 10:45:51 +04:00
iperov
51a13c90d1
SAE: you have to restart training,
...
added multiscale decoder as option.
mask now training as not multiscaled
2019-02-09 20:33:26 +04:00
iperov
4d37fd62cd
fix DFLJPG,
...
SAE: added "rare sample booster"
SAE: pixel loss replaced to smooth transition from DSSIM to PixelLoss in 15k epochs by default
2019-02-09 18:53:37 +04:00
iperov
ea7c65c4e5
upd ModelBase.py
2019-02-07 22:38:31 +04:00
iperov
a65b557b0e
loss history with epoch now saves to preview history images
2019-02-07 22:34:51 +04:00
iperov
ea7a2456c5
upgrading to numpy==1.16.1, fix ConverterMasked
2019-02-07 11:27:43 +04:00
