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novelai-storage
Stable Diffusion Webui
Commits
e4145c84
Commit
e4145c84
authored
Sep 27, 2022
by
48DESIGN
Committed by
GitHub
Sep 27, 2022
Browse files
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Merge branch 'master' into notification-sound
parents
2846ca57
c0b1177a
Changes
7
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Showing
7 changed files
with
104 additions
and
20 deletions
+104
-20
.gitignore
.gitignore
+1
-0
javascript/dragdrop.js
javascript/dragdrop.js
+15
-9
javascript/ui.js
javascript/ui.js
+2
-3
modules/processing.py
modules/processing.py
+1
-1
modules/shared.py
modules/shared.py
+2
-1
script.js
script.js
+21
-0
scripts/img2imgalt.py
scripts/img2imgalt.py
+62
-6
No files found.
.gitignore
View file @
e4145c84
...
@@ -21,3 +21,4 @@ __pycache__
...
@@ -21,3 +21,4 @@ __pycache__
/user.css
/user.css
/.idea
/.idea
notification.mp3
notification.mp3
/SwinIR
javascript/dragdrop.js
View file @
e4145c84
...
@@ -68,13 +68,19 @@ window.addEventListener('paste', e => {
...
@@ -68,13 +68,19 @@ window.addEventListener('paste', e => {
if
(
!
isValidImageList
(
files
)
)
{
if
(
!
isValidImageList
(
files
)
)
{
return
;
return
;
}
}
[...
gradioApp
().
querySelectorAll
(
'
input[type=file][accept="image/x-png,image/gif,image/jpeg"]
'
)]
.
filter
(
input
=>
!
input
.
matches
(
'
.
\\
!hidden input[type=file]
'
))
const
visibleImageFields
=
[...
gradioApp
().
querySelectorAll
(
'
[data-testid="image"]
'
)]
.
forEach
(
input
=>
{
.
filter
(
el
=>
uiElementIsVisible
(
el
));
input
.
files
=
files
;
if
(
!
visibleImageFields
.
length
)
{
input
.
dispatchEvent
(
new
Event
(
'
change
'
))
return
;
});
}
[...
gradioApp
().
querySelectorAll
(
'
[data-testid="image"]
'
)]
.
filter
(
imgWrap
=>
!
imgWrap
.
closest
(
'
.
\\
!hidden
'
))
const
firstFreeImageField
=
visibleImageFields
.
forEach
(
imgWrap
=>
dropReplaceImage
(
imgWrap
,
files
));
.
filter
(
el
=>
el
.
querySelector
(
'
input[type=file]
'
))?.[
0
];
dropReplaceImage
(
firstFreeImageField
?
firstFreeImageField
:
visibleImageFields
[
visibleImageFields
.
length
-
1
]
,
files
);
});
});
javascript/ui.js
View file @
e4145c84
// various functions for interation with ui.py not large enough to warrant putting them in separate files
// various functions for interation with ui.py not large enough to warrant putting them in separate files
function
selected_gallery_index
(){
function
selected_gallery_index
(){
var
gr
=
gradioApp
()
var
buttons
=
gradioApp
().
querySelectorAll
(
'
[style="display: block;"].tabitem .gallery-item
'
)
var
buttons
=
gradioApp
().
querySelectorAll
(
"
.gallery-item
"
)
var
button
=
gradioApp
().
querySelector
(
'
[style="display: block;"].tabitem .gallery-item.
\\
!ring-2
'
)
var
button
=
gr
.
querySelector
(
"
.gallery-item.
\\
!ring-2
"
)
var
result
=
-
1
var
result
=
-
1
buttons
.
forEach
(
function
(
v
,
i
){
if
(
v
==
button
)
{
result
=
i
}
})
buttons
.
forEach
(
function
(
v
,
i
){
if
(
v
==
button
)
{
result
=
i
}
})
...
...
modules/processing.py
View file @
e4145c84
...
@@ -406,7 +406,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
...
@@ -406,7 +406,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
index_of_first_image
=
1
index_of_first_image
=
1
if
opts
.
grid_save
:
if
opts
.
grid_save
:
images
.
save_image
(
grid
,
p
.
outpath_grids
,
"grid"
,
all_seeds
[
0
],
all_prompts
[
0
],
opts
.
grid_format
,
info
=
infotext
(),
short_filename
=
not
opts
.
grid_extended_filename
,
p
=
p
)
images
.
save_image
(
grid
,
p
.
outpath_grids
,
"grid"
,
all_seeds
[
0
],
all_prompts
[
0
],
opts
.
grid_format
,
info
=
infotext
(),
short_filename
=
not
opts
.
grid_extended_filename
,
p
=
p
,
grid
=
True
)
devices
.
torch_gc
()
devices
.
torch_gc
()
return
Processed
(
p
,
output_images
,
all_seeds
[
0
],
infotext
(),
subseed
=
all_subseeds
[
0
],
all_prompts
=
all_prompts
,
all_seeds
=
all_seeds
,
all_subseeds
=
all_subseeds
,
index_of_first_image
=
index_of_first_image
)
return
Processed
(
p
,
output_images
,
all_seeds
[
0
],
infotext
(),
subseed
=
all_subseeds
[
0
],
all_prompts
=
all_prompts
,
all_seeds
=
all_seeds
,
all_subseeds
=
all_subseeds
,
index_of_first_image
=
index_of_first_image
)
...
...
modules/shared.py
View file @
e4145c84
...
@@ -66,7 +66,7 @@ class State:
...
@@ -66,7 +66,7 @@ class State:
job
=
""
job
=
""
job_no
=
0
job_no
=
0
job_count
=
0
job_count
=
0
job_timestamp
=
0
job_timestamp
=
'0'
sampling_step
=
0
sampling_step
=
0
sampling_steps
=
0
sampling_steps
=
0
current_latent
=
None
current_latent
=
None
...
@@ -80,6 +80,7 @@ class State:
...
@@ -80,6 +80,7 @@ class State:
self
.
job_no
+=
1
self
.
job_no
+=
1
self
.
sampling_step
=
0
self
.
sampling_step
=
0
self
.
current_image_sampling_step
=
0
self
.
current_image_sampling_step
=
0
def
get_job_timestamp
(
self
):
def
get_job_timestamp
(
self
):
return
datetime
.
datetime
.
now
()
.
strftime
(
"
%
Y
%
m
%
d
%
H
%
M
%
S"
)
return
datetime
.
datetime
.
now
()
.
strftime
(
"
%
Y
%
m
%
d
%
H
%
M
%
S"
)
...
...
script.js
View file @
e4145c84
...
@@ -39,3 +39,24 @@ document.addEventListener("DOMContentLoaded", function() {
...
@@ -39,3 +39,24 @@ document.addEventListener("DOMContentLoaded", function() {
});
});
mutationObserver
.
observe
(
gradioApp
(),
{
childList
:
true
,
subtree
:
true
})
mutationObserver
.
observe
(
gradioApp
(),
{
childList
:
true
,
subtree
:
true
})
});
});
/**
* checks that a UI element is not in another hidden element or tab content
*/
function
uiElementIsVisible
(
el
)
{
let
isVisible
=
!
el
.
closest
(
'
.
\\
!hidden
'
);
if
(
!
isVisible
)
{
return
false
;
}
while
(
isVisible
=
el
.
closest
(
'
.tabitem
'
)?.
style
.
display
!==
'
none
'
)
{
if
(
!
isVisible
)
{
return
false
;
}
else
if
(
el
.
parentElement
)
{
el
=
el
.
parentElement
}
else
{
break
;
}
}
return
isVisible
;
}
\ No newline at end of file
scripts/img2imgalt.py
View file @
e4145c84
...
@@ -59,7 +59,55 @@ def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
...
@@ -59,7 +59,55 @@ def find_noise_for_image(p, cond, uncond, cfg_scale, steps):
return
x
/
x
.
std
()
return
x
/
x
.
std
()
Cached
=
namedtuple
(
"Cached"
,
[
"noise"
,
"cfg_scale"
,
"steps"
,
"latent"
,
"original_prompt"
,
"original_negative_prompt"
])
Cached
=
namedtuple
(
"Cached"
,
[
"noise"
,
"cfg_scale"
,
"steps"
,
"latent"
,
"original_prompt"
,
"original_negative_prompt"
,
"sigma_adjustment"
])
# Based on changes suggested by briansemrau in https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/736
def
find_noise_for_image_sigma_adjustment
(
p
,
cond
,
uncond
,
cfg_scale
,
steps
):
x
=
p
.
init_latent
s_in
=
x
.
new_ones
([
x
.
shape
[
0
]])
dnw
=
K
.
external
.
CompVisDenoiser
(
shared
.
sd_model
)
sigmas
=
dnw
.
get_sigmas
(
steps
)
.
flip
(
0
)
shared
.
state
.
sampling_steps
=
steps
for
i
in
trange
(
1
,
len
(
sigmas
)):
shared
.
state
.
sampling_step
+=
1
x_in
=
torch
.
cat
([
x
]
*
2
)
sigma_in
=
torch
.
cat
([
sigmas
[
i
-
1
]
*
s_in
]
*
2
)
cond_in
=
torch
.
cat
([
uncond
,
cond
])
c_out
,
c_in
=
[
K
.
utils
.
append_dims
(
k
,
x_in
.
ndim
)
for
k
in
dnw
.
get_scalings
(
sigma_in
)]
if
i
==
1
:
t
=
dnw
.
sigma_to_t
(
torch
.
cat
([
sigmas
[
i
]
*
s_in
]
*
2
))
else
:
t
=
dnw
.
sigma_to_t
(
sigma_in
)
eps
=
shared
.
sd_model
.
apply_model
(
x_in
*
c_in
,
t
,
cond
=
cond_in
)
denoised_uncond
,
denoised_cond
=
(
x_in
+
eps
*
c_out
)
.
chunk
(
2
)
denoised
=
denoised_uncond
+
(
denoised_cond
-
denoised_uncond
)
*
cfg_scale
if
i
==
1
:
d
=
(
x
-
denoised
)
/
(
2
*
sigmas
[
i
])
else
:
d
=
(
x
-
denoised
)
/
sigmas
[
i
-
1
]
dt
=
sigmas
[
i
]
-
sigmas
[
i
-
1
]
x
=
x
+
d
*
dt
sd_samplers
.
store_latent
(
x
)
# This shouldn't be necessary, but solved some VRAM issues
del
x_in
,
sigma_in
,
cond_in
,
c_out
,
c_in
,
t
,
del
eps
,
denoised_uncond
,
denoised_cond
,
denoised
,
d
,
dt
shared
.
state
.
nextjob
()
return
x
/
sigmas
[
-
1
]
class
Script
(
scripts
.
Script
):
class
Script
(
scripts
.
Script
):
...
@@ -78,9 +126,10 @@ class Script(scripts.Script):
...
@@ -78,9 +126,10 @@ class Script(scripts.Script):
cfg
=
gr
.
Slider
(
label
=
"Decode CFG scale"
,
minimum
=
0.0
,
maximum
=
15.0
,
step
=
0.1
,
value
=
1.0
)
cfg
=
gr
.
Slider
(
label
=
"Decode CFG scale"
,
minimum
=
0.0
,
maximum
=
15.0
,
step
=
0.1
,
value
=
1.0
)
st
=
gr
.
Slider
(
label
=
"Decode steps"
,
minimum
=
1
,
maximum
=
150
,
step
=
1
,
value
=
50
)
st
=
gr
.
Slider
(
label
=
"Decode steps"
,
minimum
=
1
,
maximum
=
150
,
step
=
1
,
value
=
50
)
randomness
=
gr
.
Slider
(
label
=
"Randomness"
,
minimum
=
0.0
,
maximum
=
1.0
,
step
=
0.01
,
value
=
0.0
)
randomness
=
gr
.
Slider
(
label
=
"Randomness"
,
minimum
=
0.0
,
maximum
=
1.0
,
step
=
0.01
,
value
=
0.0
)
return
[
original_prompt
,
original_negative_prompt
,
cfg
,
st
,
randomness
]
sigma_adjustment
=
gr
.
Checkbox
(
label
=
"Sigma adjustment for finding noise for image"
,
value
=
False
)
return
[
original_prompt
,
original_negative_prompt
,
cfg
,
st
,
randomness
,
sigma_adjustment
]
def
run
(
self
,
p
,
original_prompt
,
original_negative_prompt
,
cfg
,
st
,
randomness
):
def
run
(
self
,
p
,
original_prompt
,
original_negative_prompt
,
cfg
,
st
,
randomness
,
sigma_adjustment
):
p
.
batch_size
=
1
p
.
batch_size
=
1
p
.
batch_count
=
1
p
.
batch_count
=
1
...
@@ -88,7 +137,10 @@ class Script(scripts.Script):
...
@@ -88,7 +137,10 @@ class Script(scripts.Script):
def
sample_extra
(
conditioning
,
unconditional_conditioning
,
seeds
,
subseeds
,
subseed_strength
):
def
sample_extra
(
conditioning
,
unconditional_conditioning
,
seeds
,
subseeds
,
subseed_strength
):
lat
=
(
p
.
init_latent
.
cpu
()
.
numpy
()
*
10
)
.
astype
(
int
)
lat
=
(
p
.
init_latent
.
cpu
()
.
numpy
()
*
10
)
.
astype
(
int
)
same_params
=
self
.
cache
is
not
None
and
self
.
cache
.
cfg_scale
==
cfg
and
self
.
cache
.
steps
==
st
and
self
.
cache
.
original_prompt
==
original_prompt
and
self
.
cache
.
original_negative_prompt
==
original_negative_prompt
same_params
=
self
.
cache
is
not
None
and
self
.
cache
.
cfg_scale
==
cfg
and
self
.
cache
.
steps
==
st
\
and
self
.
cache
.
original_prompt
==
original_prompt
\
and
self
.
cache
.
original_negative_prompt
==
original_negative_prompt
\
and
self
.
cache
.
sigma_adjustment
==
sigma_adjustment
same_everything
=
same_params
and
self
.
cache
.
latent
.
shape
==
lat
.
shape
and
np
.
abs
(
self
.
cache
.
latent
-
lat
)
.
sum
()
<
100
same_everything
=
same_params
and
self
.
cache
.
latent
.
shape
==
lat
.
shape
and
np
.
abs
(
self
.
cache
.
latent
-
lat
)
.
sum
()
<
100
if
same_everything
:
if
same_everything
:
...
@@ -97,8 +149,11 @@ class Script(scripts.Script):
...
@@ -97,8 +149,11 @@ class Script(scripts.Script):
shared
.
state
.
job_count
+=
1
shared
.
state
.
job_count
+=
1
cond
=
p
.
sd_model
.
get_learned_conditioning
(
p
.
batch_size
*
[
original_prompt
])
cond
=
p
.
sd_model
.
get_learned_conditioning
(
p
.
batch_size
*
[
original_prompt
])
uncond
=
p
.
sd_model
.
get_learned_conditioning
(
p
.
batch_size
*
[
original_negative_prompt
])
uncond
=
p
.
sd_model
.
get_learned_conditioning
(
p
.
batch_size
*
[
original_negative_prompt
])
rec_noise
=
find_noise_for_image
(
p
,
cond
,
uncond
,
cfg
,
st
)
if
sigma_adjustment
:
self
.
cache
=
Cached
(
rec_noise
,
cfg
,
st
,
lat
,
original_prompt
,
original_negative_prompt
)
rec_noise
=
find_noise_for_image_sigma_adjustment
(
p
,
cond
,
uncond
,
cfg
,
st
)
else
:
rec_noise
=
find_noise_for_image
(
p
,
cond
,
uncond
,
cfg
,
st
)
self
.
cache
=
Cached
(
rec_noise
,
cfg
,
st
,
lat
,
original_prompt
,
original_negative_prompt
,
sigma_adjustment
)
rand_noise
=
processing
.
create_random_tensors
(
p
.
init_latent
.
shape
[
1
:],
[
p
.
seed
+
x
+
1
for
x
in
range
(
p
.
init_latent
.
shape
[
0
])])
rand_noise
=
processing
.
create_random_tensors
(
p
.
init_latent
.
shape
[
1
:],
[
p
.
seed
+
x
+
1
for
x
in
range
(
p
.
init_latent
.
shape
[
0
])])
...
@@ -121,6 +176,7 @@ class Script(scripts.Script):
...
@@ -121,6 +176,7 @@ class Script(scripts.Script):
p
.
extra_generation_params
[
"Decode CFG scale"
]
=
cfg
p
.
extra_generation_params
[
"Decode CFG scale"
]
=
cfg
p
.
extra_generation_params
[
"Decode steps"
]
=
st
p
.
extra_generation_params
[
"Decode steps"
]
=
st
p
.
extra_generation_params
[
"Randomness"
]
=
randomness
p
.
extra_generation_params
[
"Randomness"
]
=
randomness
p
.
extra_generation_params
[
"Sigma Adjustment"
]
=
sigma_adjustment
processed
=
processing
.
process_images
(
p
)
processed
=
processing
.
process_images
(
p
)
...
...
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