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novelai-storage
Stable Diffusion Webui
Commits
599f61a1
Commit
599f61a1
authored
Aug 13, 2023
by
AUTOMATIC1111
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use dataclass for StableDiffusionProcessing
parent
fa9370b7
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2
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2 changed files
with
176 additions
and
147 deletions
+176
-147
modules/processing.py
modules/processing.py
+172
-146
modules/sd_samplers_common.py
modules/sd_samplers_common.py
+4
-1
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modules/processing.py
View file @
599f61a1
from
__future__
import
annotations
import
json
import
json
import
logging
import
logging
import
math
import
math
import
os
import
os
import
sys
import
sys
import
hashlib
import
hashlib
from
dataclasses
import
dataclass
,
field
import
torch
import
torch
import
numpy
as
np
import
numpy
as
np
...
@@ -11,7 +13,7 @@ from PIL import Image, ImageOps
...
@@ -11,7 +13,7 @@ from PIL import Image, ImageOps
import
random
import
random
import
cv2
import
cv2
from
skimage
import
exposure
from
skimage
import
exposure
from
typing
import
Any
,
Dict
,
List
from
typing
import
Any
import
modules.sd_hijack
import
modules.sd_hijack
from
modules
import
devices
,
prompt_parser
,
masking
,
sd_samplers
,
lowvram
,
generation_parameters_copypaste
,
extra_networks
,
sd_vae_approx
,
scripts
,
sd_samplers_common
,
sd_unet
,
errors
,
rng
from
modules
import
devices
,
prompt_parser
,
masking
,
sd_samplers
,
lowvram
,
generation_parameters_copypaste
,
extra_networks
,
sd_vae_approx
,
scripts
,
sd_samplers_common
,
sd_unet
,
errors
,
rng
...
@@ -104,106 +106,126 @@ def txt2img_image_conditioning(sd_model, x, width, height):
...
@@ -104,106 +106,126 @@ def txt2img_image_conditioning(sd_model, x, width, height):
return
x
.
new_zeros
(
x
.
shape
[
0
],
5
,
1
,
1
,
dtype
=
x
.
dtype
,
device
=
x
.
device
)
return
x
.
new_zeros
(
x
.
shape
[
0
],
5
,
1
,
1
,
dtype
=
x
.
dtype
,
device
=
x
.
device
)
@
dataclass
(
repr
=
False
)
class
StableDiffusionProcessing
:
class
StableDiffusionProcessing
:
"""
sd_model
:
object
=
None
The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
outpath_samples
:
str
=
None
"""
outpath_grids
:
str
=
None
prompt
:
str
=
""
prompt_for_display
:
str
=
None
negative_prompt
:
str
=
""
styles
:
list
[
str
]
=
field
(
default_factory
=
list
)
seed
:
int
=
-
1
subseed
:
int
=
-
1
subseed_strength
:
float
=
0
seed_resize_from_h
:
int
=
-
1
seed_resize_from_w
:
int
=
-
1
seed_enable_extras
:
bool
=
True
sampler_name
:
str
=
None
batch_size
:
int
=
1
n_iter
:
int
=
1
steps
:
int
=
50
cfg_scale
:
float
=
7.0
width
:
int
=
512
height
:
int
=
512
restore_faces
:
bool
=
None
tiling
:
bool
=
None
do_not_save_samples
:
bool
=
False
do_not_save_grid
:
bool
=
False
extra_generation_params
:
dict
[
str
,
Any
]
=
None
overlay_images
:
list
=
None
eta
:
float
=
None
do_not_reload_embeddings
:
bool
=
False
denoising_strength
:
float
=
0
ddim_discretize
:
str
=
None
s_min_uncond
:
float
=
None
s_churn
:
float
=
None
s_tmax
:
float
=
None
s_tmin
:
float
=
None
s_noise
:
float
=
None
override_settings
:
dict
[
str
,
Any
]
=
None
override_settings_restore_afterwards
:
bool
=
True
sampler_index
:
int
=
None
refiner_checkpoint
:
str
=
None
refiner_switch_at
:
float
=
None
token_merging_ratio
=
0
token_merging_ratio_hr
=
0
disable_extra_networks
:
bool
=
False
script_args
:
list
=
None
cached_uc
=
[
None
,
None
]
cached_uc
=
[
None
,
None
]
cached_c
=
[
None
,
None
]
cached_c
=
[
None
,
None
]
def
__init__
(
self
,
sd_model
=
None
,
outpath_samples
=
None
,
outpath_grids
=
None
,
prompt
:
str
=
""
,
styles
:
List
[
str
]
=
None
,
seed
:
int
=
-
1
,
subseed
:
int
=
-
1
,
subseed_strength
:
float
=
0
,
seed_resize_from_h
:
int
=
-
1
,
seed_resize_from_w
:
int
=
-
1
,
seed_enable_extras
:
bool
=
True
,
sampler_name
:
str
=
None
,
batch_size
:
int
=
1
,
n_iter
:
int
=
1
,
steps
:
int
=
50
,
cfg_scale
:
float
=
7.0
,
width
:
int
=
512
,
height
:
int
=
512
,
restore_faces
:
bool
=
None
,
tiling
:
bool
=
None
,
do_not_save_samples
:
bool
=
False
,
do_not_save_grid
:
bool
=
False
,
extra_generation_params
:
Dict
[
Any
,
Any
]
=
None
,
overlay_images
:
Any
=
None
,
negative_prompt
:
str
=
None
,
eta
:
float
=
None
,
do_not_reload_embeddings
:
bool
=
False
,
denoising_strength
:
float
=
0
,
ddim_discretize
:
str
=
None
,
s_min_uncond
:
float
=
0.0
,
s_churn
:
float
=
0.0
,
s_tmax
:
float
=
None
,
s_tmin
:
float
=
0.0
,
s_noise
:
float
=
None
,
override_settings
:
Dict
[
str
,
Any
]
=
None
,
override_settings_restore_afterwards
:
bool
=
True
,
sampler_index
:
int
=
None
,
refiner_checkpoint
:
str
=
None
,
refiner_switch_at
:
float
=
None
,
script_args
:
list
=
None
):
sampler
:
sd_samplers_common
.
Sampler
|
None
=
field
(
default
=
None
,
init
=
False
)
if
sampler_index
is
not
None
:
is_using_inpainting_conditioning
:
bool
=
field
(
default
=
False
,
init
=
False
)
paste_to
:
tuple
|
None
=
field
(
default
=
None
,
init
=
False
)
is_hr_pass
:
bool
=
field
(
default
=
False
,
init
=
False
)
c
:
tuple
=
field
(
default
=
None
,
init
=
False
)
uc
:
tuple
=
field
(
default
=
None
,
init
=
False
)
rng
:
rng
.
ImageRNG
|
None
=
field
(
default
=
None
,
init
=
False
)
step_multiplier
:
int
=
field
(
default
=
1
,
init
=
False
)
color_corrections
:
list
=
field
(
default
=
None
,
init
=
False
)
scripts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
all_seeds
:
list
=
field
(
default
=
None
,
init
=
False
)
all_subseeds
:
list
=
field
(
default
=
None
,
init
=
False
)
iteration
:
int
=
field
(
default
=
0
,
init
=
False
)
main_prompt
:
str
=
field
(
default
=
None
,
init
=
False
)
main_negative_prompt
:
str
=
field
(
default
=
None
,
init
=
False
)
prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
seeds
:
list
=
field
(
default
=
None
,
init
=
False
)
subseeds
:
list
=
field
(
default
=
None
,
init
=
False
)
extra_network_data
:
dict
=
field
(
default
=
None
,
init
=
False
)
user
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_model_name
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_model_hash
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_vae_name
:
str
=
field
(
default
=
None
,
init
=
False
)
sd_vae_hash
:
str
=
field
(
default
=
None
,
init
=
False
)
def
__post_init__
(
self
):
if
self
.
sampler_index
is
not
None
:
print
(
"sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name"
,
file
=
sys
.
stderr
)
print
(
"sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name"
,
file
=
sys
.
stderr
)
self
.
outpath_samples
:
str
=
outpath_samples
self
.
outpath_grids
:
str
=
outpath_grids
self
.
prompt
:
str
=
prompt
self
.
prompt_for_display
:
str
=
None
self
.
negative_prompt
:
str
=
(
negative_prompt
or
""
)
self
.
styles
:
list
=
styles
or
[]
self
.
seed
:
int
=
seed
self
.
subseed
:
int
=
subseed
self
.
subseed_strength
:
float
=
subseed_strength
self
.
seed_resize_from_h
:
int
=
seed_resize_from_h
self
.
seed_resize_from_w
:
int
=
seed_resize_from_w
self
.
sampler_name
:
str
=
sampler_name
self
.
batch_size
:
int
=
batch_size
self
.
n_iter
:
int
=
n_iter
self
.
steps
:
int
=
steps
self
.
cfg_scale
:
float
=
cfg_scale
self
.
width
:
int
=
width
self
.
height
:
int
=
height
self
.
restore_faces
:
bool
=
restore_faces
self
.
tiling
:
bool
=
tiling
self
.
do_not_save_samples
:
bool
=
do_not_save_samples
self
.
do_not_save_grid
:
bool
=
do_not_save_grid
self
.
extra_generation_params
:
dict
=
extra_generation_params
or
{}
self
.
overlay_images
=
overlay_images
self
.
eta
=
eta
self
.
do_not_reload_embeddings
=
do_not_reload_embeddings
self
.
paste_to
=
None
self
.
color_corrections
=
None
self
.
denoising_strength
:
float
=
denoising_strength
self
.
sampler_noise_scheduler_override
=
None
self
.
sampler_noise_scheduler_override
=
None
self
.
ddim_discretize
=
ddim_discretize
or
opts
.
ddim_discretize
self
.
s_min_uncond
=
self
.
s_min_uncond
if
self
.
s_min_uncond
is
not
None
else
opts
.
s_min_uncond
self
.
s_min_uncond
=
s_min_uncond
or
opts
.
s_min_uncond
self
.
s_churn
=
self
.
s_churn
if
self
.
s_churn
is
not
None
else
opts
.
s_churn
self
.
s_churn
=
s_churn
or
opts
.
s_churn
self
.
s_tmin
=
self
.
s_tmin
if
self
.
s_tmin
is
not
None
else
opts
.
s_tmin
self
.
s_tmin
=
s_tmin
or
opts
.
s_tmin
self
.
s_tmax
=
(
self
.
s_tmax
if
self
.
s_tmax
is
not
None
else
opts
.
s_tmax
)
or
float
(
'inf'
)
self
.
s_tmax
=
(
s_tmax
if
s_tmax
is
not
None
else
opts
.
s_tmax
)
or
float
(
'inf'
)
self
.
s_noise
=
self
.
s_noise
if
self
.
s_noise
is
not
None
else
opts
.
s_noise
self
.
s_noise
=
s_noise
if
s_noise
is
not
None
else
opts
.
s_noise
self
.
override_settings
=
{
k
:
v
for
k
,
v
in
(
override_settings
or
{})
.
items
()
if
k
not
in
shared
.
restricted_opts
}
self
.
extra_generation_params
=
self
.
extra_generation_params
or
{}
self
.
override_settings_restore_afterwards
=
override_settings_restore_afterwards
self
.
override_settings
=
self
.
override_settings
or
{}
self
.
refiner_checkpoint
=
refiner_checkpoint
self
.
script_args
=
self
.
script_args
or
{}
self
.
refiner_switch_at
=
refiner_switch_at
self
.
is_using_inpainting_conditioning
=
False
self
.
disable_extra_networks
=
False
self
.
token_merging_ratio
=
0
self
.
token_merging_ratio_hr
=
0
self
.
refiner_checkpoint_info
=
None
self
.
refiner_checkpoint_info
=
None
if
not
seed_enable_extras
:
if
not
se
lf
.
se
ed_enable_extras
:
self
.
subseed
=
-
1
self
.
subseed
=
-
1
self
.
subseed_strength
=
0
self
.
subseed_strength
=
0
self
.
seed_resize_from_h
=
0
self
.
seed_resize_from_h
=
0
self
.
seed_resize_from_w
=
0
self
.
seed_resize_from_w
=
0
self
.
scripts
=
None
self
.
script_args
=
script_args
self
.
all_prompts
=
None
self
.
all_negative_prompts
=
None
self
.
all_seeds
=
None
self
.
all_subseeds
=
None
self
.
iteration
=
0
self
.
is_hr_pass
=
False
self
.
sampler
=
None
self
.
main_prompt
=
None
self
.
main_negative_prompt
=
None
self
.
prompts
=
None
self
.
negative_prompts
=
None
self
.
extra_network_data
=
None
self
.
seeds
=
None
self
.
subseeds
=
None
self
.
step_multiplier
=
1
self
.
cached_uc
=
StableDiffusionProcessing
.
cached_uc
self
.
cached_uc
=
StableDiffusionProcessing
.
cached_uc
self
.
cached_c
=
StableDiffusionProcessing
.
cached_c
self
.
cached_c
=
StableDiffusionProcessing
.
cached_c
self
.
uc
=
None
self
.
c
=
None
self
.
rng
:
rng
.
ImageRNG
=
None
self
.
user
=
None
self
.
sd_model_name
=
None
self
.
sd_model_hash
=
None
self
.
sd_vae_name
=
None
self
.
sd_vae_hash
=
None
@
property
@
property
def
sd_model
(
self
):
def
sd_model
(
self
):
return
shared
.
sd_model
return
shared
.
sd_model
@
sd_model
.
setter
def
sd_model
(
self
,
value
):
pass
def
txt2img_image_conditioning
(
self
,
x
,
width
=
None
,
height
=
None
):
def
txt2img_image_conditioning
(
self
,
x
,
width
=
None
,
height
=
None
):
self
.
is_using_inpainting_conditioning
=
self
.
sd_model
.
model
.
conditioning_key
in
{
'hybrid'
,
'concat'
}
self
.
is_using_inpainting_conditioning
=
self
.
sd_model
.
model
.
conditioning_key
in
{
'hybrid'
,
'concat'
}
...
@@ -932,49 +954,51 @@ def old_hires_fix_first_pass_dimensions(width, height):
...
@@ -932,49 +954,51 @@ def old_hires_fix_first_pass_dimensions(width, height):
return
width
,
height
return
width
,
height
@
dataclass
(
repr
=
False
)
class
StableDiffusionProcessingTxt2Img
(
StableDiffusionProcessing
):
class
StableDiffusionProcessingTxt2Img
(
StableDiffusionProcessing
):
sampler
=
None
enable_hr
:
bool
=
False
denoising_strength
:
float
=
0.75
firstphase_width
:
int
=
0
firstphase_height
:
int
=
0
hr_scale
:
float
=
2.0
hr_upscaler
:
str
=
None
hr_second_pass_steps
:
int
=
0
hr_resize_x
:
int
=
0
hr_resize_y
:
int
=
0
hr_checkpoint_name
:
str
=
None
hr_sampler_name
:
str
=
None
hr_prompt
:
str
=
''
hr_negative_prompt
:
str
=
''
cached_hr_uc
=
[
None
,
None
]
cached_hr_uc
=
[
None
,
None
]
cached_hr_c
=
[
None
,
None
]
cached_hr_c
=
[
None
,
None
]
def
__init__
(
self
,
enable_hr
:
bool
=
False
,
denoising_strength
:
float
=
0.75
,
firstphase_width
:
int
=
0
,
firstphase_height
:
int
=
0
,
hr_scale
:
float
=
2.0
,
hr_upscaler
:
str
=
None
,
hr_second_pass_steps
:
int
=
0
,
hr_resize_x
:
int
=
0
,
hr_resize_y
:
int
=
0
,
hr_checkpoint_name
:
str
=
None
,
hr_sampler_name
:
str
=
None
,
hr_prompt
:
str
=
''
,
hr_negative_prompt
:
str
=
''
,
**
kwargs
):
hr_checkpoint_info
:
dict
=
field
(
default
=
None
,
init
=
False
)
super
()
.
__init__
(
**
kwargs
)
hr_upscale_to_x
:
int
=
field
(
default
=
0
,
init
=
False
)
self
.
enable_hr
=
enable_hr
hr_upscale_to_y
:
int
=
field
(
default
=
0
,
init
=
False
)
self
.
denoising_strength
=
denoising_strength
truncate_x
:
int
=
field
(
default
=
0
,
init
=
False
)
self
.
hr_scale
=
hr_scale
truncate_y
:
int
=
field
(
default
=
0
,
init
=
False
)
self
.
hr_upscaler
=
hr_upscaler
applied_old_hires_behavior_to
:
tuple
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_second_pass_steps
=
hr_second_pass_steps
latent_scale_mode
:
dict
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_resize_x
=
hr_resize_x
hr_c
:
tuple
|
None
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_resize_y
=
hr_resize_y
hr_uc
:
tuple
|
None
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_upscale_to_x
=
hr_resize_x
all_hr_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_upscale_to_y
=
hr_resize_y
all_hr_negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_checkpoint_name
=
hr_checkpoint_name
hr_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_checkpoint_info
=
None
hr_negative_prompts
:
list
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_sampler_name
=
hr_sampler_name
hr_extra_network_data
:
list
=
field
(
default
=
None
,
init
=
False
)
self
.
hr_prompt
=
hr_prompt
self
.
hr_negative_prompt
=
hr_negative_prompt
def
__post_init__
(
self
):
self
.
all_hr_prompts
=
None
super
()
.
__post_init__
()
self
.
all_hr_negative_prompts
=
None
self
.
latent_scale_mode
=
None
if
self
.
firstphase_width
!=
0
or
self
.
firstphase_height
!=
0
:
if
firstphase_width
!=
0
or
firstphase_height
!=
0
:
self
.
hr_upscale_to_x
=
self
.
width
self
.
hr_upscale_to_x
=
self
.
width
self
.
hr_upscale_to_y
=
self
.
height
self
.
hr_upscale_to_y
=
self
.
height
self
.
width
=
firstphase_width
self
.
width
=
self
.
firstphase_width
self
.
height
=
firstphase_height
self
.
height
=
self
.
firstphase_height
self
.
truncate_x
=
0
self
.
truncate_y
=
0
self
.
applied_old_hires_behavior_to
=
None
self
.
hr_prompts
=
None
self
.
hr_negative_prompts
=
None
self
.
hr_extra_network_data
=
None
self
.
cached_hr_uc
=
StableDiffusionProcessingTxt2Img
.
cached_hr_uc
self
.
cached_hr_uc
=
StableDiffusionProcessingTxt2Img
.
cached_hr_uc
self
.
cached_hr_c
=
StableDiffusionProcessingTxt2Img
.
cached_hr_c
self
.
cached_hr_c
=
StableDiffusionProcessingTxt2Img
.
cached_hr_c
self
.
hr_c
=
None
self
.
hr_uc
=
None
def
calculate_target_resolution
(
self
):
def
calculate_target_resolution
(
self
):
if
opts
.
use_old_hires_fix_width_height
and
self
.
applied_old_hires_behavior_to
!=
(
self
.
width
,
self
.
height
):
if
opts
.
use_old_hires_fix_width_height
and
self
.
applied_old_hires_behavior_to
!=
(
self
.
width
,
self
.
height
):
...
@@ -1252,7 +1276,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
...
@@ -1252,7 +1276,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return
super
()
.
get_conds
()
return
super
()
.
get_conds
()
def
parse_extra_network_prompts
(
self
):
def
parse_extra_network_prompts
(
self
):
res
=
super
()
.
parse_extra_network_prompts
()
res
=
super
()
.
parse_extra_network_prompts
()
...
@@ -1265,32 +1288,37 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
...
@@ -1265,32 +1288,37 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
return
res
return
res
@
dataclass
(
repr
=
False
)
class
StableDiffusionProcessingImg2Img
(
StableDiffusionProcessing
):
class
StableDiffusionProcessingImg2Img
(
StableDiffusionProcessing
):
sampler
=
None
init_images
:
list
=
None
resize_mode
:
int
=
0
def
__init__
(
self
,
init_images
:
list
=
None
,
resize_mode
:
int
=
0
,
denoising_strength
:
float
=
0.75
,
image_cfg_scale
:
float
=
None
,
mask
:
Any
=
None
,
mask_blur
:
int
=
None
,
mask_blur_x
:
int
=
4
,
mask_blur_y
:
int
=
4
,
inpainting_fill
:
int
=
0
,
inpaint_full_res
:
bool
=
True
,
inpaint_full_res_padding
:
int
=
0
,
inpainting_mask_invert
:
int
=
0
,
initial_noise_multiplier
:
float
=
None
,
**
kwargs
):
denoising_strength
:
float
=
0.75
super
()
.
__init__
(
**
kwargs
)
image_cfg_scale
:
float
=
None
mask
:
Any
=
None
self
.
init_images
=
init_images
mask_blur_x
:
int
=
4
self
.
resize_mode
:
int
=
resize_mode
mask_blur_y
:
int
=
4
self
.
denoising_strength
:
float
=
denoising_strength
mask_blur
:
int
=
None
self
.
image_cfg_scale
:
float
=
image_cfg_scale
if
shared
.
sd_model
.
cond_stage_key
==
"edit"
else
None
inpainting_fill
:
int
=
0
self
.
init_latent
=
None
inpaint_full_res
:
bool
=
True
self
.
image_mask
=
mask
inpaint_full_res_padding
:
int
=
0
self
.
latent_mask
=
None
inpainting_mask_invert
:
int
=
0
self
.
mask_for_overlay
=
None
initial_noise_multiplier
:
float
=
None
self
.
mask_blur_x
=
mask_blur_x
latent_mask
:
Image
=
None
self
.
mask_blur_y
=
mask_blur_y
if
mask_blur
is
not
None
:
image_mask
:
Any
=
field
(
default
=
None
,
init
=
False
)
self
.
mask_blur
=
mask_blur
self
.
inpainting_fill
=
inpainting_fill
nmask
:
torch
.
Tensor
=
field
(
default
=
None
,
init
=
False
)
self
.
inpaint_full_res
=
inpaint_full_res
image_conditioning
:
torch
.
Tensor
=
field
(
default
=
None
,
init
=
False
)
self
.
inpaint_full_res_padding
=
inpaint_full_res_padding
init_img_hash
:
str
=
field
(
default
=
None
,
init
=
False
)
self
.
inpainting_mask_invert
=
inpainting_mask_invert
mask_for_overlay
:
Image
=
field
(
default
=
None
,
init
=
False
)
self
.
initial_noise_multiplier
=
opts
.
initial_noise_multiplier
if
initial_noise_multiplier
is
None
else
initial_noise_multiplier
init_latent
:
torch
.
Tensor
=
field
(
default
=
None
,
init
=
False
)
def
__post_init__
(
self
):
super
()
.
__post_init__
()
self
.
image_mask
=
self
.
mask
self
.
mask
=
None
self
.
mask
=
None
self
.
nmask
=
None
self
.
initial_noise_multiplier
=
opts
.
initial_noise_multiplier
if
self
.
initial_noise_multiplier
is
None
else
self
.
initial_noise_multiplier
self
.
image_conditioning
=
None
@
property
@
property
def
mask_blur
(
self
):
def
mask_blur
(
self
):
...
@@ -1300,15 +1328,13 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
...
@@ -1300,15 +1328,13 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
@
mask_blur
.
setter
@
mask_blur
.
setter
def
mask_blur
(
self
,
value
):
def
mask_blur
(
self
,
value
):
if
isinstance
(
value
,
int
):
self
.
mask_blur_x
=
value
self
.
mask_blur_x
=
value
self
.
mask_blur_y
=
value
self
.
mask_blur_y
=
value
@
mask_blur
.
deleter
def
mask_blur
(
self
):
del
self
.
mask_blur_x
del
self
.
mask_blur_y
def
init
(
self
,
all_prompts
,
all_seeds
,
all_subseeds
):
def
init
(
self
,
all_prompts
,
all_seeds
,
all_subseeds
):
self
.
image_cfg_scale
:
float
=
self
.
image_cfg_scale
if
shared
.
sd_model
.
cond_stage_key
==
"edit"
else
None
self
.
sampler
=
sd_samplers
.
create_sampler
(
self
.
sampler_name
,
self
.
sd_model
)
self
.
sampler
=
sd_samplers
.
create_sampler
(
self
.
sampler_name
,
self
.
sd_model
)
crop_region
=
None
crop_region
=
None
...
...
modules/sd_samplers_common.py
View file @
599f61a1
...
@@ -305,5 +305,8 @@ class Sampler:
...
@@ -305,5 +305,8 @@ class Sampler:
current_iter_seeds
=
p
.
all_seeds
[
p
.
iteration
*
p
.
batch_size
:(
p
.
iteration
+
1
)
*
p
.
batch_size
]
current_iter_seeds
=
p
.
all_seeds
[
p
.
iteration
*
p
.
batch_size
:(
p
.
iteration
+
1
)
*
p
.
batch_size
]
return
BrownianTreeNoiseSampler
(
x
,
sigma_min
,
sigma_max
,
seed
=
current_iter_seeds
)
return
BrownianTreeNoiseSampler
(
x
,
sigma_min
,
sigma_max
,
seed
=
current_iter_seeds
)
def
sample
(
self
,
p
,
x
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
raise
NotImplementedError
()
def
sample_img2img
(
self
,
p
,
x
,
noise
,
conditioning
,
unconditional_conditioning
,
steps
=
None
,
image_conditioning
=
None
):
raise
NotImplementedError
()
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