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novelai-storage
Stable Diffusion Webui
Commits
e7f2f1e1
Commit
e7f2f1e1
authored
Jan 08, 2023
by
AUTOMATIC1111
Committed by
GitHub
Jan 08, 2023
Browse files
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Browse Files
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Plain Diff
Merge pull request #6469 from noodleanon/scripts-from-api
Run scripts from API
parents
085427de
6d0cc1e2
Changes
4
Show whitespace changes
Inline
Side-by-side
Showing
4 changed files
with
48 additions
and
9 deletions
+48
-9
modules/api/api.py
modules/api/api.py
+42
-5
modules/api/models.py
modules/api/models.py
+2
-2
modules/processing.py
modules/processing.py
+2
-2
scripts/sd_upscale.py
scripts/sd_upscale.py
+2
-0
No files found.
modules/api/api.py
View file @
e7f2f1e1
...
@@ -11,7 +11,7 @@ from fastapi.security import HTTPBasic, HTTPBasicCredentials
...
@@ -11,7 +11,7 @@ from fastapi.security import HTTPBasic, HTTPBasicCredentials
from
secrets
import
compare_digest
from
secrets
import
compare_digest
import
modules.shared
as
shared
import
modules.shared
as
shared
from
modules
import
sd_samplers
,
deepbooru
,
sd_hijack
,
images
from
modules
import
sd_samplers
,
deepbooru
,
sd_hijack
,
images
,
scripts
,
ui
from
modules.api.models
import
*
from
modules.api.models
import
*
from
modules.processing
import
StableDiffusionProcessingTxt2Img
,
StableDiffusionProcessingImg2Img
,
process_images
from
modules.processing
import
StableDiffusionProcessingTxt2Img
,
StableDiffusionProcessingImg2Img
,
process_images
from
modules.extras
import
run_extras
from
modules.extras
import
run_extras
...
@@ -28,8 +28,13 @@ def upscaler_to_index(name: str):
...
@@ -28,8 +28,13 @@ def upscaler_to_index(name: str):
try
:
try
:
return
[
x
.
name
.
lower
()
for
x
in
shared
.
sd_upscalers
]
.
index
(
name
.
lower
())
return
[
x
.
name
.
lower
()
for
x
in
shared
.
sd_upscalers
]
.
index
(
name
.
lower
())
except
:
except
:
raise
HTTPException
(
status_code
=
400
,
detail
=
f
"Invalid upscaler, needs to be on of these: {' , '.join([x.name for x in sd_upscalers])}"
)
raise
HTTPException
(
status_code
=
400
,
detail
=
f
"Invalid upscaler, needs to be on
e
of these: {' , '.join([x.name for x in sd_upscalers])}"
)
def
script_name_to_index
(
name
,
scripts
):
try
:
return
[
script
.
title
()
.
lower
()
for
script
in
scripts
]
.
index
(
name
.
lower
())
except
:
raise
HTTPException
(
status_code
=
422
,
detail
=
f
"Script '{name}' not found"
)
def
validate_sampler_name
(
name
):
def
validate_sampler_name
(
name
):
config
=
sd_samplers
.
all_samplers_map
.
get
(
name
,
None
)
config
=
sd_samplers
.
all_samplers_map
.
get
(
name
,
None
)
...
@@ -144,6 +149,14 @@ class Api:
...
@@ -144,6 +149,14 @@ class Api:
raise
HTTPException
(
status_code
=
401
,
detail
=
"Incorrect username or password"
,
headers
=
{
"WWW-Authenticate"
:
"Basic"
})
raise
HTTPException
(
status_code
=
401
,
detail
=
"Incorrect username or password"
,
headers
=
{
"WWW-Authenticate"
:
"Basic"
})
def
text2imgapi
(
self
,
txt2imgreq
:
StableDiffusionTxt2ImgProcessingAPI
):
def
text2imgapi
(
self
,
txt2imgreq
:
StableDiffusionTxt2ImgProcessingAPI
):
if
txt2imgreq
.
script_name
is
not
None
:
if
scripts
.
scripts_txt2img
.
scripts
==
[]:
scripts
.
scripts_txt2img
.
initialize_scripts
(
False
)
ui
.
create_ui
()
script_idx
=
script_name_to_index
(
txt2imgreq
.
script_name
,
scripts
.
scripts_txt2img
.
selectable_scripts
)
script
=
scripts
.
scripts_txt2img
.
selectable_scripts
[
script_idx
]
populate
=
txt2imgreq
.
copy
(
update
=
{
# Override __init__ params
populate
=
txt2imgreq
.
copy
(
update
=
{
# Override __init__ params
"sampler_name"
:
validate_sampler_name
(
txt2imgreq
.
sampler_name
or
txt2imgreq
.
sampler_index
),
"sampler_name"
:
validate_sampler_name
(
txt2imgreq
.
sampler_name
or
txt2imgreq
.
sampler_index
),
"do_not_save_samples"
:
True
,
"do_not_save_samples"
:
True
,
...
@@ -153,10 +166,19 @@ class Api:
...
@@ -153,10 +166,19 @@ class Api:
if
populate
.
sampler_name
:
if
populate
.
sampler_name
:
populate
.
sampler_index
=
None
# prevent a warning later on
populate
.
sampler_index
=
None
# prevent a warning later on
args
=
vars
(
populate
)
args
.
pop
(
'script_name'
,
None
)
with
self
.
queue_lock
:
with
self
.
queue_lock
:
p
=
StableDiffusionProcessingTxt2Img
(
sd_model
=
shared
.
sd_model
,
**
vars
(
populate
)
)
p
=
StableDiffusionProcessingTxt2Img
(
sd_model
=
shared
.
sd_model
,
**
args
)
shared
.
state
.
begin
()
shared
.
state
.
begin
()
if
'script'
in
locals
():
p
.
outpath_grids
=
opts
.
outdir_txt2img_grids
p
.
outpath_samples
=
opts
.
outdir_txt2img_samples
p
.
script_args
=
[
script_idx
+
1
]
+
[
None
]
*
(
script
.
args_from
-
1
)
+
p
.
script_args
processed
=
scripts
.
scripts_txt2img
.
run
(
p
,
*
p
.
script_args
)
else
:
processed
=
process_images
(
p
)
processed
=
process_images
(
p
)
shared
.
state
.
end
()
shared
.
state
.
end
()
...
@@ -170,6 +192,14 @@ class Api:
...
@@ -170,6 +192,14 @@ class Api:
if
init_images
is
None
:
if
init_images
is
None
:
raise
HTTPException
(
status_code
=
404
,
detail
=
"Init image not found"
)
raise
HTTPException
(
status_code
=
404
,
detail
=
"Init image not found"
)
if
img2imgreq
.
script_name
is
not
None
:
if
scripts
.
scripts_img2img
.
scripts
==
[]:
scripts
.
scripts_img2img
.
initialize_scripts
(
True
)
ui
.
create_ui
()
script_idx
=
script_name_to_index
(
img2imgreq
.
script_name
,
scripts
.
scripts_img2img
.
selectable_scripts
)
script
=
scripts
.
scripts_img2img
.
selectable_scripts
[
script_idx
]
mask
=
img2imgreq
.
mask
mask
=
img2imgreq
.
mask
if
mask
:
if
mask
:
mask
=
decode_base64_to_image
(
mask
)
mask
=
decode_base64_to_image
(
mask
)
...
@@ -186,12 +216,19 @@ class Api:
...
@@ -186,12 +216,19 @@ class Api:
args
=
vars
(
populate
)
args
=
vars
(
populate
)
args
.
pop
(
'include_init_images'
,
None
)
# this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine.
args
.
pop
(
'include_init_images'
,
None
)
# this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine.
args
.
pop
(
'script_name'
,
None
)
with
self
.
queue_lock
:
with
self
.
queue_lock
:
p
=
StableDiffusionProcessingImg2Img
(
sd_model
=
shared
.
sd_model
,
**
args
)
p
=
StableDiffusionProcessingImg2Img
(
sd_model
=
shared
.
sd_model
,
**
args
)
p
.
init_images
=
[
decode_base64_to_image
(
x
)
for
x
in
init_images
]
p
.
init_images
=
[
decode_base64_to_image
(
x
)
for
x
in
init_images
]
shared
.
state
.
begin
()
shared
.
state
.
begin
()
if
'script'
in
locals
():
p
.
outpath_grids
=
opts
.
outdir_img2img_grids
p
.
outpath_samples
=
opts
.
outdir_img2img_samples
p
.
script_args
=
[
script_idx
+
1
]
+
[
None
]
*
(
script
.
args_from
-
1
)
+
p
.
script_args
processed
=
scripts
.
scripts_img2img
.
run
(
p
,
*
p
.
script_args
)
else
:
processed
=
process_images
(
p
)
processed
=
process_images
(
p
)
shared
.
state
.
end
()
shared
.
state
.
end
()
...
...
modules/api/models.py
View file @
e7f2f1e1
...
@@ -100,13 +100,13 @@ class PydanticModelGenerator:
...
@@ -100,13 +100,13 @@ class PydanticModelGenerator:
StableDiffusionTxt2ImgProcessingAPI
=
PydanticModelGenerator
(
StableDiffusionTxt2ImgProcessingAPI
=
PydanticModelGenerator
(
"StableDiffusionProcessingTxt2Img"
,
"StableDiffusionProcessingTxt2Img"
,
StableDiffusionProcessingTxt2Img
,
StableDiffusionProcessingTxt2Img
,
[{
"key"
:
"sampler_index"
,
"type"
:
str
,
"default"
:
"Euler"
}]
[{
"key"
:
"sampler_index"
,
"type"
:
str
,
"default"
:
"Euler"
}
,
{
"key"
:
"script_name"
,
"type"
:
str
,
"default"
:
None
},
{
"key"
:
"script_args"
,
"type"
:
list
,
"default"
:
[]}
]
)
.
generate_model
()
)
.
generate_model
()
StableDiffusionImg2ImgProcessingAPI
=
PydanticModelGenerator
(
StableDiffusionImg2ImgProcessingAPI
=
PydanticModelGenerator
(
"StableDiffusionProcessingImg2Img"
,
"StableDiffusionProcessingImg2Img"
,
StableDiffusionProcessingImg2Img
,
StableDiffusionProcessingImg2Img
,
[{
"key"
:
"sampler_index"
,
"type"
:
str
,
"default"
:
"Euler"
},
{
"key"
:
"init_images"
,
"type"
:
list
,
"default"
:
None
},
{
"key"
:
"denoising_strength"
,
"type"
:
float
,
"default"
:
0.75
},
{
"key"
:
"mask"
,
"type"
:
str
,
"default"
:
None
},
{
"key"
:
"include_init_images"
,
"type"
:
bool
,
"default"
:
False
,
"exclude"
:
True
}]
[{
"key"
:
"sampler_index"
,
"type"
:
str
,
"default"
:
"Euler"
},
{
"key"
:
"init_images"
,
"type"
:
list
,
"default"
:
None
},
{
"key"
:
"denoising_strength"
,
"type"
:
float
,
"default"
:
0.75
},
{
"key"
:
"mask"
,
"type"
:
str
,
"default"
:
None
},
{
"key"
:
"include_init_images"
,
"type"
:
bool
,
"default"
:
False
,
"exclude"
:
True
}
,
{
"key"
:
"script_name"
,
"type"
:
str
,
"default"
:
None
},
{
"key"
:
"script_args"
,
"type"
:
list
,
"default"
:
[]}
]
)
.
generate_model
()
)
.
generate_model
()
class
TextToImageResponse
(
BaseModel
):
class
TextToImageResponse
(
BaseModel
):
...
...
modules/processing.py
View file @
e7f2f1e1
...
@@ -98,7 +98,7 @@ class StableDiffusionProcessing():
...
@@ -98,7 +98,7 @@ class StableDiffusionProcessing():
"""
"""
The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
"""
"""
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
=
False
,
tiling
:
bool
=
False
,
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_churn
:
float
=
0.0
,
s_tmax
:
float
=
None
,
s_tmin
:
float
=
0.0
,
s_noise
:
float
=
1.0
,
override_settings
:
Dict
[
str
,
Any
]
=
None
,
override_settings_restore_afterwards
:
bool
=
True
,
sampler_index
:
int
=
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
=
False
,
tiling
:
bool
=
False
,
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_churn
:
float
=
0.0
,
s_tmax
:
float
=
None
,
s_tmin
:
float
=
0.0
,
s_noise
:
float
=
1.0
,
override_settings
:
Dict
[
str
,
Any
]
=
None
,
override_settings_restore_afterwards
:
bool
=
True
,
sampler_index
:
int
=
None
,
script_args
:
list
=
None
):
if
sampler_index
is
not
None
:
if
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
)
...
@@ -149,7 +149,7 @@ class StableDiffusionProcessing():
...
@@ -149,7 +149,7 @@ class StableDiffusionProcessing():
self
.
seed_resize_from_w
=
0
self
.
seed_resize_from_w
=
0
self
.
scripts
=
None
self
.
scripts
=
None
self
.
script_args
=
None
self
.
script_args
=
script_args
self
.
all_prompts
=
None
self
.
all_prompts
=
None
self
.
all_negative_prompts
=
None
self
.
all_negative_prompts
=
None
self
.
all_seeds
=
None
self
.
all_seeds
=
None
...
...
scripts/sd_upscale.py
View file @
e7f2f1e1
...
@@ -25,6 +25,8 @@ class Script(scripts.Script):
...
@@ -25,6 +25,8 @@ class Script(scripts.Script):
return
[
info
,
overlap
,
upscaler_index
,
scale_factor
]
return
[
info
,
overlap
,
upscaler_index
,
scale_factor
]
def
run
(
self
,
p
,
_
,
overlap
,
upscaler_index
,
scale_factor
):
def
run
(
self
,
p
,
_
,
overlap
,
upscaler_index
,
scale_factor
):
if
isinstance
(
upscaler_index
,
str
):
upscaler_index
=
[
x
.
name
.
lower
()
for
x
in
shared
.
sd_upscalers
]
.
index
(
upscaler_index
.
lower
())
processing
.
fix_seed
(
p
)
processing
.
fix_seed
(
p
)
upscaler
=
shared
.
sd_upscalers
[
upscaler_index
]
upscaler
=
shared
.
sd_upscalers
[
upscaler_index
]
...
...
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