mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2025-08-08 13:19:54 +00:00
Merge branch 'master' of https://github.com/AUTOMATIC1111/stable-diffusion-webui
This commit is contained in:
@@ -150,6 +150,7 @@ class Api:
|
||||
self.add_api_route("/sdapi/v1/train/embedding", self.train_embedding, methods=["POST"], response_model=TrainResponse)
|
||||
self.add_api_route("/sdapi/v1/train/hypernetwork", self.train_hypernetwork, methods=["POST"], response_model=TrainResponse)
|
||||
self.add_api_route("/sdapi/v1/memory", self.get_memory, methods=["GET"], response_model=MemoryResponse)
|
||||
self.add_api_route("/sdapi/v1/scripts", self.get_scripts_list, methods=["GET"], response_model=ScriptsList)
|
||||
|
||||
def add_api_route(self, path: str, endpoint, **kwargs):
|
||||
if shared.cmd_opts.api_auth:
|
||||
@@ -170,6 +171,12 @@ class Api:
|
||||
script_idx = script_name_to_index(script_name, script_runner.selectable_scripts)
|
||||
script = script_runner.selectable_scripts[script_idx]
|
||||
return script, script_idx
|
||||
|
||||
def get_scripts_list(self):
|
||||
t2ilist = [str(title.lower()) for title in scripts.scripts_txt2img.titles]
|
||||
i2ilist = [str(title.lower()) for title in scripts.scripts_img2img.titles]
|
||||
|
||||
return ScriptsList(txt2img = t2ilist, img2img = i2ilist)
|
||||
|
||||
def get_script(self, script_name, script_runner):
|
||||
if script_name is None or script_name == "":
|
||||
@@ -215,12 +222,11 @@ class Api:
|
||||
ui.create_ui()
|
||||
selectable_scripts, selectable_script_idx = self.get_selectable_script(txt2imgreq.script_name, script_runner)
|
||||
|
||||
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),
|
||||
"do_not_save_samples": True,
|
||||
"do_not_save_grid": True
|
||||
}
|
||||
)
|
||||
"do_not_save_samples": not txt2imgreq.save_images,
|
||||
"do_not_save_grid": not txt2imgreq.save_images,
|
||||
})
|
||||
if populate.sampler_name:
|
||||
populate.sampler_index = None # prevent a warning later on
|
||||
|
||||
@@ -231,22 +237,25 @@ class Api:
|
||||
|
||||
script_args = self.init_script_args(txt2imgreq, selectable_scripts, selectable_script_idx, script_runner)
|
||||
|
||||
send_images = args.pop('send_images', True)
|
||||
args.pop('save_images', None)
|
||||
|
||||
with self.queue_lock:
|
||||
p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **args)
|
||||
p.scripts = script_runner
|
||||
p.outpath_grids = opts.outdir_txt2img_grids
|
||||
p.outpath_samples = opts.outdir_txt2img_samples
|
||||
|
||||
shared.state.begin()
|
||||
if selectable_scripts != None:
|
||||
p.script_args = script_args
|
||||
p.outpath_grids = opts.outdir_txt2img_grids
|
||||
p.outpath_samples = opts.outdir_txt2img_samples
|
||||
processed = scripts.scripts_txt2img.run(p, *p.script_args) # Need to pass args as list here
|
||||
else:
|
||||
p.script_args = tuple(script_args) # Need to pass args as tuple here
|
||||
processed = process_images(p)
|
||||
shared.state.end()
|
||||
|
||||
b64images = list(map(encode_pil_to_base64, processed.images))
|
||||
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
|
||||
|
||||
return TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
|
||||
|
||||
@@ -267,11 +276,10 @@ class Api:
|
||||
|
||||
populate = img2imgreq.copy(update={ # Override __init__ params
|
||||
"sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
|
||||
"do_not_save_samples": True,
|
||||
"do_not_save_grid": True,
|
||||
"mask": mask
|
||||
}
|
||||
)
|
||||
"do_not_save_samples": not img2imgreq.save_images,
|
||||
"do_not_save_grid": not img2imgreq.save_images,
|
||||
"mask": mask,
|
||||
})
|
||||
if populate.sampler_name:
|
||||
populate.sampler_index = None # prevent a warning later on
|
||||
|
||||
@@ -283,23 +291,26 @@ class Api:
|
||||
|
||||
script_args = self.init_script_args(img2imgreq, selectable_scripts, selectable_script_idx, script_runner)
|
||||
|
||||
send_images = args.pop('send_images', True)
|
||||
args.pop('save_images', None)
|
||||
|
||||
with self.queue_lock:
|
||||
p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
|
||||
p.init_images = [decode_base64_to_image(x) for x in init_images]
|
||||
p.scripts = script_runner
|
||||
p.outpath_grids = opts.outdir_img2img_grids
|
||||
p.outpath_samples = opts.outdir_img2img_samples
|
||||
|
||||
shared.state.begin()
|
||||
if selectable_scripts != None:
|
||||
p.script_args = script_args
|
||||
p.outpath_grids = opts.outdir_img2img_grids
|
||||
p.outpath_samples = opts.outdir_img2img_samples
|
||||
processed = scripts.scripts_img2img.run(p, *p.script_args) # Need to pass args as list here
|
||||
else:
|
||||
p.script_args = tuple(script_args) # Need to pass args as tuple here
|
||||
processed = process_images(p)
|
||||
shared.state.end()
|
||||
|
||||
b64images = list(map(encode_pil_to_base64, processed.images))
|
||||
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
|
||||
|
||||
if not img2imgreq.include_init_images:
|
||||
img2imgreq.init_images = None
|
||||
|
@@ -14,8 +14,8 @@ API_NOT_ALLOWED = [
|
||||
"outpath_samples",
|
||||
"outpath_grids",
|
||||
"sampler_index",
|
||||
"do_not_save_samples",
|
||||
"do_not_save_grid",
|
||||
# "do_not_save_samples",
|
||||
# "do_not_save_grid",
|
||||
"extra_generation_params",
|
||||
"overlay_images",
|
||||
"do_not_reload_embeddings",
|
||||
@@ -100,13 +100,32 @@ class PydanticModelGenerator:
|
||||
StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
|
||||
"StableDiffusionProcessingTxt2Img",
|
||||
StableDiffusionProcessingTxt2Img,
|
||||
[{"key": "sampler_index", "type": str, "default": "Euler"}, {"key": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}, {"key": "alwayson_scripts", "type": dict, "default": {}}]
|
||||
[
|
||||
{"key": "sampler_index", "type": str, "default": "Euler"},
|
||||
{"key": "script_name", "type": str, "default": None},
|
||||
{"key": "script_args", "type": list, "default": []},
|
||||
{"key": "send_images", "type": bool, "default": True},
|
||||
{"key": "save_images", "type": bool, "default": False},
|
||||
{"key": "alwayson_scripts", "type": dict, "default": {}},
|
||||
]
|
||||
).generate_model()
|
||||
|
||||
StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
|
||||
"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": "script_name", "type": str, "default": None}, {"key": "script_args", "type": list, "default": []}, {"key": "alwayson_scripts", "type": dict, "default": {}}]
|
||||
|
||||
[
|
||||
{"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": []},
|
||||
{"key": "send_images", "type": bool, "default": True},
|
||||
{"key": "save_images", "type": bool, "default": False},
|
||||
{"key": "alwayson_scripts", "type": dict, "default": {}},
|
||||
]
|
||||
).generate_model()
|
||||
|
||||
class TextToImageResponse(BaseModel):
|
||||
@@ -267,3 +286,7 @@ class EmbeddingsResponse(BaseModel):
|
||||
class MemoryResponse(BaseModel):
|
||||
ram: dict = Field(title="RAM", description="System memory stats")
|
||||
cuda: dict = Field(title="CUDA", description="nVidia CUDA memory stats")
|
||||
|
||||
class ScriptsList(BaseModel):
|
||||
txt2img: list = Field(default=None,title="Txt2img", description="Titles of scripts (txt2img)")
|
||||
img2img: list = Field(default=None,title="Img2img", description="Titles of scripts (img2img)")
|
Reference in New Issue
Block a user