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Add ip_adapter and face_id fields for txt2img/ímg2img APIs

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Enes Sadık Özbek
2023-12-31 00:49:41 +03:00
parent ad895f0dac
commit 88a86b901f
2 changed files with 48 additions and 1 deletions
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modules/api/api.py
+31
View File
@@ -260,8 +260,31 @@ class Api:
p.per_script_args[alwayson_script.title()] = request.alwayson_scripts[alwayson_script_name]["args"]
return script_args
def prepare_img_gen_request(self, request, img_gen_type: str):
if hasattr(request, "face_id") and request.face_id and not request.script_name and "FaceID" not in request.alwayson_scripts:
request.script_name = "FaceID"
request.script_args = [request.face_id.scale, request.face_id.image]
del request.face_id
if hasattr(request, "ip_adapter") and request.ip_adapter and request.script_name != "IP Adapter" and "IP Adapter" not in request.alwayson_scripts:
request.alwayson_scripts = {} if request.alwayson_scripts is None else request.alwayson_scripts
request.alwayson_scripts["IP Adapter"] = {
"args": [request.ip_adapter.adapter, request.ip_adapter.scale, request.ip_adapter.image]
}
del request.ip_adapter
def sanitize_img_gen_request(self, request, img_gen_type: str):
if hasattr(request, "alwayson_scripts") and request.alwayson_scripts and "IP Adapter" in request.alwayson_scripts:
# Avoid returning the same base64 ipadapter input image in the response
request.alwayson_scripts["IP Adapter"]["args"][2] = "<base64 encoded image>"
if hasattr(request, "script_name") and request.script_name == "FaceID":
# Avoid returning the same base64 FaceID input image in the response
request.script_args[1] = "<base64 encoded image>"
def text2imgapi(self, txt2imgreq: models.StableDiffusionTxt2ImgProcessingAPI):
self.prepare_img_gen_request(txt2imgreq, "txt2img")
script_runner = scripts.scripts_txt2img
if not script_runner.scripts:
script_runner.initialize_scripts(False)
@@ -279,6 +302,8 @@ class Api:
args = vars(populate)
args.pop('script_name', None)
args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
args.pop('face_id', None)
args.pop('ip_adapter', None)
args.pop('alwayson_scripts', None)
send_images = args.pop('send_images', True)
args.pop('save_images', None)
@@ -298,9 +323,12 @@ class Api:
shared.state.end(api=False)
b64images = list(map(encode_pil_to_base64, processed.images)) if send_images else []
self.sanitize_img_gen_request(txt2imgreq, "txt2img")
return models.TextToImageResponse(images=b64images, parameters=vars(txt2imgreq), info=processed.js())
def img2imgapi(self, img2imgreq: models.StableDiffusionImg2ImgProcessingAPI):
self.prepare_img_gen_request(img2imgreq, "img2img")
init_images = img2imgreq.init_images
if init_images is None:
raise HTTPException(status_code=404, detail="Init image not found")
@@ -327,6 +355,8 @@ class Api:
args.pop('script_name', None)
args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
args.pop('alwayson_scripts', None)
args.pop('face_id', None)
args.pop('ip_adapter', None)
send_images = args.pop('send_images', True)
args.pop('save_images', None)
@@ -349,6 +379,7 @@ class Api:
if not img2imgreq.include_init_images:
img2imgreq.init_images = None
img2imgreq.mask = None
self.sanitize_img_gen_request(img2imgreq, "img2img")
return models.ImageToImageResponse(images=b64images, parameters=vars(img2imgreq), info=processed.js())
def extras_single_image_api(self, req: models.ExtrasSingleImageRequest):
modules/api/models.py
+17 -1
View File
@@ -91,6 +91,18 @@ class PydanticModelGenerator:
DynamicModel.__config__.allow_mutation = True
return DynamicModel
class IPAdapterItem(BaseModel):
adapter: str = Field(title="Adapter", default="Base", description="Adapter to use")
image: str = Field(title="Image", default="", description="Adapter image, must be a Base64 string containing the image's data.")
scale: float = Field(title="Scale", default=0.5, gt=0, le=1, description="Scale of the adapter image, must be between 0 and 1.")
class FaceIDItem(BaseModel):
image: str = Field(title="Image", default="", description="Source face image, must be a Base64 string containing the image's data.")
scale: float = Field(title="Scale", default=0.5, gt=0, le=1, description="Scale of the source face, must be between 0 and 1.")
StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
"StableDiffusionProcessingTxt2Img",
StableDiffusionProcessingTxt2Img,
@@ -101,6 +113,8 @@ StableDiffusionTxt2ImgProcessingAPI = PydanticModelGenerator(
{"key": "send_images", "type": bool, "default": True},
{"key": "save_images", "type": bool, "default": False},
{"key": "alwayson_scripts", "type": dict, "default": {}},
{"key": "ip_adapter", "type": Optional[IPAdapterItem], "default": None, "exclude": True},
{"key": "face_id", "type": Optional[FaceIDItem], "default": None, "exclude": True},
]
).generate_model()
@@ -112,12 +126,14 @@ StableDiffusionImg2ImgProcessingAPI = PydanticModelGenerator(
{"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": "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": {}},
{"key": "ip_adapter", "type": Optional[IPAdapterItem], "default": None, "exclude": True},
{"key": "face_id", "type": Optional[FaceIDItem], "default": None, "exclude": True},
]
).generate_model()