mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 17:24:32 +02:00
cleanup api
This commit is contained in:
Vladimir Mandic
+8
-6
@@ -5,8 +5,7 @@ from fastapi import FastAPI, APIRouter, Depends, Request
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from fastapi.security import HTTPBasic, HTTPBasicCredentials
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from fastapi.exceptions import HTTPException
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from modules import errors, shared, postprocessing
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from modules.api import models, endpoints, script, helpers, server, nvml, generate
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from modules.control import api as control_api
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from modules.api import models, endpoints, script, helpers, server, nvml, generate, process, control
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errors.install()
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@@ -29,6 +28,8 @@ class Api:
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self.app = app
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self.queue_lock = queue_lock
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self.generate = generate.APIGenerate(queue_lock)
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self.process = process.APIProcess(queue_lock)
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self.control = control.APIControl(queue_lock)
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# server api
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self.add_api_route("/sdapi/v1/motd", server.get_motd, methods=["GET"], response_model=str)
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@@ -49,18 +50,19 @@ class Api:
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# core api using locking
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self.add_api_route("/sdapi/v1/txt2img", self.generate.post_text2img, methods=["POST"], response_model=models.ResTxt2Img)
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self.add_api_route("/sdapi/v1/img2img", self.generate.post_img2img, methods=["POST"], response_model=models.ResImg2Img)
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self.add_api_route("/sdapi/v1/control", self.control.post_control, methods=["POST"], response_model=control.ResControl)
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self.add_api_route("/sdapi/v1/extra-single-image", self.extras_single_image_api, methods=["POST"], response_model=models.ResProcessImage)
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self.add_api_route("/sdapi/v1/extra-batch-images", self.extras_batch_images_api, methods=["POST"], response_model=models.ResProcessBatch)
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self.add_api_route("/sdapi/v1/preprocess", control_api.post_preprocess, methods=["POST"])
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self.add_api_route("/sdapi/v1/mask", control_api.post_mask, methods=["POST"])
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self.add_api_route("/sdapi/v1/preprocess", self.process.post_preprocess, methods=["POST"])
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self.add_api_route("/sdapi/v1/mask", self.process.post_mask, methods=["POST"])
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# api dealing with optional scripts
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self.add_api_route("/sdapi/v1/scripts", script.get_scripts_list, methods=["GET"], response_model=models.ResScripts)
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self.add_api_route("/sdapi/v1/script-info", script.get_script_info, methods=["GET"], response_model=List[models.ItemScript])
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# enumerator api
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self.add_api_route("/sdapi/v1/preprocessors", control_api.get_preprocess, methods=["GET"])
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self.add_api_route("/sdapi/v1/masking", control_api.get_mask, methods=["GET"])
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self.add_api_route("/sdapi/v1/preprocessors", self.process.get_preprocess, methods=["GET"], response_model=List[process.ItemPreprocess])
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self.add_api_route("/sdapi/v1/masking", self.process.get_mask, methods=["GET"], response_model=process.ItemMask)
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self.add_api_route("/sdapi/v1/interrogate", endpoints.get_interrogate, methods=["GET"], response_model=List[str])
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self.add_api_route("/sdapi/v1/samplers", endpoints.get_samplers, methods=["GET"], response_model=List[models.ItemSampler])
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self.add_api_route("/sdapi/v1/upscalers", endpoints.get_upscalers, methods=["GET"], response_model=List[models.ItemUpscaler])
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@@ -0,0 +1,114 @@
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from typing import Optional, List
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from threading import Lock
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from pydantic import BaseModel, Field # pylint: disable=no-name-in-module
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from modules import errors, shared, scripts, ui
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from modules.api import script, helpers
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from modules.processing import StableDiffusionProcessingControl
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from modules.control import run as run_control
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# TODO control api
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# should use control.run, not process_images directly
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errors.install()
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class ReqControl(BaseModel):
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pass
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class ResControl(BaseModel):
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images: List[str] = Field(default=None, title="Image", description="The generated images in base64 format.")
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params: dict = Field(default={}, title="Settings", description="Process settings")
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info: str = Field(default="", title="Info", description="Process info")
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class APIControl():
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def __init__(self, queue_lock: Lock):
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self.queue_lock = queue_lock
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self.default_script_arg = []
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def sanitize_args(self, args: dict):
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args = vars(args)
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args.pop('include_init_images', None) # this is meant to be done by "exclude": True in model
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args.pop('script_name', None)
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args.pop('script_args', None) # will refeed them to the pipeline directly after initializing them
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args.pop('alwayson_scripts', None)
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args.pop('face', None)
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args.pop('face_id', None)
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args.pop('ip_adapter', None)
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args.pop('save_images', None)
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return args
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def sanitize_b64(self, request):
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def sanitize_str(args: list):
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for idx in range(0, len(args)):
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if isinstance(args[idx], str) and len(args[idx]) >= 1000:
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args[idx] = f"<str {len(args[idx])}>"
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if hasattr(request, "alwayson_scripts") and request.alwayson_scripts:
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for script_name in request.alwayson_scripts.keys():
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script_obj = request.alwayson_scripts[script_name]
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if script_obj and "args" in script_obj and script_obj["args"]:
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sanitize_str(script_obj["args"])
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if hasattr(request, "script_args") and request.script_args:
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sanitize_str(request.script_args)
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def prepare_face_module(self, request):
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if hasattr(request, "face") and request.face and not request.script_name and (not request.alwayson_scripts or "face" not in request.alwayson_scripts.keys()):
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request.script_name = "face"
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request.script_args = [
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request.face.mode,
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request.face.source_images,
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request.face.ip_model,
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request.face.ip_override_sampler,
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request.face.ip_cache_model,
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request.face.ip_strength,
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request.face.ip_structure,
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request.face.id_strength,
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request.face.id_conditioning,
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request.face.id_cache,
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request.face.pm_trigger,
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request.face.pm_strength,
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request.face.pm_start,
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request.face.fs_cache
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]
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del request.face
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def post_control(self, req: ReqControl):
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self.prepare_face_module(req)
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# prepare script
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script_runner = scripts.scripts_control
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if not script_runner.scripts:
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script_runner.initialize_scripts(False)
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ui.create_ui(None)
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if not self.default_script_arg:
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self.default_script_arg = script.init_default_script_args(script_runner)
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# prepare args
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args = req.copy(update={ # Override __init__ params
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"sampler_name": helpers.validate_sampler_name(req.sampler_name or req.sampler_index),
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"sampler_index": None,
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"do_not_save_samples": not req.save_images,
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"do_not_save_grid": not req.save_images,
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"init_images": [helpers.decode_base64_to_image(x) for x in req.init_images] if req.init_images else None,
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"mask": helpers.decode_base64_to_image(req.mask) if req.mask else None,
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})
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args = self.sanitize_args(args)
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send_images = args.pop('send_images', True)
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# run
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with self.queue_lock:
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shared.state.begin('api-control', api=True)
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# selectable_scripts, selectable_script_idx = script.get_selectable_script(req.script_name, script_runner)
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# script_args = script.init_script_args(p, req, self.default_script_arg, selectable_scripts, selectable_script_idx, script_runner)
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# output_images, _processed_images, output_info = run_control(**args, **script_args)
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output_images = None
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output_info = None
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shared.state.end(api=False)
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# return
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b64images = list(map(helpers.encode_pil_to_base64, output_images)) if send_images else []
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self.sanitize_b64(req)
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return ResControl(images=b64images, params=vars(req), info=output_info)
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@@ -1,5 +1,5 @@
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from threading import Lock
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from fastapi.exceptions import HTTPException
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from fastapi.responses import JSONResponse
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from modules import errors, shared, scripts, ui
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from modules.api import models, script, helpers
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from modules.processing import StableDiffusionProcessingTxt2Img, StableDiffusionProcessingImg2Img, process_images
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@@ -100,7 +100,7 @@ class APIGenerate():
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self.prepare_face_module(img2imgreq)
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init_images = img2imgreq.init_images
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if init_images is None:
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raise HTTPException(status_code=404, detail="Init image not found")
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return JSONResponse(status_code=400, content={"error": "Init image is none"})
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mask = img2imgreq.mask
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if mask:
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mask = helpers.decode_base64_to_image(mask)
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@@ -208,7 +208,7 @@ ReqTxt2Img = PydanticModelGenerator(
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StableDiffusionTxt2ImgProcessingAPI = ReqTxt2Img
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class ResTxt2Img(BaseModel):
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images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
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images: List[str] = Field(default=None, title="Image", description="The generated images in base64 format.")
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parameters: dict
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info: str
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@@ -233,7 +233,7 @@ ReqImg2Img = PydanticModelGenerator(
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StableDiffusionImg2ImgProcessingAPI = ReqImg2Img
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class ResImg2Img(BaseModel):
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images: List[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
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images: List[str] = Field(default=None, title="Image", description="The generated images in base64 format.")
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parameters: dict
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info: str
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@@ -0,0 +1,100 @@
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from typing import Optional, List
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from threading import Lock
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from pydantic import BaseModel, Field # pylint: disable=no-name-in-module
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from fastapi.responses import JSONResponse
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from modules.api.helpers import decode_base64_to_image, encode_pil_to_base64
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from modules import errors, shared
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processor = None # cached instance of processor
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errors.install()
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class ReqPreprocess(BaseModel):
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image: str = Field(title="Image", description="The base64 encoded image")
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model: str = Field(title="Model", description="The model to use for preprocessing")
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params: Optional[dict] = Field(default={}, title="Settings", description="Preprocessor settings")
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class ResPreprocess(BaseModel):
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model: str = Field(default='', title="Model", description="The processor model used")
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image: str = Field(default='', title="Image", description="The processed image in base64 format")
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class ReqMask(BaseModel):
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image: str = Field(title="Image", description="The base64 encoded image")
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type: str = Field(title="Mask type", description="Type of masking image to return")
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mask: Optional[str] = Field(title="Mask", description="If optional maks image is not provided auto-masking will be performed")
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model: Optional[str] = Field(title="Model", description="The model to use for preprocessing")
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params: Optional[dict] = Field(default={}, title="Settings", description="Preprocessor settings")
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class ResMask(BaseModel):
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mask: str = Field(default='', title="Image", description="The processed image in base64 format")
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class ItemPreprocess(BaseModel):
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name: str = Field(title="Name")
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params: dict = Field(title="Params")
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class ItemMask(BaseModel):
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models: List[str] = Field(title="Models")
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colormaps: List[str] = Field(title="Color maps")
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params: dict = Field(title="Params")
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types: List[str] = Field(title="Types")
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class APIProcess():
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def __init__(self, queue_lock: Lock):
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self.queue_lock = queue_lock
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def get_preprocess(self):
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from modules.control import processors
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items = []
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for k, v in processors.config.items():
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items.append(ItemPreprocess(name=k, params=v.get('params', {})))
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return items
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def post_preprocess(self, req: ReqPreprocess):
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global processor # pylint: disable=global-statement
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from modules.control import processors
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models = list(processors.config)
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if req.model not in models:
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return JSONResponse(status_code=400, content={"error": f"Processor model not found: id={req.model}"})
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image = decode_base64_to_image(req.image)
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if processor is None or processor.processor_id != req.model:
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with self.queue_lock:
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processor = processors.Processor(req.model)
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for k, v in req.params.items():
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if k not in processors.config[processor.processor_id]['params']:
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return JSONResponse(status_code=400, content={"error": f"Processor invalid parameter: id={req.model} {k}={v}"})
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shared.state.begin('api-preprocess', api=True)
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processed = processor(image, local_config=req.params)
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image = encode_pil_to_base64(processed)
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shared.state.end(api=False)
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return ResPreprocess(model=processor.processor_id, image=image)
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def get_mask(self):
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from modules import masking
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return ItemMask(models=list(masking.MODELS), colormaps=masking.COLORMAP, params=vars(masking.opts), types=masking.TYPES)
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def post_mask(self, req: ReqMask):
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from modules import masking
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if req.model:
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if req.model not in masking.MODELS:
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return JSONResponse(status_code=400, content={"error": f"Mask model not found: id={req.model}"})
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else:
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masking.init_model(req.model)
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if req.type not in masking.TYPES:
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return JSONResponse(status_code=400, content={"error": f"Mask type not found: id={req.type}"})
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image = decode_base64_to_image(req.image)
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mask = decode_base64_to_image(req.mask) if req.mask else None
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for k, v in req.params.items():
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if not hasattr(masking.opts, k):
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return JSONResponse(status_code=400, content={"error": f"Mask invalid parameter: {k}={v}"})
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else:
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setattr(masking.opts, k, v)
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shared.state.begin('api-mask', api=True)
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with self.queue_lock:
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processed = masking.run_mask(input_image=image, input_mask=mask, return_type=req.type)
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shared.state.end(api=False)
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if processed is None:
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return JSONResponse(status_code=400, content={"error": "Mask is none"})
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image = encode_pil_to_base64(processed)
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return ResMask(mask=image)
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