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mirror of https://github.com/vladmandic/automatic synced 2026-09-19 09:14:35 +02:00
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modernize typing

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Vladimir Mandic
2026-02-19 09:15:37 +01:00
parent 7aded79e8a
commit bfe014f5da
222 changed files with 1538 additions and 1444 deletions
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modules/api/process.py
+14 -15
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@@ -1,4 +1,3 @@
from typing import Optional, List
from threading import Lock
from pydantic import BaseModel, Field # pylint: disable=no-name-in-module
from fastapi.responses import JSONResponse
@@ -15,7 +14,7 @@ errors.install()
class ReqPreprocess(BaseModel):
image: str = Field(title="Image", description="The base64 encoded image")
model: str = Field(title="Model", description="The model to use for preprocessing")
params: Optional[dict] = Field(default={}, title="Settings", description="Preprocessor settings")
params: dict | None = Field(default={}, title="Settings", description="Preprocessor settings")
class ResPreprocess(BaseModel):
model: str = Field(default='', title="Model", description="The processor model used")
@@ -24,20 +23,20 @@ class ResPreprocess(BaseModel):
class ReqMask(BaseModel):
image: str = Field(title="Image", description="The base64 encoded image")
type: str = Field(title="Mask type", description="Type of masking image to return")
mask: Optional[str] = Field(title="Mask", description="If optional maks image is not provided auto-masking will be performed")
model: Optional[str] = Field(title="Model", description="The model to use for preprocessing")
params: Optional[dict] = Field(default={}, title="Settings", description="Preprocessor settings")
mask: str | None = Field(title="Mask", description="If optional maks image is not provided auto-masking will be performed")
model: str | None = Field(title="Model", description="The model to use for preprocessing")
params: dict | None = Field(default={}, title="Settings", description="Preprocessor settings")
class ReqFace(BaseModel):
image: str = Field(title="Image", description="The base64 encoded image")
model: Optional[str] = Field(title="Model", description="The model to use for detection")
model: str | None = Field(title="Model", description="The model to use for detection")
class ResFace(BaseModel):
classes: List[int] = Field(title="Class", description="The class of detected item")
labels: List[str] = Field(title="Label", description="The label of detected item")
boxes: List[List[int]] = Field(title="Box", description="The bounding box of detected item")
images: List[str] = Field(title="Image", description="The base64 encoded images of detected faces")
scores: List[float] = Field(title="Scores", description="The scores of the detected faces")
classes: list[int] = Field(title="Class", description="The class of detected item")
labels: list[str] = Field(title="Label", description="The label of detected item")
boxes: list[list[int]] = Field(title="Box", description="The bounding box of detected item")
images: list[str] = Field(title="Image", description="The base64 encoded images of detected faces")
scores: list[float] = Field(title="Scores", description="The scores of the detected faces")
class ResMask(BaseModel):
mask: str = Field(default='', title="Image", description="The processed image in base64 format")
@@ -47,13 +46,13 @@ class ItemPreprocess(BaseModel):
params: dict = Field(title="Params")
class ItemMask(BaseModel):
models: List[str] = Field(title="Models")
colormaps: List[str] = Field(title="Color maps")
models: list[str] = Field(title="Models")
colormaps: list[str] = Field(title="Color maps")
params: dict = Field(title="Params")
types: List[str] = Field(title="Types")
types: list[str] = Field(title="Types")
class APIProcess():
class APIProcess:
def __init__(self, queue_lock: Lock):
self.queue_lock = queue_lock