mirror of
https://github.com/invoke-ai/InvokeAI.git
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Merge branch 'main' into refactor/remove_unused_pipeline_methods
This commit is contained in:
@@ -1,22 +1,20 @@
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import io
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from typing import Optional
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from PIL import Image
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from fastapi import Body, HTTPException, Path, Query, Request, Response, UploadFile
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from fastapi.responses import FileResponse
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from fastapi.routing import APIRouter
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from PIL import Image
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from pydantic import BaseModel, Field
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from pydantic import BaseModel
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from invokeai.app.invocations.metadata import ImageMetadata
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from invokeai.app.models.image import ImageCategory, ResourceOrigin
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from invokeai.app.services.image_record_storage import OffsetPaginatedResults
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from invokeai.app.services.item_storage import PaginatedResults
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from invokeai.app.services.models.image_record import (
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ImageDTO,
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ImageRecordChanges,
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ImageUrlsDTO,
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)
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from ..dependencies import ApiDependencies
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images_router = APIRouter(prefix="/v1/images", tags=["images"])
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@@ -152,8 +150,9 @@ async def get_image_metadata(
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raise HTTPException(status_code=404)
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@images_router.get(
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@images_router.api_route(
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"/i/{image_name}/full",
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methods=["GET", "HEAD"],
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operation_id="get_image_full",
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response_class=Response,
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responses={
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@@ -24,11 +24,10 @@ InvokeAI:
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sequential_guidance: false
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precision: float16
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max_cache_size: 6
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max_vram_cache_size: 2.7
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max_vram_cache_size: 0.5
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always_use_cpu: false
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free_gpu_mem: false
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Features:
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restore: true
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esrgan: true
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patchmatch: true
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internet_available: true
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@@ -165,7 +164,7 @@ import pydoc
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import os
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import sys
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from argparse import ArgumentParser
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from omegaconf import OmegaConf, DictConfig
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from omegaconf import OmegaConf, DictConfig, ListConfig
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from pathlib import Path
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from pydantic import BaseSettings, Field, parse_obj_as
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from typing import ClassVar, Dict, List, Set, Literal, Union, get_origin, get_type_hints, get_args
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@@ -173,6 +172,7 @@ from typing import ClassVar, Dict, List, Set, Literal, Union, get_origin, get_ty
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INIT_FILE = Path("invokeai.yaml")
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DB_FILE = Path("invokeai.db")
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LEGACY_INIT_FILE = Path("invokeai.init")
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DEFAULT_MAX_VRAM = 0.5
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class InvokeAISettings(BaseSettings):
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@@ -189,7 +189,12 @@ class InvokeAISettings(BaseSettings):
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opt = parser.parse_args(argv)
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for name in self.__fields__:
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if name not in self._excluded():
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setattr(self, name, getattr(opt, name))
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value = getattr(opt, name)
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if isinstance(value, ListConfig):
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value = list(value)
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elif isinstance(value, DictConfig):
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value = dict(value)
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setattr(self, name, value)
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def to_yaml(self) -> str:
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"""
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@@ -282,14 +287,10 @@ class InvokeAISettings(BaseSettings):
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return [
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"type",
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"initconf",
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"gpu_mem_reserved",
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"max_loaded_models",
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"version",
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"from_file",
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"model",
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"restore",
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"root",
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"nsfw_checker",
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]
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class Config:
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@@ -388,15 +389,11 @@ class InvokeAIAppConfig(InvokeAISettings):
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internet_available : bool = Field(default=True, description="If true, attempt to download models on the fly; otherwise only use local models", category='Features')
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log_tokenization : bool = Field(default=False, description="Enable logging of parsed prompt tokens.", category='Features')
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patchmatch : bool = Field(default=True, description="Enable/disable patchmatch inpaint code", category='Features')
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restore : bool = Field(default=True, description="Enable/disable face restoration code (DEPRECATED)", category='DEPRECATED')
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always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", category='Memory/Performance')
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free_gpu_mem : bool = Field(default=False, description="If true, purge model from GPU after each generation.", category='Memory/Performance')
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max_loaded_models : int = Field(default=3, gt=0, description="(DEPRECATED: use max_cache_size) Maximum number of models to keep in memory for rapid switching", category='DEPRECATED')
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max_cache_size : float = Field(default=6.0, gt=0, description="Maximum memory amount used by model cache for rapid switching", category='Memory/Performance')
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max_vram_cache_size : float = Field(default=2.75, ge=0, description="Amount of VRAM reserved for model storage", category='Memory/Performance')
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gpu_mem_reserved : float = Field(default=2.75, ge=0, description="DEPRECATED: use max_vram_cache_size. Amount of VRAM reserved for model storage", category='DEPRECATED')
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nsfw_checker : bool = Field(default=True, description="DEPRECATED: use Web settings to enable/disable", category='DEPRECATED')
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precision : Literal[tuple(['auto','float16','float32','autocast'])] = Field(default='auto',description='Floating point precision', category='Memory/Performance')
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sequential_guidance : bool = Field(default=False, description="Whether to calculate guidance in serial instead of in parallel, lowering memory requirements", category='Memory/Performance')
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xformers_enabled : bool = Field(default=True, description="Enable/disable memory-efficient attention", category='Memory/Performance')
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@@ -414,9 +411,7 @@ class InvokeAIAppConfig(InvokeAISettings):
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outdir : Path = Field(default='outputs', description='Default folder for output images', category='Paths')
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from_file : Path = Field(default=None, description='Take command input from the indicated file (command-line client only)', category='Paths')
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use_memory_db : bool = Field(default=False, description='Use in-memory database for storing image metadata', category='Paths')
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ignore_missing_core_models : bool = Field(default=False, description='Ignore missing models in models/core/convert')
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model : str = Field(default='stable-diffusion-1.5', description='Initial model name', category='Models')
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ignore_missing_core_models : bool = Field(default=False, description='Ignore missing models in models/core/convert', category='Features')
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log_handlers : List[str] = Field(default=["console"], description='Log handler. Valid options are "console", "file=<path>", "syslog=path|address:host:port", "http=<url>"', category="Logging")
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# note - would be better to read the log_format values from logging.py, but this creates circular dependencies issues
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@@ -426,6 +421,9 @@ class InvokeAIAppConfig(InvokeAISettings):
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version : bool = Field(default=False, description="Show InvokeAI version and exit", category="Other")
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# fmt: on
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class Config:
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validate_assignment = True
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def parse_args(self, argv: List[str] = None, conf: DictConfig = None, clobber=False):
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"""
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Update settings with contents of init file, environment, and
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