mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
merge with main
This commit is contained in:
Lincoln Stein
commit
87a5b771c4
@ -26,7 +26,7 @@ from invokeai.backend.model_manager.config import (
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from ..dependencies import ApiDependencies
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model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2"])
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model_records_router = APIRouter(prefix="/v1/model/record", tags=["model_manager_v2_unstable"])
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class ModelsList(BaseModel):
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@ -77,7 +77,7 @@ class CalculateImageTilesInvocation(BaseInvocation):
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title="Calculate Image Tiles Even Split",
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tags=["tiles"],
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category="tiles",
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version="1.0.0",
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version="1.1.0",
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classification=Classification.Beta,
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)
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class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
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@ -97,11 +97,11 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
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ge=1,
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description="Number of tiles to divide image into on the y axis",
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)
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overlap_fraction: float = InputField(
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default=0.25,
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overlap: int = InputField(
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default=128,
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ge=0,
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lt=1,
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description="Overlap between adjacent tiles as a fraction of the tile's dimensions (0-1)",
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multiple_of=8,
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description="The overlap, in pixels, between adjacent tiles.",
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)
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def invoke(self, context: InvocationContext) -> CalculateImageTilesOutput:
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@ -110,7 +110,7 @@ class CalculateImageTilesEvenSplitInvocation(BaseInvocation):
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image_width=self.image_width,
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num_tiles_x=self.num_tiles_x,
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num_tiles_y=self.num_tiles_y,
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overlap_fraction=self.overlap_fraction,
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overlap=self.overlap,
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)
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return CalculateImageTilesOutput(tiles=tiles)
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@ -5,6 +5,7 @@ from invokeai.app.services.image_files.image_files_base import ImageFileStorageB
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from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
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from invokeai.app.services.shared.sqlite_migrator.migrations.migration_1 import build_migration_1
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from invokeai.app.services.shared.sqlite_migrator.migrations.migration_2 import build_migration_2
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from invokeai.app.services.shared.sqlite_migrator.migrations.migration_3 import build_migration_3
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from invokeai.app.services.shared.sqlite_migrator.migrations.migration_4 import build_migration_4
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from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_impl import SqliteMigrator
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@ -28,6 +29,7 @@ def init_db(config: InvokeAIAppConfig, logger: Logger, image_files: ImageFileSto
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migrator = SqliteMigrator(db=db)
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migrator.register_migration(build_migration_1())
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migrator.register_migration(build_migration_2(image_files=image_files, logger=logger))
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migrator.register_migration(build_migration_3())
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migrator.register_migration(build_migration_4())
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migrator.run_migrations()
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@ -11,6 +11,8 @@ from invokeai.app.services.workflow_records.workflow_records_common import (
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UnsafeWorkflowWithVersionValidator,
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)
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from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
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class Migration2Callback:
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def __init__(self, image_files: ImageFileStorageBase, logger: Logger):
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@ -24,6 +26,7 @@ class Migration2Callback:
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self._add_workflow_library(cursor)
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self._drop_model_manager_metadata(cursor)
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self._recreate_model_config(cursor)
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self._migrate_model_config_records(cursor)
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self._migrate_embedded_workflows(cursor)
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def _add_images_has_workflow(self, cursor: sqlite3.Cursor) -> None:
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@ -131,6 +134,11 @@ class Migration2Callback:
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"""
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)
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def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
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"""After updating the model config table, we repopulate it."""
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model_record_migrator = MigrateModelYamlToDb1(cursor)
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model_record_migrator.migrate()
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def _migrate_embedded_workflows(self, cursor: sqlite3.Cursor) -> None:
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"""
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In the v3.5.0 release, InvokeAI changed how it handles embedded workflows. The `images` table in
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@ -0,0 +1,75 @@
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import sqlite3
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from invokeai.app.services.shared.sqlite_migrator.sqlite_migrator_common import Migration
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from .util.migrate_yaml_config_1 import MigrateModelYamlToDb1
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class Migration3Callback:
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def __init__(self) -> None:
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pass
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def __call__(self, cursor: sqlite3.Cursor) -> None:
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self._drop_model_manager_metadata(cursor)
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self._recreate_model_config(cursor)
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self._migrate_model_config_records(cursor)
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def _drop_model_manager_metadata(self, cursor: sqlite3.Cursor) -> None:
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"""Drops the `model_manager_metadata` table."""
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cursor.execute("DROP TABLE IF EXISTS model_manager_metadata;")
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def _recreate_model_config(self, cursor: sqlite3.Cursor) -> None:
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"""
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Drops the `model_config` table, recreating it.
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In 3.4.0, this table used explicit columns but was changed to use json_extract 3.5.0.
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Because this table is not used in production, we are able to simply drop it and recreate it.
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"""
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cursor.execute("DROP TABLE IF EXISTS model_config;")
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cursor.execute(
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"""--sql
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CREATE TABLE IF NOT EXISTS model_config (
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id TEXT NOT NULL PRIMARY KEY,
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-- The next 3 fields are enums in python, unrestricted string here
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base TEXT GENERATED ALWAYS as (json_extract(config, '$.base')) VIRTUAL NOT NULL,
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type TEXT GENERATED ALWAYS as (json_extract(config, '$.type')) VIRTUAL NOT NULL,
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name TEXT GENERATED ALWAYS as (json_extract(config, '$.name')) VIRTUAL NOT NULL,
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path TEXT GENERATED ALWAYS as (json_extract(config, '$.path')) VIRTUAL NOT NULL,
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format TEXT GENERATED ALWAYS as (json_extract(config, '$.format')) VIRTUAL NOT NULL,
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original_hash TEXT, -- could be null
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-- Serialized JSON representation of the whole config object,
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-- which will contain additional fields from subclasses
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config TEXT NOT NULL,
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created_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
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-- Updated via trigger
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updated_at DATETIME NOT NULL DEFAULT(STRFTIME('%Y-%m-%d %H:%M:%f', 'NOW')),
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-- unique constraint on combo of name, base and type
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UNIQUE(name, base, type)
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);
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"""
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)
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def _migrate_model_config_records(self, cursor: sqlite3.Cursor) -> None:
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"""After updating the model config table, we repopulate it."""
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model_record_migrator = MigrateModelYamlToDb1(cursor)
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model_record_migrator.migrate()
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def build_migration_3() -> Migration:
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"""
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Build the migration from database version 2 to 3.
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This migration does the following:
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- Drops the `model_config` table, recreating it
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- Migrates data from `models.yaml` into the `model_config` table
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"""
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migration_3 = Migration(
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from_version=2,
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to_version=3,
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callback=Migration3Callback(),
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)
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return migration_3
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@ -86,8 +86,8 @@ def build_migration_4() -> Migration:
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Adds the tables needed to store model metadata and tags.
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"""
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migration_4 = Migration(
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from_version=2, # until migration_3 is merged, pretend we are doing 2-3
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to_version=3,
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from_version=3,
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to_version=4,
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callback=Migration4Callback(),
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)
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@ -1,8 +1,12 @@
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# Copyright (c) 2023 Lincoln D. Stein
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"""Migrate from the InvokeAI v2 models.yaml format to the v3 sqlite format."""
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import json
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import sqlite3
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from hashlib import sha1
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from logging import Logger
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from pathlib import Path
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from typing import Optional
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from omegaconf import DictConfig, OmegaConf
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from pydantic import TypeAdapter
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@ -10,13 +14,12 @@ from pydantic import TypeAdapter
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from invokeai.app.services.config import InvokeAIAppConfig
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from invokeai.app.services.model_records import (
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DuplicateModelException,
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ModelRecordServiceSQL,
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UnknownModelException,
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)
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from invokeai.app.services.shared.sqlite.sqlite_database import SqliteDatabase
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from invokeai.backend.model_manager.config import (
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AnyModelConfig,
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BaseModelType,
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ModelConfigFactory,
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ModelType,
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)
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from invokeai.backend.model_manager.hash import FastModelHash
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@ -25,9 +28,9 @@ from invokeai.backend.util.logging import InvokeAILogger
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ModelsValidator = TypeAdapter(AnyModelConfig)
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class MigrateModelYamlToDb:
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class MigrateModelYamlToDb1:
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"""
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Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.2.0)
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Migrate the InvokeAI models.yaml format (VERSION 3.0.0) to SQL3 database format (VERSION 3.5.0).
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The class has one externally useful method, migrate(), which scans the
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currently models.yaml file and imports all its entries into invokeai.db.
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@ -41,17 +44,13 @@ class MigrateModelYamlToDb:
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config: InvokeAIAppConfig
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logger: Logger
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cursor: sqlite3.Cursor
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def __init__(self) -> None:
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def __init__(self, cursor: sqlite3.Cursor = None) -> None:
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self.config = InvokeAIAppConfig.get_config()
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self.config.parse_args()
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self.logger = InvokeAILogger.get_logger()
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def get_db(self) -> ModelRecordServiceSQL:
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"""Fetch the sqlite3 database for this installation."""
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db_path = None if self.config.use_memory_db else self.config.db_path
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db = SqliteDatabase(db_path=db_path, logger=self.logger, verbose=self.config.log_sql)
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return ModelRecordServiceSQL(db)
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self.cursor = cursor
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def get_yaml(self) -> DictConfig:
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"""Fetch the models.yaml DictConfig for this installation."""
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@ -62,8 +61,10 @@ class MigrateModelYamlToDb:
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def migrate(self) -> None:
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"""Do the migration from models.yaml to invokeai.db."""
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db = self.get_db()
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yaml = self.get_yaml()
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try:
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yaml = self.get_yaml()
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except OSError:
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return
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for model_key, stanza in yaml.items():
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if model_key == "__metadata__":
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@ -86,22 +87,62 @@ class MigrateModelYamlToDb:
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new_config: AnyModelConfig = ModelsValidator.validate_python(stanza) # type: ignore # see https://github.com/pydantic/pydantic/discussions/7094
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try:
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if original_record := db.search_by_path(stanza.path):
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key = original_record[0].key
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if original_record := self._search_by_path(stanza.path):
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key = original_record.key
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self.logger.info(f"Updating model {model_name} with information from models.yaml using key {key}")
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db.update_model(key, new_config)
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self._update_model(key, new_config)
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else:
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self.logger.info(f"Adding model {model_name} with key {model_key}")
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db.add_model(new_key, new_config)
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self._add_model(new_key, new_config)
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except DuplicateModelException:
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self.logger.warning(f"Model {model_name} is already in the database")
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except UnknownModelException:
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self.logger.warning(f"Model at {stanza.path} could not be found in database")
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def _search_by_path(self, path: Path) -> Optional[AnyModelConfig]:
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self.cursor.execute(
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"""--sql
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SELECT config FROM model_config
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WHERE path=?;
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""",
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(str(path),),
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)
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results = [ModelConfigFactory.make_config(json.loads(x[0])) for x in self.cursor.fetchall()]
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return results[0] if results else None
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def main():
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MigrateModelYamlToDb().migrate()
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def _update_model(self, key: str, config: AnyModelConfig) -> None:
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record = ModelConfigFactory.make_config(config, key=key) # ensure it is a valid config obect
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json_serialized = record.model_dump_json() # and turn it into a json string.
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self.cursor.execute(
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"""--sql
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UPDATE model_config
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SET
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config=?
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WHERE id=?;
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""",
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(json_serialized, key),
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)
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if self.cursor.rowcount == 0:
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raise UnknownModelException("model not found")
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if __name__ == "__main__":
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main()
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def _add_model(self, key: str, config: AnyModelConfig) -> None:
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record = ModelConfigFactory.make_config(config, key=key) # ensure it is a valid config obect.
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json_serialized = record.model_dump_json() # and turn it into a json string.
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try:
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self.cursor.execute(
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"""--sql
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INSERT INTO model_config (
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id,
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original_hash,
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config
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)
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VALUES (?,?,?);
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""",
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(
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key,
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record.original_hash,
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json_serialized,
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),
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)
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except sqlite3.IntegrityError as exc:
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raise DuplicateModelException(f"{record.name}: model is already in database") from exc
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@ -389,7 +389,7 @@ class TextualInversionCheckpointProbe(CheckpointProbeBase):
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elif "clip_g" in checkpoint:
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token_dim = checkpoint["clip_g"].shape[-1]
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else:
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token_dim = list(checkpoint.values())[0].shape[0]
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token_dim = list(checkpoint.values())[0].shape[-1]
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if token_dim == 768:
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return BaseModelType.StableDiffusion1
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elif token_dim == 1024:
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@ -102,7 +102,7 @@ def calc_tiles_with_overlap(
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def calc_tiles_even_split(
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image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap_fraction: float = 0
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image_height: int, image_width: int, num_tiles_x: int, num_tiles_y: int, overlap: int = 0
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) -> list[Tile]:
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"""Calculate the tile coordinates for a given image shape with the number of tiles requested.
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@ -111,31 +111,35 @@ def calc_tiles_even_split(
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image_width (int): The image width in px.
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num_x_tiles (int): The number of tile to split the image into on the X-axis.
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num_y_tiles (int): The number of tile to split the image into on the Y-axis.
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overlap_fraction (float, optional): The target overlap as fraction of the tiles size. Defaults to 0.
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overlap (int, optional): The overlap between adjacent tiles in pixels. Defaults to 0.
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Returns:
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list[Tile]: A list of tiles that cover the image shape. Ordered from left-to-right, top-to-bottom.
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"""
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# Ensure tile size is divisible by 8
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# Ensure the image is divisible by LATENT_SCALE_FACTOR
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if image_width % LATENT_SCALE_FACTOR != 0 or image_height % LATENT_SCALE_FACTOR != 0:
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raise ValueError(f"image size (({image_width}, {image_height})) must be divisible by {LATENT_SCALE_FACTOR}")
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# Calculate the overlap size based on the percentage and adjust it to be divisible by 8 (rounding up)
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overlap_x = LATENT_SCALE_FACTOR * math.ceil(
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int((image_width / num_tiles_x) * overlap_fraction) / LATENT_SCALE_FACTOR
|
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)
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overlap_y = LATENT_SCALE_FACTOR * math.ceil(
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int((image_height / num_tiles_y) * overlap_fraction) / LATENT_SCALE_FACTOR
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)
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# Calculate the tile size based on the number of tiles and overlap, and ensure it's divisible by 8 (rounding down)
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tile_size_x = LATENT_SCALE_FACTOR * math.floor(
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((image_width + overlap_x * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
|
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)
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tile_size_y = LATENT_SCALE_FACTOR * math.floor(
|
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((image_height + overlap_y * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
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)
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if num_tiles_x > 1:
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# ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
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assert overlap <= image_width - (LATENT_SCALE_FACTOR * (num_tiles_x - 1))
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tile_size_x = LATENT_SCALE_FACTOR * math.floor(
|
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((image_width + overlap * (num_tiles_x - 1)) // num_tiles_x) / LATENT_SCALE_FACTOR
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)
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assert overlap < tile_size_x
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else:
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tile_size_x = image_width
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|
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if num_tiles_y > 1:
|
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# ensure the overlap is not more than the maximum overlap if we only have 1 tile then we dont care about overlap
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assert overlap <= image_height - (LATENT_SCALE_FACTOR * (num_tiles_y - 1))
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tile_size_y = LATENT_SCALE_FACTOR * math.floor(
|
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((image_height + overlap * (num_tiles_y - 1)) // num_tiles_y) / LATENT_SCALE_FACTOR
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)
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assert overlap < tile_size_y
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else:
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tile_size_y = image_height
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|
||||
# tiles[y * num_tiles_x + x] is the tile for the y'th row, x'th column.
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tiles: list[Tile] = []
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@ -143,7 +147,7 @@ def calc_tiles_even_split(
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# Calculate tile coordinates. (Ignore overlap values for now.)
|
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for tile_idx_y in range(num_tiles_y):
|
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# Calculate the top and bottom of the row
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top = tile_idx_y * (tile_size_y - overlap_y)
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top = tile_idx_y * (tile_size_y - overlap)
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bottom = min(top + tile_size_y, image_height)
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# For the last row adjust bottom to be the height of the image
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if tile_idx_y == num_tiles_y - 1:
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@ -151,7 +155,7 @@ def calc_tiles_even_split(
|
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|
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for tile_idx_x in range(num_tiles_x):
|
||||
# Calculate the left & right coordinate of each tile
|
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left = tile_idx_x * (tile_size_x - overlap_x)
|
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left = tile_idx_x * (tile_size_x - overlap)
|
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right = min(left + tile_size_x, image_width)
|
||||
# For the last tile in the row adjust right to be the width of the image
|
||||
if tile_idx_x == num_tiles_x - 1:
|
||||
|
||||
@ -4,6 +4,7 @@ pip install <path_to_git_source>.
|
||||
"""
|
||||
import os
|
||||
import platform
|
||||
from distutils.version import LooseVersion
|
||||
|
||||
import pkg_resources
|
||||
import psutil
|
||||
@ -31,10 +32,6 @@ else:
|
||||
console = Console(style=Style(color="grey74", bgcolor="grey19"))
|
||||
|
||||
|
||||
def get_versions() -> dict:
|
||||
return requests.get(url=INVOKE_AI_REL).json()
|
||||
|
||||
|
||||
def invokeai_is_running() -> bool:
|
||||
for p in psutil.process_iter():
|
||||
try:
|
||||
@ -50,6 +47,20 @@ def invokeai_is_running() -> bool:
|
||||
return False
|
||||
|
||||
|
||||
def get_pypi_versions():
|
||||
url = "https://pypi.org/pypi/invokeai/json"
|
||||
try:
|
||||
data = requests.get(url).json()
|
||||
except Exception:
|
||||
raise Exception("Unable to fetch version information from PyPi")
|
||||
|
||||
versions = list(data["releases"].keys())
|
||||
versions.sort(key=LooseVersion, reverse=True)
|
||||
latest_version = [v for v in versions if "rc" not in v][0]
|
||||
latest_release_candidate = [v for v in versions if "rc" in v][0]
|
||||
return latest_version, latest_release_candidate, versions
|
||||
|
||||
|
||||
def welcome(latest_release: str, latest_prerelease: str):
|
||||
@group()
|
||||
def text():
|
||||
@ -63,8 +74,7 @@ def welcome(latest_release: str, latest_prerelease: str):
|
||||
yield "[bold yellow]Options:"
|
||||
yield f"""[1] Update to the latest [bold]official release[/bold] ([italic]{latest_release}[/italic])
|
||||
[2] Update to the latest [bold]pre-release[/bold] (may be buggy; caveat emptor!) ([italic]{latest_prerelease}[/italic])
|
||||
[3] Manually enter the [bold]tag name[/bold] for the version you wish to update to
|
||||
[4] Manually enter the [bold]branch name[/bold] for the version you wish to update to"""
|
||||
[3] Manually enter the [bold]version[/bold] you wish to update to"""
|
||||
|
||||
console.rule()
|
||||
print(
|
||||
@ -92,44 +102,35 @@ def get_extras():
|
||||
|
||||
|
||||
def main():
|
||||
versions = get_versions()
|
||||
released_versions = [x for x in versions if not (x["draft"] or x["prerelease"])]
|
||||
prerelease_versions = [x for x in versions if not x["draft"] and x["prerelease"]]
|
||||
latest_release = released_versions[0]["tag_name"] if len(released_versions) else None
|
||||
latest_prerelease = prerelease_versions[0]["tag_name"] if len(prerelease_versions) else None
|
||||
|
||||
if invokeai_is_running():
|
||||
print(":exclamation: [bold red]Please terminate all running instances of InvokeAI before updating.[/red bold]")
|
||||
input("Press any key to continue...")
|
||||
return
|
||||
|
||||
latest_release, latest_prerelease, versions = get_pypi_versions()
|
||||
|
||||
welcome(latest_release, latest_prerelease)
|
||||
|
||||
tag = None
|
||||
branch = None
|
||||
release = None
|
||||
choice = Prompt.ask("Choice:", choices=["1", "2", "3", "4"], default="1")
|
||||
release = latest_release
|
||||
choice = Prompt.ask("Choice:", choices=["1", "2", "3"], default="1")
|
||||
|
||||
if choice == "1":
|
||||
release = latest_release
|
||||
elif choice == "2":
|
||||
release = latest_prerelease
|
||||
elif choice == "3":
|
||||
while not tag:
|
||||
tag = Prompt.ask("Enter an InvokeAI tag name")
|
||||
elif choice == "4":
|
||||
while not branch:
|
||||
branch = Prompt.ask("Enter an InvokeAI branch name")
|
||||
while True:
|
||||
release = Prompt.ask("Enter an InvokeAI version")
|
||||
release.strip()
|
||||
if release in versions:
|
||||
break
|
||||
print(f":exclamation: [bold red]'{release}' is not a recognized InvokeAI release.[/red bold]")
|
||||
|
||||
extras = get_extras()
|
||||
|
||||
print(f":crossed_fingers: Upgrading to [yellow]{tag or release or branch}[/yellow]")
|
||||
if release:
|
||||
cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_SRC}/{release}.zip" --use-pep517 --upgrade'
|
||||
elif tag:
|
||||
cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_TAG}/{tag}.zip" --use-pep517 --upgrade'
|
||||
else:
|
||||
cmd = f'pip install "invokeai{extras} @ {INVOKE_AI_BRANCH}/{branch}.zip" --use-pep517 --upgrade'
|
||||
print(f":crossed_fingers: Upgrading to [yellow]{release}[/yellow]")
|
||||
cmd = f'pip install "invokeai{extras}=={release}" --use-pep517 --upgrade'
|
||||
|
||||
print("")
|
||||
print("")
|
||||
if os.system(cmd) == 0:
|
||||
|
||||
@ -1109,7 +1109,10 @@
|
||||
"deletedInvalidEdge": "Eliminata connessione non valida {{source}} -> {{target}}",
|
||||
"unknownInput": "Input sconosciuto: {{name}}",
|
||||
"prototypeDesc": "Questa invocazione è un prototipo. Potrebbe subire modifiche sostanziali durante gli aggiornamenti dell'app e potrebbe essere rimossa in qualsiasi momento.",
|
||||
"betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine."
|
||||
"betaDesc": "Questa invocazione è in versione beta. Fino a quando non sarà stabile, potrebbe subire modifiche importanti durante gli aggiornamenti dell'app. Abbiamo intenzione di supportare questa invocazione a lungo termine.",
|
||||
"newWorkflow": "Nuovo flusso di lavoro",
|
||||
"newWorkflowDesc": "Creare un nuovo flusso di lavoro?",
|
||||
"newWorkflowDesc2": "Il flusso di lavoro attuale presenta modifiche non salvate."
|
||||
},
|
||||
"boards": {
|
||||
"autoAddBoard": "Aggiungi automaticamente bacheca",
|
||||
@ -1629,7 +1632,10 @@
|
||||
"deleteWorkflow": "Elimina flusso di lavoro",
|
||||
"workflows": "Flussi di lavoro",
|
||||
"noDescription": "Nessuna descrizione",
|
||||
"userWorkflows": "I miei flussi di lavoro"
|
||||
"userWorkflows": "I miei flussi di lavoro",
|
||||
"newWorkflowCreated": "Nuovo flusso di lavoro creato",
|
||||
"downloadWorkflow": "Salva su file",
|
||||
"uploadWorkflow": "Carica da file"
|
||||
},
|
||||
"app": {
|
||||
"storeNotInitialized": "Il negozio non è inizializzato"
|
||||
|
||||
@ -138,7 +138,6 @@ dependencies = [
|
||||
"invokeai-node-web" = "invokeai.app.api_app:invoke_api"
|
||||
"invokeai-import-images" = "invokeai.frontend.install.import_images:main"
|
||||
"invokeai-db-maintenance" = "invokeai.backend.util.db_maintenance:main"
|
||||
"invokeai-migrate-models-to-db" = "invokeai.backend.model_manager.migrate_to_db:main"
|
||||
|
||||
[project.urls]
|
||||
"Homepage" = "https://invoke-ai.github.io/InvokeAI/"
|
||||
|
||||
@ -305,9 +305,7 @@ def test_calc_tiles_min_overlap_input_validation(
|
||||
|
||||
def test_calc_tiles_even_split_single_tile():
|
||||
"""Test calc_tiles_even_split() behavior when a single tile covers the image."""
|
||||
tiles = calc_tiles_even_split(
|
||||
image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap_fraction=0.25
|
||||
)
|
||||
tiles = calc_tiles_even_split(image_height=512, image_width=1024, num_tiles_x=1, num_tiles_y=1, overlap=64)
|
||||
|
||||
expected_tiles = [
|
||||
Tile(
|
||||
@ -322,36 +320,34 @@ def test_calc_tiles_even_split_single_tile():
|
||||
def test_calc_tiles_even_split_evenly_divisible():
|
||||
"""Test calc_tiles_even_split() behavior when the image is evenly covered by multiple tiles."""
|
||||
# Parameters mimic roughly the same output as the original tile generations of the same test name
|
||||
tiles = calc_tiles_even_split(
|
||||
image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
|
||||
)
|
||||
tiles = calc_tiles_even_split(image_height=576, image_width=1600, num_tiles_x=3, num_tiles_y=2, overlap=64)
|
||||
|
||||
expected_tiles = [
|
||||
# Row 0
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=320, left=0, right=624),
|
||||
overlap=TBLR(top=0, bottom=72, left=0, right=136),
|
||||
coords=TBLR(top=0, bottom=320, left=0, right=576),
|
||||
overlap=TBLR(top=0, bottom=64, left=0, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=320, left=488, right=1112),
|
||||
overlap=TBLR(top=0, bottom=72, left=136, right=136),
|
||||
coords=TBLR(top=0, bottom=320, left=512, right=1088),
|
||||
overlap=TBLR(top=0, bottom=64, left=64, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=320, left=976, right=1600),
|
||||
overlap=TBLR(top=0, bottom=72, left=136, right=0),
|
||||
coords=TBLR(top=0, bottom=320, left=1024, right=1600),
|
||||
overlap=TBLR(top=0, bottom=64, left=64, right=0),
|
||||
),
|
||||
# Row 1
|
||||
Tile(
|
||||
coords=TBLR(top=248, bottom=576, left=0, right=624),
|
||||
overlap=TBLR(top=72, bottom=0, left=0, right=136),
|
||||
coords=TBLR(top=256, bottom=576, left=0, right=576),
|
||||
overlap=TBLR(top=64, bottom=0, left=0, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=248, bottom=576, left=488, right=1112),
|
||||
overlap=TBLR(top=72, bottom=0, left=136, right=136),
|
||||
coords=TBLR(top=256, bottom=576, left=512, right=1088),
|
||||
overlap=TBLR(top=64, bottom=0, left=64, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=248, bottom=576, left=976, right=1600),
|
||||
overlap=TBLR(top=72, bottom=0, left=136, right=0),
|
||||
coords=TBLR(top=256, bottom=576, left=1024, right=1600),
|
||||
overlap=TBLR(top=64, bottom=0, left=64, right=0),
|
||||
),
|
||||
]
|
||||
assert tiles == expected_tiles
|
||||
@ -360,36 +356,34 @@ def test_calc_tiles_even_split_evenly_divisible():
|
||||
def test_calc_tiles_even_split_not_evenly_divisible():
|
||||
"""Test calc_tiles_even_split() behavior when the image requires 'uneven' overlaps to achieve proper coverage."""
|
||||
# Parameters mimic roughly the same output as the original tile generations of the same test name
|
||||
tiles = calc_tiles_even_split(
|
||||
image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap_fraction=0.25
|
||||
)
|
||||
tiles = calc_tiles_even_split(image_height=400, image_width=1200, num_tiles_x=3, num_tiles_y=2, overlap=64)
|
||||
|
||||
expected_tiles = [
|
||||
# Row 0
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=224, left=0, right=464),
|
||||
overlap=TBLR(top=0, bottom=56, left=0, right=104),
|
||||
coords=TBLR(top=0, bottom=232, left=0, right=440),
|
||||
overlap=TBLR(top=0, bottom=64, left=0, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=224, left=360, right=824),
|
||||
overlap=TBLR(top=0, bottom=56, left=104, right=104),
|
||||
coords=TBLR(top=0, bottom=232, left=376, right=816),
|
||||
overlap=TBLR(top=0, bottom=64, left=64, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=224, left=720, right=1200),
|
||||
overlap=TBLR(top=0, bottom=56, left=104, right=0),
|
||||
coords=TBLR(top=0, bottom=232, left=752, right=1200),
|
||||
overlap=TBLR(top=0, bottom=64, left=64, right=0),
|
||||
),
|
||||
# Row 1
|
||||
Tile(
|
||||
coords=TBLR(top=168, bottom=400, left=0, right=464),
|
||||
overlap=TBLR(top=56, bottom=0, left=0, right=104),
|
||||
coords=TBLR(top=168, bottom=400, left=0, right=440),
|
||||
overlap=TBLR(top=64, bottom=0, left=0, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=168, bottom=400, left=360, right=824),
|
||||
overlap=TBLR(top=56, bottom=0, left=104, right=104),
|
||||
coords=TBLR(top=168, bottom=400, left=376, right=816),
|
||||
overlap=TBLR(top=64, bottom=0, left=64, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=168, bottom=400, left=720, right=1200),
|
||||
overlap=TBLR(top=56, bottom=0, left=104, right=0),
|
||||
coords=TBLR(top=168, bottom=400, left=752, right=1200),
|
||||
overlap=TBLR(top=64, bottom=0, left=64, right=0),
|
||||
),
|
||||
]
|
||||
|
||||
@ -399,28 +393,26 @@ def test_calc_tiles_even_split_not_evenly_divisible():
|
||||
def test_calc_tiles_even_split_difficult_size():
|
||||
"""Test calc_tiles_even_split() behavior when the image is a difficult size to spilt evenly and keep div8."""
|
||||
# Parameters are a difficult size for other tile gen routines to calculate
|
||||
tiles = calc_tiles_even_split(
|
||||
image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap_fraction=0.25
|
||||
)
|
||||
tiles = calc_tiles_even_split(image_height=1000, image_width=1000, num_tiles_x=2, num_tiles_y=2, overlap=64)
|
||||
|
||||
expected_tiles = [
|
||||
# Row 0
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=560, left=0, right=560),
|
||||
overlap=TBLR(top=0, bottom=128, left=0, right=128),
|
||||
coords=TBLR(top=0, bottom=528, left=0, right=528),
|
||||
overlap=TBLR(top=0, bottom=64, left=0, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=0, bottom=560, left=432, right=1000),
|
||||
overlap=TBLR(top=0, bottom=128, left=128, right=0),
|
||||
coords=TBLR(top=0, bottom=528, left=464, right=1000),
|
||||
overlap=TBLR(top=0, bottom=64, left=64, right=0),
|
||||
),
|
||||
# Row 1
|
||||
Tile(
|
||||
coords=TBLR(top=432, bottom=1000, left=0, right=560),
|
||||
overlap=TBLR(top=128, bottom=0, left=0, right=128),
|
||||
coords=TBLR(top=464, bottom=1000, left=0, right=528),
|
||||
overlap=TBLR(top=64, bottom=0, left=0, right=64),
|
||||
),
|
||||
Tile(
|
||||
coords=TBLR(top=432, bottom=1000, left=432, right=1000),
|
||||
overlap=TBLR(top=128, bottom=0, left=128, right=0),
|
||||
coords=TBLR(top=464, bottom=1000, left=464, right=1000),
|
||||
overlap=TBLR(top=64, bottom=0, left=64, right=0),
|
||||
),
|
||||
]
|
||||
|
||||
@ -428,11 +420,13 @@ def test_calc_tiles_even_split_difficult_size():
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap_fraction", "raises"],
|
||||
["image_height", "image_width", "num_tiles_x", "num_tiles_y", "overlap", "raises"],
|
||||
[
|
||||
(128, 128, 1, 1, 0.25, False), # OK
|
||||
(128, 128, 1, 1, 127, False), # OK
|
||||
(128, 128, 1, 1, 0, False), # OK
|
||||
(128, 128, 2, 1, 0, False), # OK
|
||||
(128, 128, 2, 2, 0, False), # OK
|
||||
(128, 128, 2, 1, 120, True), # overlap equals tile_height.
|
||||
(128, 128, 1, 2, 120, True), # overlap equals tile_width.
|
||||
(127, 127, 1, 1, 0, True), # image size must be dividable by 8
|
||||
],
|
||||
)
|
||||
@ -441,15 +435,15 @@ def test_calc_tiles_even_split_input_validation(
|
||||
image_width: int,
|
||||
num_tiles_x: int,
|
||||
num_tiles_y: int,
|
||||
overlap_fraction: float,
|
||||
overlap: int,
|
||||
raises: bool,
|
||||
):
|
||||
"""Test that calc_tiles_even_split() raises an exception if the inputs are invalid."""
|
||||
if raises:
|
||||
with pytest.raises(ValueError):
|
||||
calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
|
||||
with pytest.raises((AssertionError, ValueError)):
|
||||
calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
|
||||
else:
|
||||
calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap_fraction)
|
||||
calc_tiles_even_split(image_height, image_width, num_tiles_x, num_tiles_y, overlap)
|
||||
|
||||
|
||||
#############################################
|
||||
|
||||
Loading…
Reference in New Issue
Block a user