mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
fix broken scripts
This PR fixes the following scripts: 1) Scripts that can be executed within the repo's scripts directory. Note that these are for development testing and are not intended to be exposed to the user. configure_invokeai.py - configuration dream.py - the legacy CLI images2prompt.py - legacy "dream prompt" retriever invoke-new.py - new nodes-based CLI invoke.py - the legacy CLI under another name make_models_markdown_table.py - a utility used during the release/doc process pypi_helper.py - another utility used during the release process sd-metadata.py - retrieve JSON-formatted metadata from a PNG file 2) Scripts that are installed by pip install. They get placed into the venv's PATH and are intended to be the official entry points: invokeai-node-cli - new nodes-based CLI invokeai-node-web - new nodes-based web server invokeai - legacy CLI invokeai-configure - install time configuration script invokeai-merge - model merging script invokeai-ti - textual inversion script invokeai-model-install - model installer invokeai-update - update script invokeai-metadata" - retrieve JSON-formatted metadata from PNG files
This commit is contained in:
Lincoln Stein
parent
b3dccfaeb6
commit
bdc7b8b75a
@ -3,7 +3,7 @@
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import os
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from argparse import Namespace
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from ...globals import Globals
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from ...backend import Globals
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from ..services.generate_initializer import get_generate
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from ..services.graph import GraphExecutionState
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from ..services.image_storage import DiskImageStorage
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@ -13,7 +13,7 @@ from fastapi_events.handlers.local import local_handler
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from fastapi_events.middleware import EventHandlerASGIMiddleware
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from pydantic.schema import schema
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from ..args import Args
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from ..backend import Args
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from .api.dependencies import ApiDependencies
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from .api.routers import images, sessions
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from .api.sockets import SocketIO
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@ -18,7 +18,7 @@ from typing import (
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from pydantic import BaseModel
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from pydantic.fields import Field
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from ..args import Args
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from ..backend import Args
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from .invocations import *
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from .invocations.baseinvocation import BaseInvocation
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from .invocations.image import ImageField
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@ -6,7 +6,7 @@ from argparse import Namespace
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import invokeai.version
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from invokeai.backend import Generate, ModelManager
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from ...globals import Globals
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from ...backend import Globals
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# TODO: most of this code should be split into individual services as the Generate.py code is deprecated
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@ -3,3 +3,5 @@ Initialization file for invokeai.backend
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"""
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from .generate import Generate
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from .model_management import ModelManager
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from .args import Args
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from .globals import Globals
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30
invokeai/frontend/CLI/sd_metadata.py
Normal file
30
invokeai/frontend/CLI/sd_metadata.py
Normal file
@ -0,0 +1,30 @@
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'''
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This is a modularized version of the sd-metadata.py script,
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which retrieves and prints the metadata from a series of generated png files.
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'''
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import sys
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import json
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from invokeai.backend.image_util import retrieve_metadata
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def print_metadata():
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if len(sys.argv) < 2:
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print("Usage: file2prompt.py <file1.png> <file2.png> <file3.png>...")
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print("This script opens up the indicated invoke.py-generated PNG file(s) and prints out their metadata.")
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exit(-1)
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filenames = sys.argv[1:]
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for f in filenames:
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try:
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metadata = retrieve_metadata(f)
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print(f'{f}:\n',json.dumps(metadata['sd-metadata'], indent=4))
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except FileNotFoundError:
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sys.stderr.write(f'{f} not found\n')
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continue
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except PermissionError:
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sys.stderr.write(f'{f} could not be opened due to inadequate permissions\n')
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continue
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if __name__== '__main__':
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print_metadata()
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@ -104,7 +104,7 @@ dependencies = [
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[project.scripts]
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# legacy entrypoints; provided for backwards compatibility
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"invoke.py" = "invokeai.frontend.CLI:command_line_interface"
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"invoke.py" = "invokeai.frontend.CLI:invokeai_command_line_interface"
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"configure_invokeai.py" = "invokeai.frontend.install:invokeai_configure"
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"textual_inversion.py" = "invokeai.frontend.training:invokeai_textual_inversion"
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@ -115,6 +115,9 @@ dependencies = [
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"invokeai-ti" = "invokeai.frontend.training:invokeai_textual_inversion"
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"invokeai-model-install" = "invokeai.frontend.install:invokeai_model_install"
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"invokeai-update" = "invokeai.frontend.config:invokeai_update"
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"invokeai-metadata" = "invokeai.frontend.CLI.sd_metadata:print_metadata"
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"invokeai-node-cli" = "invokeai.app.cli_app:invoke_cli"
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"invokeai-node-web" = "invokeai.app.api_app:invoke_api"
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[project.urls]
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"Homepage" = "https://invoke-ai.github.io/InvokeAI/"
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4
scripts/configure_invokeai.py
Normal file → Executable file
4
scripts/configure_invokeai.py
Normal file → Executable file
@ -2,8 +2,8 @@
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# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
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import warnings
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from ldm.invoke.config import invokeai_configure
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from invokeai.frontend.install import invokeai_configure as configure
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if __name__ == '__main__':
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warnings.warn("configure_invokeai.py is deprecated, running 'invokeai-configure'...", DeprecationWarning)
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invokeai_configure.main()
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configure()
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6
scripts/dream.py
Normal file → Executable file
6
scripts/dream.py
Normal file → Executable file
@ -1,10 +1,10 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python
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# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
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import warnings
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import ldm.invoke.CLI
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from invokeai.frontend.CLI import invokeai_command_line_interface as main
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warnings.warn("dream.py is being deprecated, please run invoke.py for the "
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"new UI/API or legacy_api.py for the old API",
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DeprecationWarning)
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ldm.invoke.CLI.main()
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main()
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@ -1,4 +1,4 @@
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#!/usr/bin/env python3
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#!/usr/bin/env python
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'''This script reads the "Invoke" Stable Diffusion prompt embedded in files generated by invoke.py'''
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import sys
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6
scripts/invoke-new.py
Normal file → Executable file
6
scripts/invoke-new.py
Normal file → Executable file
@ -1,3 +1,5 @@
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#!/usr/bin/env python
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# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
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import os
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@ -8,11 +10,11 @@ def main():
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os.chdir(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
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if '--web' in sys.argv:
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from ldm.invoke.app.api_app import invoke_api
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from invokeai.app.api_app import invoke_api
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invoke_api()
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else:
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# TODO: Parse some top-level args here.
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from ldm.invoke.app.cli_app import invoke_cli
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from invokeai.app.cli_app import invoke_cli
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invoke_cli()
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@ -1,4 +1,5 @@
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#!/usr/bin/env python
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import ldm.invoke.CLI
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ldm.invoke.CLI.main()
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from invokeai.frontend.CLI import invokeai_command_line_interface as main
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main()
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@ -1,681 +0,0 @@
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#!/usr/bin/env python3
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# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
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import argparse
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import shlex
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import os
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import re
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import sys
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import copy
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import warnings
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import time
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import ldm.invoke.readline
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from ldm.invoke.pngwriter import PngWriter, PromptFormatter
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from ldm.invoke.server_legacy import DreamServer, ThreadingDreamServer
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from ldm.invoke.image_util import make_grid
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from omegaconf import OmegaConf
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# Placeholder to be replaced with proper class that tracks the
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# outputs and associates with the prompt that generated them.
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# Just want to get the formatting look right for now.
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output_cntr = 0
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def main():
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"""Initialize command-line parsers and the diffusion model"""
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arg_parser = create_argv_parser()
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opt = arg_parser.parse_args()
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if opt.laion400m:
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print('--laion400m flag has been deprecated. Please use --model laion400m instead.')
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sys.exit(-1)
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if opt.weights != 'model':
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print('--weights argument has been deprecated. Please configure ./configs/models.yaml, and call it using --model instead.')
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sys.exit(-1)
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try:
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models = OmegaConf.load(opt.config)
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width = models[opt.model].width
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height = models[opt.model].height
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config = models[opt.model].config
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weights = models[opt.model].weights
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except (FileNotFoundError, IOError, KeyError) as e:
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print(f'{e}. Aborting.')
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sys.exit(-1)
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print('* Initializing, be patient...\n')
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sys.path.append('.')
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from pytorch_lightning import logging
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from ldm.generate import Generate
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# these two lines prevent a horrible warning message from appearing
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# when the frozen CLIP tokenizer is imported
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import transformers
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transformers.logging.set_verbosity_error()
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# creating a simple text2image object with a handful of
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# defaults passed on the command line.
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# additional parameters will be added (or overriden) during
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# the user input loop
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t2i = Generate(
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# width=width,
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# height=height,
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sampler_name=opt.sampler_name,
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weights=weights,
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full_precision=opt.full_precision,
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config=config,
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# grid=opt.grid,
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# this is solely for recreating the prompt
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# seamless=opt.seamless,
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embedding_path=opt.embedding_path,
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# device_type=opt.device,
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# ignore_ctrl_c=opt.infile is None,
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)
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# make sure the output directory exists
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if not os.path.exists(opt.outdir):
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os.makedirs(opt.outdir)
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# gets rid of annoying messages about random seed
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logging.getLogger('pytorch_lightning').setLevel(logging.ERROR)
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# load the infile as a list of lines
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infile = None
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if opt.infile:
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try:
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if os.path.isfile(opt.infile):
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infile = open(opt.infile, 'r', encoding='utf-8')
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elif opt.infile == '-': # stdin
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infile = sys.stdin
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else:
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raise FileNotFoundError(f'{opt.infile} not found.')
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except (FileNotFoundError, IOError) as e:
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print(f'{e}. Aborting.')
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sys.exit(-1)
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if opt.seamless:
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print(">> changed to seamless tiling mode")
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# preload the model
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t2i.load_model()
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if not infile:
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print(
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"\n* Initialization done! Awaiting your command (-h for help, 'q' to quit)"
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)
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cmd_parser = create_cmd_parser()
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if opt.web:
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dream_server_loop(t2i, opt.host, opt.port, opt.outdir)
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else:
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main_loop(t2i, opt.outdir, opt.prompt_as_dir, cmd_parser, infile)
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def main_loop(t2i, outdir, prompt_as_dir, parser, infile):
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"""prompt/read/execute loop"""
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done = False
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path_filter = re.compile(r'[<>:"/\\|?*]')
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last_results = list()
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# os.pathconf is not available on Windows
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if hasattr(os, 'pathconf'):
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path_max = os.pathconf(outdir, 'PC_PATH_MAX')
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name_max = os.pathconf(outdir, 'PC_NAME_MAX')
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else:
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path_max = 260
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name_max = 255
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while not done:
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try:
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command = get_next_command(infile)
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except EOFError:
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done = True
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continue
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except KeyboardInterrupt:
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done = True
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continue
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# skip empty lines
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if not command.strip():
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continue
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if command.startswith(('#', '//')):
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continue
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# before splitting, escape single quotes so as not to mess
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# up the parser
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command = command.replace("'", "\\'")
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try:
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elements = shlex.split(command)
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except ValueError as e:
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print(str(e))
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continue
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if elements[0] == 'q':
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done = True
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break
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if elements[0].startswith(
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'!dream'
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): # in case a stored prompt still contains the !dream command
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elements.pop(0)
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# rearrange the arguments to mimic how it works in the Dream bot.
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switches = ['']
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switches_started = False
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for el in elements:
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if el[0] == '-' and not switches_started:
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switches_started = True
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if switches_started:
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switches.append(el)
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else:
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switches[0] += el
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switches[0] += ' '
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switches[0] = switches[0][: len(switches[0]) - 1]
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try:
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opt = parser.parse_args(switches)
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except SystemExit:
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parser.print_help()
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continue
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if len(opt.prompt) == 0:
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print('Try again with a prompt!')
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continue
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# retrieve previous value!
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if opt.init_img is not None and re.match('^-\\d+$', opt.init_img):
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try:
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opt.init_img = last_results[int(opt.init_img)][0]
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print(f'>> Reusing previous image {opt.init_img}')
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except IndexError:
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print(
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f'>> No previous initial image at position {opt.init_img} found')
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opt.init_img = None
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continue
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if opt.seed is not None and opt.seed < 0: # retrieve previous value!
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try:
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opt.seed = last_results[opt.seed][1]
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print(f'>> Reusing previous seed {opt.seed}')
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except IndexError:
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print(f'>> No previous seed at position {opt.seed} found')
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opt.seed = None
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continue
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do_grid = opt.grid or t2i.grid
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if opt.with_variations is not None:
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# shotgun parsing, woo
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parts = []
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broken = False # python doesn't have labeled loops...
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for part in opt.with_variations.split(','):
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seed_and_weight = part.split(':')
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if len(seed_and_weight) != 2:
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print(f'could not parse with_variation part "{part}"')
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broken = True
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break
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try:
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seed = int(seed_and_weight[0])
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weight = float(seed_and_weight[1])
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except ValueError:
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print(f'could not parse with_variation part "{part}"')
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broken = True
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break
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parts.append([seed, weight])
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if broken:
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continue
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if len(parts) > 0:
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opt.with_variations = parts
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else:
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opt.with_variations = None
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if opt.outdir:
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if not os.path.exists(opt.outdir):
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os.makedirs(opt.outdir)
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current_outdir = opt.outdir
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elif prompt_as_dir:
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# sanitize the prompt to a valid folder name
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subdir = path_filter.sub('_', opt.prompt)[:name_max].rstrip(' .')
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# truncate path to maximum allowed length
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# 27 is the length of '######.##########.##.png', plus two separators and a NUL
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subdir = subdir[:(path_max - 27 - len(os.path.abspath(outdir)))]
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current_outdir = os.path.join(outdir, subdir)
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print('Writing files to directory: "' + current_outdir + '"')
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# make sure the output directory exists
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if not os.path.exists(current_outdir):
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os.makedirs(current_outdir)
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else:
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current_outdir = outdir
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# Here is where the images are actually generated!
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last_results = []
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try:
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file_writer = PngWriter(current_outdir)
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prefix = file_writer.unique_prefix()
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results = [] # list of filename, prompt pairs
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grid_images = dict() # seed -> Image, only used if `do_grid`
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def image_writer(image, seed, upscaled=False):
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path = None
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if do_grid:
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grid_images[seed] = image
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else:
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if upscaled and opt.save_original:
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filename = f'{prefix}.{seed}.postprocessed.png'
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else:
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filename = f'{prefix}.{seed}.png'
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if opt.variation_amount > 0:
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iter_opt = argparse.Namespace(**vars(opt)) # copy
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this_variation = [[seed, opt.variation_amount]]
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if opt.with_variations is None:
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iter_opt.with_variations = this_variation
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else:
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iter_opt.with_variations = opt.with_variations + this_variation
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iter_opt.variation_amount = 0
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normalized_prompt = PromptFormatter(
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t2i, iter_opt).normalize_prompt()
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metadata_prompt = f'{normalized_prompt} -S{iter_opt.seed}'
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elif opt.with_variations is not None:
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normalized_prompt = PromptFormatter(
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t2i, opt).normalize_prompt()
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# use the original seed - the per-iteration value is the last variation-seed
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metadata_prompt = f'{normalized_prompt} -S{opt.seed}'
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else:
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normalized_prompt = PromptFormatter(
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t2i, opt).normalize_prompt()
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metadata_prompt = f'{normalized_prompt} -S{seed}'
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path = file_writer.save_image_and_prompt_to_png(
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image, metadata_prompt, filename)
|
||||
if (not upscaled) or opt.save_original:
|
||||
# only append to results if we didn't overwrite an earlier output
|
||||
results.append([path, metadata_prompt])
|
||||
last_results.append([path, seed])
|
||||
|
||||
t2i.prompt2image(image_callback=image_writer, **vars(opt))
|
||||
|
||||
if do_grid and len(grid_images) > 0:
|
||||
grid_img = make_grid(list(grid_images.values()))
|
||||
grid_seeds = list(grid_images.keys())
|
||||
first_seed = last_results[0][1]
|
||||
filename = f'{prefix}.{first_seed}.png'
|
||||
# TODO better metadata for grid images
|
||||
normalized_prompt = PromptFormatter(
|
||||
t2i, opt).normalize_prompt()
|
||||
metadata_prompt = f'{normalized_prompt} -S{first_seed} --grid -n{len(grid_images)} # {grid_seeds}'
|
||||
path = file_writer.save_image_and_prompt_to_png(
|
||||
grid_img, metadata_prompt, filename
|
||||
)
|
||||
results = [[path, metadata_prompt]]
|
||||
|
||||
except AssertionError as e:
|
||||
print(e)
|
||||
continue
|
||||
|
||||
except OSError as e:
|
||||
print(e)
|
||||
continue
|
||||
|
||||
print('Outputs:')
|
||||
log_path = os.path.join(current_outdir, 'dream_log.txt')
|
||||
write_log_message(results, log_path)
|
||||
print()
|
||||
|
||||
print('goodbye!')
|
||||
|
||||
|
||||
def get_next_command(infile=None) -> str: # command string
|
||||
if infile is None:
|
||||
command = input('dream> ')
|
||||
else:
|
||||
command = infile.readline()
|
||||
if not command:
|
||||
raise EOFError
|
||||
else:
|
||||
command = command.strip()
|
||||
print(f'#{command}')
|
||||
return command
|
||||
|
||||
|
||||
def dream_server_loop(t2i, host, port, outdir):
|
||||
print('\n* --web was specified, starting web server...')
|
||||
# Change working directory to the stable-diffusion directory
|
||||
os.chdir(
|
||||
os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
|
||||
)
|
||||
|
||||
# Start server
|
||||
DreamServer.model = t2i
|
||||
DreamServer.outdir = outdir
|
||||
dream_server = ThreadingDreamServer((host, port))
|
||||
print(">> Started Stable Diffusion dream server!")
|
||||
if host == '0.0.0.0':
|
||||
print(
|
||||
f"Point your browser at http://localhost:{port} or use the host's DNS name or IP address.")
|
||||
else:
|
||||
print(">> Default host address now 127.0.0.1 (localhost). Use --host 0.0.0.0 to bind any address.")
|
||||
print(f">> Point your browser at http://{host}:{port}.")
|
||||
|
||||
try:
|
||||
dream_server.serve_forever()
|
||||
except KeyboardInterrupt:
|
||||
pass
|
||||
|
||||
dream_server.server_close()
|
||||
|
||||
|
||||
def write_log_message(results, log_path):
|
||||
"""logs the name of the output image, prompt, and prompt args to the terminal and log file"""
|
||||
global output_cntr
|
||||
log_lines = [f'{path}: {prompt}\n' for path, prompt in results]
|
||||
for l in log_lines:
|
||||
output_cntr += 1
|
||||
print(f'[{output_cntr}] {l}',end='')
|
||||
|
||||
|
||||
with open(log_path, 'a', encoding='utf-8') as file:
|
||||
file.writelines(log_lines)
|
||||
|
||||
|
||||
SAMPLER_CHOICES = [
|
||||
'ddim',
|
||||
'k_dpm_2_a',
|
||||
'k_dpm_2',
|
||||
'k_dpmpp_2_a',
|
||||
'k_dpmpp_2',
|
||||
'k_euler_a',
|
||||
'k_euler',
|
||||
'k_heun',
|
||||
'k_lms',
|
||||
'plms',
|
||||
]
|
||||
|
||||
|
||||
def create_argv_parser():
|
||||
parser = argparse.ArgumentParser(
|
||||
description="""Generate images using Stable Diffusion.
|
||||
Use --web to launch the web interface.
|
||||
Use --from_file to load prompts from a file path or standard input ("-").
|
||||
Otherwise you will be dropped into an interactive command prompt (type -h for help.)
|
||||
Other command-line arguments are defaults that can usually be overridden
|
||||
prompt the command prompt.
|
||||
"""
|
||||
)
|
||||
parser.add_argument(
|
||||
'--laion400m',
|
||||
'--latent_diffusion',
|
||||
'-l',
|
||||
dest='laion400m',
|
||||
action='store_true',
|
||||
help='Fallback to the latent diffusion (laion400m) weights and config',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--from_file',
|
||||
dest='infile',
|
||||
type=str,
|
||||
help='If specified, load prompts from this file',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-n',
|
||||
'--iterations',
|
||||
type=int,
|
||||
default=1,
|
||||
help='Number of images to generate',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-F',
|
||||
'--full_precision',
|
||||
dest='full_precision',
|
||||
action='store_true',
|
||||
help='Use more memory-intensive full precision math for calculations',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-g',
|
||||
'--grid',
|
||||
action='store_true',
|
||||
help='Generate a grid instead of individual images',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-A',
|
||||
'-m',
|
||||
'--sampler',
|
||||
dest='sampler_name',
|
||||
choices=SAMPLER_CHOICES,
|
||||
metavar='SAMPLER_NAME',
|
||||
default='k_lms',
|
||||
help=f'Set the initial sampler. Default: k_lms. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--outdir',
|
||||
'-o',
|
||||
type=str,
|
||||
default='outputs/img-samples',
|
||||
help='Directory to save generated images and a log of prompts and seeds. Default: outputs/img-samples',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--seamless',
|
||||
action='store_true',
|
||||
help='Change the model to seamless tiling (circular) mode',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--embedding_path',
|
||||
type=str,
|
||||
help='Path to a pre-trained embedding manager checkpoint - can only be set on command line',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--prompt_as_dir',
|
||||
'-p',
|
||||
action='store_true',
|
||||
help='Place images in subdirectories named after the prompt.',
|
||||
)
|
||||
# GFPGAN related args
|
||||
parser.add_argument(
|
||||
'--gfpgan_bg_upsampler',
|
||||
type=str,
|
||||
default='realesrgan',
|
||||
help='Background upsampler. Default: realesrgan. Options: realesrgan, none.',
|
||||
|
||||
)
|
||||
parser.add_argument(
|
||||
'--gfpgan_bg_tile',
|
||||
type=int,
|
||||
default=400,
|
||||
help='Tile size for background sampler, 0 for no tile during testing. Default: 400.',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--gfpgan_model_path',
|
||||
type=str,
|
||||
default='./models/gfpgan/GFPGANv1.4.pth',
|
||||
help='Indicates the path to the GFPGAN model.',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--web',
|
||||
dest='web',
|
||||
action='store_true',
|
||||
help='Start in web server mode.',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--host',
|
||||
type=str,
|
||||
default='127.0.0.1',
|
||||
help='Web server: Host or IP to listen on. Set to 0.0.0.0 to accept traffic from other devices on your network.'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--port',
|
||||
type=int,
|
||||
default='9090',
|
||||
help='Web server: Port to listen on'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--weights',
|
||||
default='model',
|
||||
help='Indicates the Stable Diffusion model to use.',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--device',
|
||||
'-d',
|
||||
type=str,
|
||||
default='cuda',
|
||||
help="device to run stable diffusion on. defaults to cuda `torch.cuda.current_device()` if available"
|
||||
)
|
||||
parser.add_argument(
|
||||
'--model',
|
||||
default='stable-diffusion-1.4',
|
||||
help='Indicates which diffusion model to load. (currently "stable-diffusion-1.4" (default) or "laion400m")',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--config',
|
||||
default='configs/models.yaml',
|
||||
help='Path to configuration file for alternate models.',
|
||||
)
|
||||
return parser
|
||||
|
||||
|
||||
def create_cmd_parser():
|
||||
parser = argparse.ArgumentParser(
|
||||
description='Example: dream> a fantastic alien landscape -W1024 -H960 -s100 -n12'
|
||||
)
|
||||
parser.add_argument('prompt')
|
||||
parser.add_argument('-s', '--steps', type=int, help='Number of steps')
|
||||
parser.add_argument(
|
||||
'-S',
|
||||
'--seed',
|
||||
type=int,
|
||||
help='Image seed; a +ve integer, or use -1 for the previous seed, -2 for the one before that, etc',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-n',
|
||||
'--iterations',
|
||||
type=int,
|
||||
default=1,
|
||||
help='Number of samplings to perform (slower, but will provide seeds for individual images)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-W', '--width', type=int, help='Image width, multiple of 64'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-H', '--height', type=int, help='Image height, multiple of 64'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-C',
|
||||
'--cfg_scale',
|
||||
default=7.5,
|
||||
type=float,
|
||||
help='Classifier free guidance (CFG) scale - higher numbers cause generator to "try" harder.',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-g', '--grid', action='store_true', help='generate a grid'
|
||||
)
|
||||
parser.add_argument(
|
||||
'--outdir',
|
||||
'-o',
|
||||
type=str,
|
||||
default=None,
|
||||
help='Directory to save generated images and a log of prompts and seeds',
|
||||
)
|
||||
parser.add_argument(
|
||||
'--seamless',
|
||||
action='store_true',
|
||||
help='Change the model to seamless tiling (circular) mode',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-i',
|
||||
'--individual',
|
||||
action='store_true',
|
||||
help='Generate individual files (default)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-I',
|
||||
'--init_img',
|
||||
type=str,
|
||||
help='Path to input image for img2img mode (supersedes width and height)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-M',
|
||||
'--init_mask',
|
||||
type=str,
|
||||
help='Path to input mask for inpainting mode (supersedes width and height)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-T',
|
||||
'-fit',
|
||||
'--fit',
|
||||
action='store_true',
|
||||
help='If specified, will resize the input image to fit within the dimensions of width x height (512x512 default)',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-f',
|
||||
'--strength',
|
||||
default=0.75,
|
||||
type=float,
|
||||
help='Strength for noising/unnoising. 0.0 preserves image exactly, 1.0 replaces it completely',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-G',
|
||||
'--gfpgan_strength',
|
||||
default=0,
|
||||
type=float,
|
||||
help='The strength at which to apply the GFPGAN model to the result, in order to improve faces.',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-U',
|
||||
'--upscale',
|
||||
nargs='+',
|
||||
default=None,
|
||||
type=float,
|
||||
help='Scale factor (2, 4) for upscaling followed by upscaling strength (0-1.0). If strength not specified, defaults to 0.75'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-save_orig',
|
||||
'--save_original',
|
||||
action='store_true',
|
||||
help='Save original. Use it when upscaling to save both versions.',
|
||||
)
|
||||
# variants is going to be superseded by a generalized "prompt-morph" function
|
||||
# parser.add_argument('-v','--variants',type=int,help="in img2img mode, the first generated image will get passed back to img2img to generate the requested number of variants")
|
||||
parser.add_argument(
|
||||
'-x',
|
||||
'--skip_normalize',
|
||||
action='store_true',
|
||||
help='Skip subprompt weight normalization',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-A',
|
||||
'-m',
|
||||
'--sampler',
|
||||
dest='sampler_name',
|
||||
default=None,
|
||||
type=str,
|
||||
choices=SAMPLER_CHOICES,
|
||||
metavar='SAMPLER_NAME',
|
||||
help=f'Switch to a different sampler. Supported samplers: {", ".join(SAMPLER_CHOICES)}',
|
||||
)
|
||||
parser.add_argument(
|
||||
'-t',
|
||||
'--log_tokenization',
|
||||
action='store_true',
|
||||
help='shows how the prompt is split into tokens'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-v',
|
||||
'--variation_amount',
|
||||
default=0.0,
|
||||
type=float,
|
||||
help='If > 0, generates variations on the initial seed instead of random seeds per iteration. Must be between 0 and 1. Higher values will be more different.'
|
||||
)
|
||||
parser.add_argument(
|
||||
'-V',
|
||||
'--with_variations',
|
||||
default=None,
|
||||
type=str,
|
||||
help='list of variations to apply, in the format `seed:weight,seed:weight,...'
|
||||
)
|
||||
return parser
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
2
scripts/pypi_helper.py
Normal file → Executable file
2
scripts/pypi_helper.py
Normal file → Executable file
@ -1,3 +1,5 @@
|
||||
#!/usr/bin/env python
|
||||
|
||||
import requests
|
||||
|
||||
from ldm.invoke import __app_name__, __version__
|
||||
|
||||
@ -2,7 +2,7 @@
|
||||
|
||||
import sys
|
||||
import json
|
||||
from ldm.invoke.pngwriter import retrieve_metadata
|
||||
from invokeai.backend.image_util import retrieve_metadata
|
||||
|
||||
if len(sys.argv) < 2:
|
||||
print("Usage: file2prompt.py <file1.png> <file2.png> <file3.png>...")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user