fix broken scripts (#2857)

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
```

invokeai/app/api/dependencies.py

@@ -3,7 +3,7 @@
 import os
 from argparse import Namespace
 
-from ...globals import Globals
+from ...backend import Globals
 from ..services.generate_initializer import get_generate
 from ..services.graph import GraphExecutionState
 from ..services.image_storage import DiskImageStorage

invokeai/app/api_app.py

@@ -13,7 +13,7 @@ from fastapi_events.handlers.local import local_handler
 from fastapi_events.middleware import EventHandlerASGIMiddleware
 from pydantic.schema import schema
 
-from ..args import Args
+from ..backend import Args
 from .api.dependencies import ApiDependencies
 from .api.routers import images, sessions
 from .api.sockets import SocketIO

invokeai/app/cli_app.py

@@ -18,7 +18,7 @@ from typing import (
 from pydantic import BaseModel
 from pydantic.fields import Field
 
-from ..args import Args
+from ..backend import Args
 from .invocations import *
 from .invocations.baseinvocation import BaseInvocation
 from .invocations.image import ImageField

invokeai/app/services/generate_initializer.py

@@ -6,7 +6,7 @@ from argparse import Namespace
 import invokeai.version
 from invokeai.backend import Generate, ModelManager
 
-from ...globals import Globals
+from ...backend import Globals
 
 
 # TODO: most of this code should be split into individual services as the Generate.py code is deprecated

invokeai/backend/__init__.py

@@ -3,3 +3,5 @@ Initialization file for invokeai.backend
 """
 from .generate import Generate
 from .model_management import ModelManager
+from .args import Args
+from .globals import Globals

invokeai/frontend/CLI/sd_metadata.py

@@ -0,0 +1,30 @@
+'''
+This is a modularized version of the sd-metadata.py script,
+which retrieves and prints the metadata from a series of generated png files.
+'''
+import sys
+import json
+from invokeai.backend.image_util import retrieve_metadata
+
+
+def print_metadata():
+    if len(sys.argv) < 2:
+        print("Usage: file2prompt.py <file1.png> <file2.png> <file3.png>...")
+        print("This script opens up the indicated invoke.py-generated PNG file(s) and prints out their metadata.")
+        exit(-1)
+
+    filenames = sys.argv[1:]
+    for f in filenames:
+        try:
+            metadata = retrieve_metadata(f)
+            print(f'{f}:\n',json.dumps(metadata['sd-metadata'], indent=4))
+        except FileNotFoundError:
+            sys.stderr.write(f'{f} not found\n')
+            continue
+        except PermissionError:
+            sys.stderr.write(f'{f} could not be opened due to inadequate permissions\n')
+            continue
+
+if __name__== '__main__':
+    print_metadata()
+

pyproject.toml

@@ -104,7 +104,7 @@ dependencies = [
 [project.scripts]
 
 # legacy entrypoints; provided for backwards compatibility
-"invoke.py" = "invokeai.frontend.CLI:command_line_interface"
+"invoke.py" = "invokeai.frontend.CLI:invokeai_command_line_interface"
 "configure_invokeai.py" = "invokeai.frontend.install:invokeai_configure"
 "textual_inversion.py" = "invokeai.frontend.training:invokeai_textual_inversion"
 
@@ -115,6 +115,9 @@ dependencies = [
 "invokeai-ti" = "invokeai.frontend.training:invokeai_textual_inversion"
 "invokeai-model-install" = "invokeai.frontend.install:invokeai_model_install"
 "invokeai-update" = "invokeai.frontend.config:invokeai_update"
+"invokeai-metadata" = "invokeai.frontend.CLI.sd_metadata:print_metadata"
+"invokeai-node-cli" = "invokeai.app.cli_app:invoke_cli"
+"invokeai-node-web" = "invokeai.app.api_app:invoke_api"
 
 [project.urls]
 "Homepage" = "https://invoke-ai.github.io/InvokeAI/"

scripts/configure_invokeai.py

@@ -2,8 +2,8 @@
 # Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
 
 import warnings
-from ldm.invoke.config import invokeai_configure
+from invokeai.frontend.install import invokeai_configure as configure
 
 if __name__ == '__main__':
     warnings.warn("configure_invokeai.py is deprecated, running 'invokeai-configure'...", DeprecationWarning)
-    invokeai_configure.main()
+    configure()

scripts/dream.py

@@ -1,10 +1,10 @@
-#!/usr/bin/env python3
+#!/usr/bin/env python
 # Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
 
 import warnings
-import ldm.invoke.CLI
+from invokeai.frontend.CLI import invokeai_command_line_interface as main
 warnings.warn("dream.py is being deprecated, please run invoke.py for the "
               "new UI/API or legacy_api.py for the old API",
               DeprecationWarning)
-ldm.invoke.CLI.main()
+main()
 

scripts/images2prompt.py

@@ -1,4 +1,4 @@
-#!/usr/bin/env python3
+#!/usr/bin/env python
 '''This script reads the "Invoke" Stable Diffusion prompt embedded in files generated by invoke.py'''
 
 import sys

scripts/invoke-new.py

@@ -1,3 +1,5 @@
+#!/usr/bin/env python
+
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
 import os
@@ -8,11 +10,11 @@ def main():
     os.chdir(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 
     if '--web' in sys.argv:
-        from ldm.invoke.app.api_app import invoke_api
+        from invokeai.app.api_app import invoke_api
         invoke_api()
     else:
         # TODO: Parse some top-level args here.
-        from ldm.invoke.app.cli_app import invoke_cli
+        from invokeai.app.cli_app import invoke_cli
         invoke_cli()
 
 

scripts/invoke.py

@@ -1,4 +1,5 @@
 #!/usr/bin/env python
 
-import ldm.invoke.CLI
+from invokeai.frontend.CLI import invokeai_command_line_interface as main
-ldm.invoke.CLI.main()
+main()
+

scripts/legacy_api.py

@@ -1,681 +0,0 @@
-#!/usr/bin/env python3
-# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
-
-import argparse
-import shlex
-import os
-import re
-import sys
-import copy
-import warnings
-import time
-import ldm.invoke.readline
-from ldm.invoke.pngwriter import PngWriter, PromptFormatter
-from ldm.invoke.server_legacy import DreamServer, ThreadingDreamServer
-from ldm.invoke.image_util import make_grid
-from omegaconf import OmegaConf
-
-# Placeholder to be replaced with proper class that tracks the
-# outputs and associates with the prompt that generated them.
-# Just want to get the formatting look right for now.
-output_cntr = 0
-
-
-def main():
-    """Initialize command-line parsers and the diffusion model"""
-    arg_parser = create_argv_parser()
-    opt = arg_parser.parse_args()
-
-    if opt.laion400m:
-        print('--laion400m flag has been deprecated. Please use --model laion400m instead.')
-        sys.exit(-1)
-    if opt.weights != 'model':
-        print('--weights argument has been deprecated. Please configure ./configs/models.yaml, and call it using --model instead.')
-        sys.exit(-1)
-
-    try:
-        models = OmegaConf.load(opt.config)
-        width = models[opt.model].width
-        height = models[opt.model].height
-        config = models[opt.model].config
-        weights = models[opt.model].weights
-    except (FileNotFoundError, IOError, KeyError) as e:
-        print(f'{e}. Aborting.')
-        sys.exit(-1)
-
-    print('* Initializing, be patient...\n')
-    sys.path.append('.')
-    from pytorch_lightning import logging
-    from ldm.generate import Generate
-
-    # these two lines prevent a horrible warning message from appearing
-    # when the frozen CLIP tokenizer is imported
-    import transformers
-
-    transformers.logging.set_verbosity_error()
-
-    # creating a simple text2image object with a handful of
-    # defaults passed on the command line.
-    # additional parameters will be added (or overriden) during
-    # the user input loop
-    t2i = Generate(
-        # width=width,
-        # height=height,
-        sampler_name=opt.sampler_name,
-        weights=weights,
-        full_precision=opt.full_precision,
-        config=config,
-        # grid=opt.grid,
-        # this is solely for recreating the prompt
-        # seamless=opt.seamless,
-        embedding_path=opt.embedding_path,
-        # device_type=opt.device,
-        # ignore_ctrl_c=opt.infile is None,
-    )
-
-    # make sure the output directory exists
-    if not os.path.exists(opt.outdir):
-        os.makedirs(opt.outdir)
-
-    # gets rid of annoying messages about random seed
-    logging.getLogger('pytorch_lightning').setLevel(logging.ERROR)
-
-    # load the infile as a list of lines
-    infile = None
-    if opt.infile:
-        try:
-            if os.path.isfile(opt.infile):
-                infile = open(opt.infile, 'r', encoding='utf-8')
-            elif opt.infile == '-':  # stdin
-                infile = sys.stdin
-            else:
-                raise FileNotFoundError(f'{opt.infile} not found.')
-        except (FileNotFoundError, IOError) as e:
-            print(f'{e}. Aborting.')
-            sys.exit(-1)
-
-    if opt.seamless:
-        print(">> changed to seamless tiling mode")
-
-    # preload the model
-    t2i.load_model()
-
-    if not infile:
-        print(
-            "\n* Initialization done! Awaiting your command (-h for help, 'q' to quit)"
-        )
-
-    cmd_parser = create_cmd_parser()
-    if opt.web:
-        dream_server_loop(t2i, opt.host, opt.port, opt.outdir)
-    else:
-        main_loop(t2i, opt.outdir, opt.prompt_as_dir, cmd_parser, infile)
-
-
-def main_loop(t2i, outdir, prompt_as_dir, parser, infile):
-    """prompt/read/execute loop"""
-    done = False
-    path_filter = re.compile(r'[<>:"/\\|?*]')
-    last_results = list()
-
-    # os.pathconf is not available on Windows
-    if hasattr(os, 'pathconf'):
-        path_max = os.pathconf(outdir, 'PC_PATH_MAX')
-        name_max = os.pathconf(outdir, 'PC_NAME_MAX')
-    else:
-        path_max = 260
-        name_max = 255
-
-    while not done:
-        try:
-            command = get_next_command(infile)
-        except EOFError:
-            done = True
-            continue
-        except KeyboardInterrupt:
-            done = True
-            continue
-
-        # skip empty lines
-        if not command.strip():
-            continue
-
-        if command.startswith(('#', '//')):
-            continue
-
-        # before splitting, escape single quotes so as not to mess
-        # up the parser
-        command = command.replace("'", "\\'")
-
-        try:
-            elements = shlex.split(command)
-        except ValueError as e:
-            print(str(e))
-            continue
-
-        if elements[0] == 'q':
-            done = True
-            break
-
-        if elements[0].startswith(
-            '!dream'
-        ):   # in case a stored prompt still contains the !dream command
-            elements.pop(0)
-
-        # rearrange the arguments to mimic how it works in the Dream bot.
-        switches = ['']
-        switches_started = False
-
-        for el in elements:
-            if el[0] == '-' and not switches_started:
-                switches_started = True
-            if switches_started:
-                switches.append(el)
-            else:
-                switches[0] += el
-                switches[0] += ' '
-        switches[0] = switches[0][: len(switches[0]) - 1]
-
-        try:
-            opt = parser.parse_args(switches)
-        except SystemExit:
-            parser.print_help()
-            continue
-        if len(opt.prompt) == 0:
-            print('Try again with a prompt!')
-            continue
-        # retrieve previous value!
-        if opt.init_img is not None and re.match('^-\\d+$', opt.init_img):
-            try:
-                opt.init_img = last_results[int(opt.init_img)][0]
-                print(f'>> Reusing previous image {opt.init_img}')
-            except IndexError:
-                print(
-                    f'>> No previous initial image at position {opt.init_img} found')
-                opt.init_img = None
-                continue
-
-        if opt.seed is not None and opt.seed < 0:   # retrieve previous value!
-            try:
-                opt.seed = last_results[opt.seed][1]
-                print(f'>> Reusing previous seed {opt.seed}')
-            except IndexError:
-                print(f'>> No previous seed at position {opt.seed} found')
-                opt.seed = None
-                continue
-
-        do_grid = opt.grid or t2i.grid
-
-        if opt.with_variations is not None:
-            # shotgun parsing, woo
-            parts = []
-            broken = False  # python doesn't have labeled loops...
-            for part in opt.with_variations.split(','):
-                seed_and_weight = part.split(':')
-                if len(seed_and_weight) != 2:
-                    print(f'could not parse with_variation part "{part}"')
-                    broken = True
-                    break
-                try:
-                    seed = int(seed_and_weight[0])
-                    weight = float(seed_and_weight[1])
-                except ValueError:
-                    print(f'could not parse with_variation part "{part}"')
-                    broken = True
-                    break
-                parts.append([seed, weight])
-            if broken:
-                continue
-            if len(parts) > 0:
-                opt.with_variations = parts
-            else:
-                opt.with_variations = None
-
-        if opt.outdir:
-            if not os.path.exists(opt.outdir):
-                os.makedirs(opt.outdir)
-            current_outdir = opt.outdir
-        elif prompt_as_dir:
-            # sanitize the prompt to a valid folder name
-            subdir = path_filter.sub('_', opt.prompt)[:name_max].rstrip(' .')
-
-            # truncate path to maximum allowed length
-            # 27 is the length of '######.##########.##.png', plus two separators and a NUL
-            subdir = subdir[:(path_max - 27 - len(os.path.abspath(outdir)))]
-            current_outdir = os.path.join(outdir, subdir)
-
-            print('Writing files to directory: "' + current_outdir + '"')
-
-            # make sure the output directory exists
-            if not os.path.exists(current_outdir):
-                os.makedirs(current_outdir)
-        else:
-            current_outdir = outdir
-
-        # Here is where the images are actually generated!
-        last_results = []
-        try:
-            file_writer = PngWriter(current_outdir)
-            prefix = file_writer.unique_prefix()
-            results = []  # list of filename, prompt pairs
-            grid_images = dict()  # seed -> Image, only used if `do_grid`
-
-            def image_writer(image, seed, upscaled=False):
-                path = None
-                if do_grid:
-                    grid_images[seed] = image
-                else:
-                    if upscaled and opt.save_original:
-                        filename = f'{prefix}.{seed}.postprocessed.png'
-                    else:
-                        filename = f'{prefix}.{seed}.png'
-                    if opt.variation_amount > 0:
-                        iter_opt = argparse.Namespace(**vars(opt))  # copy
-                        this_variation = [[seed, opt.variation_amount]]
-                        if opt.with_variations is None:
-                            iter_opt.with_variations = this_variation
-                        else:
-                            iter_opt.with_variations = opt.with_variations + this_variation
-                        iter_opt.variation_amount = 0
-                        normalized_prompt = PromptFormatter(
-                            t2i, iter_opt).normalize_prompt()
-                        metadata_prompt = f'{normalized_prompt} -S{iter_opt.seed}'
-                    elif opt.with_variations is not None:
-                        normalized_prompt = PromptFormatter(
-                            t2i, opt).normalize_prompt()
-                        # use the original seed - the per-iteration value is the last variation-seed
-                        metadata_prompt = f'{normalized_prompt} -S{opt.seed}'
-                    else:
-                        normalized_prompt = PromptFormatter(
-                            t2i, opt).normalize_prompt()
-                        metadata_prompt = f'{normalized_prompt} -S{seed}'
-                    path = file_writer.save_image_and_prompt_to_png(
-                        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()

scripts/pypi_helper.py

@@ -1,3 +1,5 @@
+#!/usr/bin/env python
+
 import requests
 
 from ldm.invoke import __app_name__, __version__

scripts/sd-metadata.py

@@ -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>...")