InvokeAI/scripts/invoke.py

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#!/usr/bin/env python3
# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
import os
import re
import sys
import shlex
import copy
import warnings
import time
import traceback
sys.path.append('.') # corrects a weird problem on Macs
from ldm.invoke.readline import get_completer
from ldm.invoke.args import Args, metadata_dumps, metadata_from_png, dream_cmd_from_png
from ldm.invoke.pngwriter import PngWriter, retrieve_metadata, write_metadata
from ldm.invoke.image_util import make_grid
from ldm.invoke.log import write_log
from omegaconf import OmegaConf
from backend.invoke_ai_web_server import InvokeAIWebServer
def main():
"""Initialize command-line parsers and the diffusion model"""
opt = Args()
args = opt.parse_args()
if not args:
sys.exit(-1)
if args.laion400m:
print('--laion400m flag has been deprecated. Please use --model laion400m instead.')
sys.exit(-1)
if args.weights:
print('--weights argument has been deprecated. Please edit ./configs/models.yaml, and select the weights using --model instead.')
sys.exit(-1)
print('* Initializing, be patient...\n')
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()
# Loading Face Restoration and ESRGAN Modules
try:
gfpgan, codeformer, esrgan = None, None, None
if opt.restore or opt.esrgan:
from ldm.invoke.restoration import Restoration
restoration = Restoration()
if opt.restore:
gfpgan, codeformer = restoration.load_face_restore_models(opt.gfpgan_dir, opt.gfpgan_model_path)
else:
print('>> Face restoration disabled')
if opt.esrgan:
esrgan = restoration.load_esrgan(opt.esrgan_bg_tile)
else:
print('>> Upscaling disabled')
else:
print('>> Face restoration and upscaling disabled')
except (ModuleNotFoundError, ImportError):
print(traceback.format_exc(), file=sys.stderr)
print('>> You may need to install the ESRGAN and/or GFPGAN modules')
# 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
try:
gen = Generate(
conf = opt.conf,
model = opt.model,
sampler_name = opt.sampler_name,
embedding_path = opt.embedding_path,
full_precision = opt.full_precision,
precision = opt.precision,
gfpgan=gfpgan,
codeformer=codeformer,
esrgan=esrgan,
free_gpu_mem=opt.free_gpu_mem,
)
except (FileNotFoundError, IOError, KeyError) as e:
print(f'{e}. Aborting.')
sys.exit(-1)
# make sure the output directory exists
if not os.path.exists(opt.outdir):
os.makedirs(opt.outdir)
# 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
gen.load_model()
# web server loops forever
if opt.web or opt.gui:
invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan)
sys.exit(0)
if not infile:
print(
"\n* Initialization done! Awaiting your command (-h for help, 'q' to quit)"
)
main_loop(gen, opt, infile)
# TODO: main_loop() has gotten busy. Needs to be refactored.
def main_loop(gen, opt, infile):
"""prompt/read/execute loop"""
done = False
path_filter = re.compile(r'[<>:"/\\|?*]')
last_results = list()
model_config = OmegaConf.load(opt.conf)[opt.model]
# The readline completer reads history from the .dream_history file located in the
# output directory specified at the time of script launch. We do not currently support
# changing the history file midstream when the output directory is changed.
completer = get_completer(opt)
output_cntr = completer.get_current_history_length()+1
# os.pathconf is not available on Windows
if hasattr(os, 'pathconf'):
path_max = os.pathconf(opt.outdir, 'PC_PATH_MAX')
name_max = os.pathconf(opt.outdir, 'PC_NAME_MAX')
else:
path_max = 260
name_max = 255
while not done:
operation = 'generate' # default operation, alternative is 'postprocess'
if completer:
completer.set_default_dir(opt.outdir)
try:
command = get_next_command(infile)
except EOFError:
done = True
continue
# skip empty lines
if not command.strip():
continue
if command.startswith(('#', '//')):
continue
if len(command.strip()) == 1 and command.startswith('q'):
done = True
break
if command.startswith('!'):
subcommand = command[1:]
if subcommand.startswith('dream'): # in case a stored prompt still contains the !dream command
command = command.replace('!dream ','',1)
elif subcommand.startswith('fix'):
command = command.replace('!fix ','',1)
operation = 'postprocess'
elif subcommand.startswith('fetch'):
file_path = command.replace('!fetch ','',1)
retrieve_dream_command(opt,file_path,completer)
continue
elif subcommand.startswith('history'):
completer.show_history()
continue
elif subcommand.startswith('search'):
search_str = command.replace('!search ','',1)
completer.show_history(search_str)
continue
elif subcommand.startswith('clear'):
completer.clear_history()
continue
elif re.match('^(\d+)',subcommand):
command_no = re.match('^(\d+)',subcommand).groups()[0]
command = completer.get_line(int(command_no))
completer.set_line(command)
continue
else: # not a recognized subcommand, so give the --help text
command = '-h'
if opt.parse_cmd(command) is None:
continue
if opt.init_img:
try:
if not opt.prompt:
oldargs = metadata_from_png(opt.init_img)
opt.prompt = oldargs.prompt
print(f'>> Retrieved old prompt "{opt.prompt}" from {opt.init_img}')
except (OSError, AttributeError, KeyError):
pass
if len(opt.prompt) == 0:
print('\nTry again with a prompt!')
continue
# width and height are set by model if not specified
if not opt.width:
opt.width = model_config.width
if not opt.height:
opt.height = model_config.height
# retrieve previous value of init image if requested
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
# try to relativize pathnames
for attr in ('init_img','init_mask','init_color','embedding_path'):
if getattr(opt,attr) and not os.path.exists(getattr(opt,attr)):
basename = getattr(opt,attr)
path = os.path.join(opt.outdir,basename)
setattr(opt,attr,path)
# retrieve previous value of seed if requested
if opt.seed is not None and opt.seed < 0:
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
if opt.strength is None:
opt.strength = 0.75 if opt.out_direction is None else 0.83
if opt.with_variations is not None:
opt.with_variations = split_variations(opt.with_variations)
if opt.prompt_as_dir and operation == 'generate':
# sanitize the prompt to a valid folder name
subdir = path_filter.sub('_', opt.prompt)[:name_max].rstrip(' .')
# truncate path to maximum allowed length
# 39 is the length of '######.##########.##########-##.png', plus two separators and a NUL
subdir = subdir[:(path_max - 39 - len(os.path.abspath(opt.outdir)))]
current_outdir = os.path.join(opt.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:
if not os.path.exists(opt.outdir):
os.makedirs(opt.outdir)
current_outdir = opt.outdir
# write out the history at this point
if operation == 'postprocess':
completer.add_history(f'!fix {command}')
else:
completer.add_history(command)
# Here is where the images are actually generated!
last_results = []
try:
file_writer = PngWriter(current_outdir)
results = [] # list of filename, prompt pairs
grid_images = dict() # seed -> Image, only used if `opt.grid`
prior_variations = opt.with_variations or []
prefix = file_writer.unique_prefix()
step_callback = make_step_callback(gen, opt, prefix) if opt.save_intermediates > 0 else None
def image_writer(image, seed, upscaled=False, first_seed=None, use_prefix=None):
# note the seed is the seed of the current image
# the first_seed is the original seed that noise is added to
# when the -v switch is used to generate variations
nonlocal prior_variations
nonlocal prefix
if use_prefix is not None:
prefix = use_prefix
path = None
if opt.grid:
grid_images[seed] = image
else:
postprocessed = upscaled if upscaled else operation=='postprocess'
filename, formatted_dream_prompt = prepare_image_metadata(
opt,
prefix,
seed,
operation,
prior_variations,
postprocessed,
first_seed
)
path = file_writer.save_image_and_prompt_to_png(
image = image,
dream_prompt = formatted_dream_prompt,
metadata = metadata_dumps(
opt,
seeds = [seed if opt.variation_amount==0 and len(prior_variations)==0 else first_seed],
model_hash = gen.model_hash,
),
name = filename,
)
# update rfc metadata
if operation == 'postprocess':
tool = re.match('postprocess:(\w+)',opt.last_operation).groups()[0]
add_postprocessing_to_metadata(
opt,
opt.prompt,
filename,
tool,
formatted_dream_prompt,
)
if (not postprocessed) or opt.save_original:
# only append to results if we didn't overwrite an earlier output
results.append([path, formatted_dream_prompt])
# so that the seed autocompletes (on linux|mac when -S or --seed specified
if completer:
completer.add_seed(seed)
completer.add_seed(first_seed)
last_results.append([path, seed])
if operation == 'generate':
catch_ctrl_c = infile is None # if running interactively, we catch keyboard interrupts
opt.last_operation='generate'
gen.prompt2image(
image_callback=image_writer,
step_callback=step_callback,
catch_interrupts=catch_ctrl_c,
**vars(opt)
)
elif operation == 'postprocess':
print(f'>> fixing {opt.prompt}')
opt.last_operation = do_postprocess(gen,opt,image_writer)
if opt.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'
formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed,grid=True,iterations=len(grid_images))
formatted_dream_prompt += f' # {grid_seeds}'
metadata = metadata_dumps(
opt,
seeds = grid_seeds,
model_hash = gen.model_hash
)
path = file_writer.save_image_and_prompt_to_png(
image = grid_img,
dream_prompt = formatted_dream_prompt,
metadata = metadata,
name = filename
)
results = [[path, formatted_dream_prompt]]
except AssertionError as e:
print(e)
continue
except OSError as e:
print(e)
continue
print('Outputs:')
log_path = os.path.join(current_outdir, 'invoke_log')
output_cntr = write_log(results, log_path ,('txt', 'md'), output_cntr)
print()
print('goodbye!')
def do_postprocess (gen, opt, callback):
file_path = opt.prompt # treat the prompt as the file pathname
if os.path.dirname(file_path) == '': #basename given
file_path = os.path.join(opt.outdir,file_path)
tool=None
if opt.gfpgan_strength > 0:
tool = opt.facetool
elif opt.embiggen:
tool = 'embiggen'
elif opt.upscale:
tool = 'upscale'
elif opt.out_direction:
tool = 'outpaint'
elif opt.outcrop:
tool = 'outcrop'
opt.save_original = True # do not overwrite old image!
opt.last_operation = f'postprocess:{tool}'
try:
gen.apply_postprocessor(
image_path = file_path,
tool = tool,
gfpgan_strength = opt.gfpgan_strength,
codeformer_fidelity = opt.codeformer_fidelity,
save_original = opt.save_original,
upscale = opt.upscale,
out_direction = opt.out_direction,
outcrop = opt.outcrop,
callback = callback,
opt = opt,
)
except OSError:
print(traceback.format_exc(), file=sys.stderr)
print(f'** {file_path}: file could not be read')
return
except (KeyError, AttributeError):
print(traceback.format_exc(), file=sys.stderr)
return
return opt.last_operation
def add_postprocessing_to_metadata(opt,original_file,new_file,tool,command):
original_file = original_file if os.path.exists(original_file) else os.path.join(opt.outdir,original_file)
new_file = new_file if os.path.exists(new_file) else os.path.join(opt.outdir,new_file)
meta = retrieve_metadata(original_file)['sd-metadata']
img_data = meta['image']
pp = img_data.get('postprocessing',[]) or []
pp.append(
{
'tool':tool,
'dream_command':command,
}
)
meta['image']['postprocessing'] = pp
write_metadata(new_file,meta)
def prepare_image_metadata(
opt,
prefix,
seed,
operation='generate',
prior_variations=[],
postprocessed=False,
first_seed=None
):
if postprocessed and opt.save_original:
filename = choose_postprocess_name(opt,prefix,seed)
else:
filename = f'{prefix}.{seed}.png'
if opt.variation_amount > 0:
first_seed = first_seed or seed
this_variation = [[seed, opt.variation_amount]]
opt.with_variations = prior_variations + this_variation
formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed)
elif len(prior_variations) > 0:
formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed)
elif operation == 'postprocess':
formatted_dream_prompt = '!fix '+opt.dream_prompt_str(seed=seed)
else:
formatted_dream_prompt = opt.dream_prompt_str(seed=seed)
return filename,formatted_dream_prompt
def choose_postprocess_name(opt,prefix,seed) -> str:
match = re.search('postprocess:(\w+)',opt.last_operation)
if match:
modifier = match.group(1) # will look like "gfpgan", "upscale", "outpaint" or "embiggen"
else:
modifier = 'postprocessed'
counter = 0
filename = None
available = False
while not available:
if counter == 0:
filename = f'{prefix}.{seed}.{modifier}.png'
else:
filename = f'{prefix}.{seed}.{modifier}-{counter:02d}.png'
available = not os.path.exists(os.path.join(opt.outdir,filename))
counter += 1
return filename
def get_next_command(infile=None) -> str: # command string
if infile is None:
command = input('invoke> ')
else:
command = infile.readline()
if not command:
raise EOFError
else:
command = command.strip()
if len(command)>0:
print(f'#{command}')
return command
def invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan):
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__), '..'))
)
invoke_ai_web_server = InvokeAIWebServer(generate=gen, gfpgan=gfpgan, codeformer=codeformer, esrgan=esrgan)
try:
invoke_ai_web_server.run()
except KeyboardInterrupt:
pass
def split_variations(variations_string) -> list:
# shotgun parsing, woo
parts = []
broken = False # python doesn't have labeled loops...
for part in variations_string.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:
return None
elif len(parts) == 0:
return None
else:
return parts
def make_step_callback(gen, opt, prefix):
destination = os.path.join(opt.outdir,'intermediates',prefix)
os.makedirs(destination,exist_ok=True)
print(f'>> Intermediate images will be written into {destination}')
def callback(img, step):
if step % opt.save_intermediates == 0 or step == opt.steps-1:
filename = os.path.join(destination,f'{step:04}.png')
image = gen.sample_to_image(img)
image.save(filename,'PNG')
return callback
def retrieve_dream_command(opt,file_path,completer):
'''
Given a full or partial path to a previously-generated image file,
will retrieve and format the dream command used to generate the image,
and pop it into the readline buffer (linux, Mac), or print out a comment
for cut-and-paste (windows)
'''
dir,basename = os.path.split(file_path)
if len(dir) == 0:
path = os.path.join(opt.outdir,basename)
else:
path = file_path
try:
cmd = dream_cmd_from_png(path)
except OSError:
print(f'** {path}: file could not be read')
return
except (KeyError, AttributeError):
print(f'** {path}: file has no metadata')
return
completer.set_line(cmd)
if __name__ == '__main__':
main()