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dream-factory.py
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dream-factory.py
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# Copyright 2021 - 2024, Bill Kennedy (https://github.com/rbbrdckybk/dream-factory)
# SPDX-License-Identifier: MIT
import threading
import time
import datetime
import shlex
import subprocess
import sys
import unicodedata
import re
import random
import os
import platform
import signal
import webbrowser
import argparse
import shutil
import base64
import json
import copy
import math
from PIL import Image
from io import BytesIO
import scripts.utils as utils
import scripts.metadata as metadata
import scripts.civitai as civitai
from os.path import exists
from datetime import datetime as dt
from datetime import date
from pathlib import Path
from collections import deque
from PIL.PngImagePlugin import PngImageFile, PngInfo
from torch.cuda import get_device_name, device_count
from scripts.server import ArtServer
from scripts.sdi import SDI
# environment setup
cwd = os.getcwd()
python_path = ""
env_paths = [ \
os.path.join(cwd, 'taming-transformers'),
os.path.join(cwd, 'CLIP')
]
for path in env_paths:
python_path += os.pathsep + path
#os.environ['PYTHONPATH'] = python_path
# Prevent threads from printing at same time.
print_lock = threading.Lock()
# worker thread executes specified shell command
class Worker(threading.Thread):
def __init__(self, command, callback=lambda: None, *args):
threading.Thread.__init__(self)
self.command = command
self.callback = callback
# grab the worker info from the args
self.worker = args[0]
# grab the output buffer
self.output_buffer = None
if len(args) > 1:
self.output_buffer = args[1]
def run(self):
command = ''
original_filename = ''
original_exif = {}
original_iptc = {}
original_command = {}
process_mode = False
if not int(self.command.get('seed')) > 0:
self.command['seed'] = -1
else:
# increment seed if we've finished one or more complete loops
if control.models != []:
# multiple models in queue, only increment for each time we use all of them
complete = math.floor(control.loops / len(control.models))
seed = int(self.command.get('seed')) + complete
self.command['seed'] = seed
else:
seed = int(self.command.get('seed')) + control.loops
self.command['seed'] = seed
# check for ADetailer params
use_adetailer = False
if control.sdi_adetailer_available and self.command.get('adetailer_use') and self.command.get('adetailer_model') != '':
use_adetailer = True
if '<prompt>' in self.command.get('adetailer_prompt'):
self.command['adetailer_prompt'] = self.command.get('adetailer_prompt').replace('<prompt>', self.command.get('prompt'))
# if this is a process-mode prompt, skip past image generation stuff
if self.command.get('mode') != 'process':
# handle IPTC metadata history stuff
if self.command['iptc_title_history']:
for key in self.command['iptc_title_history']:
self.command['iptc_title'] += self.command['iptc_title_history'][key][-1]
if self.command['iptc_description_history']:
for key in self.command['iptc_description_history']:
self.command['iptc_description'] += self.command['iptc_description_history'][key][-1]
if self.command['iptc_keywords_history']:
for key in self.command['iptc_keywords_history']:
for k in self.command['iptc_keywords_history'][key][-1]:
if k not in self.command['iptc_keywords']:
self.command['iptc_keywords'].append(k)
# if this is a random prompt, settle on random values
if self.command.get('mode') == 'random':
if float(self.command.get('min_scale')) > 0 and float(self.command.get('max_scale')) > 0:
self.command['scale'] = round(random.uniform(float(self.command.get('min_scale')), float(self.command.get('max_scale'))), 1)
if float(self.command.get('min_strength')) > 0 and float(self.command.get('max_strength')) > 0:
self.command['strength'] = round(random.uniform(float(self.command.get('min_strength')), float(self.command.get('max_strength'))), 2)
if self.command.get('random_input_image_dir') != "":
self.command['input_image'] = utils.InputManager(self.command.get('random_input_image_dir')).pick_random()
# settle on random values for ranges specified in scale directive
if '-' in str(self.command['scale']):
try:
values = str(self.command['scale']).split('-', 1)
first = float(values[0].strip())
second = float(values[1].strip())
if second >= first:
self.command['scale'] = round(random.uniform(first, second), 1)
else:
self.command['scale'] = round(random.uniform(second, first), 1)
except:
pass
# settle on random values for ranges specified in strength directive
if '-' in str(self.command['strength']):
try:
values = str(self.command['strength']).split('-', 1)
first = float(values[0].strip())
second = float(values[1].strip())
if second >= first:
self.command['strength'] = round(random.uniform(first, second), 2)
else:
self.command['strength'] = round(random.uniform(second, first), 2)
except:
pass
# settle on random values for ranges specified in steps directive
if '-' in str(self.command['steps']):
try:
values = str(self.command['steps']).split('-', 1)
first = int(values[0].strip())
second = int(values[1].strip())
if second >= first:
self.command['steps'] = random.randint(first, second)
else:
self.command['steps'] = random.randint(second, first)
except:
pass
# settle of random styles if necessary
if len(self.command['styles']) > 0:
if self.command['styles'][0].startswith('random'):
num = 1
styles = []
temp = self.command['styles'][0].split(' ')
if len(temp) > 1:
num = int(temp[1])
# pick random styles
if control.sdi_styles != None and control.sdi_styles != []:
if len(control.sdi_styles) > num:
work = copy.deepcopy(control.sdi_styles)
while num > 0:
pick = random.randint(0, len(work)-1)
styles.append(work[pick]['name'])
work.pop(pick)
num = num - 1
else:
# user asked for more random styles than exist; use all of them
for s in control.sdi_styles:
styles.append(s)
# update command with random styles
self.command['styles'] = styles
# check if a model change is needed
if self.command.get('ckpt_file') != '' and (self.command.get('ckpt_file') != self.worker['sdi_instance'].model_loaded):
self.worker['sdi_instance'].load_model(self.command.get('ckpt_file'))
while self.worker['sdi_instance'].options_change_in_progress:
# wait for model change to complete
time.sleep(0.25)
elif self.command.get('ckpt_file') == '':
# revert to default config.txt model if necessary
if control.config.get('ckpt_file') != '' and control.default_model_validated and (control.config.get('ckpt_file') != self.worker['sdi_instance'].model_loaded):
self.worker['sdi_instance'].load_model(control.config.get('ckpt_file'))
while self.worker['sdi_instance'].options_change_in_progress:
# wait for model change to complete
time.sleep(0.25)
if self.command.get('prompt').strip() == '.':
self.command['prompt'] = ''
else:
# clean up potentially dangerous prompt content:
while '--' in self.command.get('prompt'):
self.command['prompt'] = self.command.get('prompt').replace('--', '-')
# check for auto-insertion of model trigger word
if (control.model_trigger_words != None) and (self.command.get('auto_insert_model_trigger') != 'off'):
# check to see if the model we're using has an associated trigger
if control.model_trigger_words.get(self.command.get('ckpt_file')) != None:
trigger = control.model_trigger_words.get(self.command.get('ckpt_file'))
p = self.command.get('prompt')
if trigger not in p:
# trigger word isn't in prompt, we need to add it
if self.command.get('auto_insert_model_trigger') == 'first_comma':
if ',' in p:
self.command['prompt'] = p.split(',', 1)[0] + ', ' + trigger + ',' + p.split(',', 1)[1]
else:
self.command['prompt'] = p + ', ' + trigger
elif self.command.get('auto_insert_model_trigger') == 'end':
self.command['prompt'] = p + ', ' + trigger
elif self.command.get('auto_insert_model_trigger') == 'start':
self.command['prompt'] = trigger + ', ' + p
elif 'keyword:' in self.command.get('auto_insert_model_trigger'):
keyword = self.command.get('auto_insert_model_trigger')
keyword = keyword.split('keyword:', 1)[1].strip()
if keyword in p:
# the keyword we need to replace with the trigger is in the prompt, replace it
self.command['prompt'] = p.replace(keyword, trigger)
# check to see if the hi-res model we're using has an associated trigger if necessary
# BK 2023-10-29
if self.command.get('highres_ckpt_file') != '':
if control.model_trigger_words.get(self.command.get('highres_ckpt_file')) != None:
trigger = control.model_trigger_words.get(self.command.get('highres_ckpt_file'))
p = self.command.get('highres_prompt')
if p.strip() == '':
p = self.command.get('prompt')
if trigger not in p:
# trigger word isn't in highres prompt, we need to add it
if self.command.get('auto_insert_model_trigger') == 'first_comma':
if ',' in p:
self.command['highres_prompt'] = p.split(',', 1)[0] + ', ' + trigger + ',' + p.split(',', 1)[1]
else:
self.command['highres_prompt'] = p + ', ' + trigger
elif self.command.get('auto_insert_model_trigger') == 'end':
self.command['highres_prompt'] = p + ', ' + trigger
elif self.command.get('auto_insert_model_trigger') == 'start':
self.command['highres_prompt'] = trigger + ', ' + p
elif 'keyword:' in self.command.get('auto_insert_model_trigger'):
keyword = self.command.get('auto_insert_model_trigger')
keyword = keyword.split('keyword:', 1)[1].strip()
if keyword in p:
# the keyword we need to replace with the trigger is in the prompt, replace it
self.command['highres_prompt'] = p.replace(keyword, trigger)
# check for wildcard replacements
p = self.command.get('prompt')
#print('before wildcard replace: ' + self.command['prompt'])
for k, v in control.wildcards.items():
key = '__' + k.lower() + '__'
if key in p.lower():
vcopy = v.copy()
# check if any of the values are wildcard keys themselves
key_replacements = 1
while key_replacements > 0:
key_replacements = 0
for v in vcopy:
#print('Checking ' + v)
check_key = v[2:][:-2].lower()
if check_key in control.wildcards.keys():
key_replacements += 1
#print('\n\nFound nested wildcard: ' + v)
#print('\nList before replacement: ' + str(vcopy))
vcopy.extend(control.wildcards[check_key])
vcopy.remove(v)
#print('\nList after replacement: ' + str(vcopy) + '\n\n')
# this will handle multiple replacements of the same key
while key in p.lower():
replace_all = False
if len(vcopy) > 0:
# pick a random value & remove it from the copied list
x = random.randint(0, len(vcopy)-1)
replace = vcopy.pop(x)
else:
# not enough values to make all replacements, sub '' instead
replace_all = True
replace = ''
# make the replacement(s)
p = utils.wildcard_replace(p, key, replace, replace_all)
# check IPTC metadata and make the same replacement if necessary
self.command['iptc_title'] = utils.wildcard_replace(self.command.get('iptc_title'), key, replace, replace_all)
self.command['iptc_description'] = utils.wildcard_replace(self.command.get('iptc_description'), key, replace, replace_all)
self.command['iptc_keywords'] = utils.wildcard_replace_list(self.command.get('iptc_keywords'), key, replace, replace_all)
self.command['iptc_copyright'] = utils.wildcard_replace(self.command.get('iptc_copyright'), key, replace, replace_all)
# handle special hard-coded prompt directive wildcards
if '__!iptc_title__' in p.lower():
p = utils.wildcard_replace(p, '__!iptc_title__', self.command.get('iptc_title'), True)
if '__!iptc_description__' in p.lower():
p = utils.wildcard_replace(p, '__!iptc_description__', self.command.get('iptc_description'), True)
if '__!iptc_keywords__' in p.lower():
p = utils.wildcard_replace_list(p, '__!iptc_keywords__', self.command.get('iptc_keywords'), True)
self.command['prompt'] = p
#print('after wildcard replace: ' + self.command['prompt'])
# check for auto-dimensions
orig_size = [self.command.get('width'), self.command.get('height')]
if self.command.get('auto_size') == 'match_controlnet_image_size':
if self.command.get('controlnet_input_image') != '':
new_size = utils.get_image_size(self.command.get('controlnet_input_image'))
if new_size != []:
self.command['width'] = new_size[0]
self.command['height'] = new_size[1]
elif self.command.get('auto_size') == 'match_input_image_size':
if self.command.get('input_image') != '':
new_size = utils.get_image_size(self.command.get('input_image'))
if new_size != []:
self.command['width'] = new_size[0]
self.command['height'] = new_size[1]
elif self.command.get('auto_size') == 'match_controlnet_image_aspect_ratio':
if self.command.get('controlnet_input_image') != '':
new_size = utils.match_image_aspect_ratio(self.command.get('controlnet_input_image'), orig_size)
if new_size != []:
self.command['width'] = new_size[0]
self.command['height'] = new_size[1]
elif self.command.get('auto_size') == 'match_input_image_aspect_ratio':
if self.command.get('input_image') != '':
new_size = utils.match_image_aspect_ratio(self.command.get('input_image'), orig_size)
if new_size != []:
self.command['width'] = new_size[0]
self.command['height'] = new_size[1]
elif "resize_longest_dimension:" in self.command.get('auto_size'):
new_long_dim = self.command.get('auto_size').split(':', 1)[1].strip()
new_size = utils.resize_based_on_longest_dimension(new_long_dim, orig_size)
if new_size != []:
self.command['width'] = new_size[0]
self.command['height'] = new_size[1]
# check for ControlNet params
use_controlnet = False
scribble_mode = False
cn_params = [64, 64, 64]
img2img = False
if control.sdi_controlnet_available and self.command.get('controlnet_input_image') != '' and (self.command.get('controlnet_model') != '' or 'reference' in self.command.get('controlnet_pre')):
use_controlnet = True
if self.command.get('input_image') != '':
img2img = True
# encode CN image
encoded = base64.b64encode(open(self.command.get('controlnet_input_image'), "rb").read())
encodedString = str(encoded, encoding='utf-8')
cn_img_payload = 'data:image/png;base64,' + encodedString
# get preprocessor params
if len(self.command.get('controlnet_pre')) >= 3:
found = False
for p in control.sdi_controlnet_preprocessors:
#if self.command.get('controlnet_pre').lower() == p[0]:
# self.command['controlnet_pre'] = p[0]
# cn_params = p[1]
# break
if self.command.get('controlnet_pre').lower() == p.lower():
self.command['controlnet_pre'] = p
# these are the openpose defaults; not sure if these are needed
# TODO: investigate
cn_params = [512, 64, 64]
found = True
break
if not found:
self.command['controlnet_pre'] = 'none'
else:
self.command['controlnet_pre'] = 'none'
# check for auto-model from filename
auto = self.command.get('controlnet_model').lower().strip()
if auto.startswith('auto'):
cn_img = self.command.get('controlnet_input_image')
cn_img = utils.filename_from_abspath(cn_img)
auto_model = ''
# attempt to extract controlnet model from cn input file
if '-' in cn_img:
auto_model = cn_img.split('-', 1)[0]
validated = False
if len(auto_model) >= 3 and control.sdi_controlnet_models != None:
for m in control.sdi_controlnet_models:
if auto_model.lower() in m.lower():
auto_model = m
validated = True
break
if not validated:
auto_model = ''
else:
auto_model = ''
if auto_model == '':
# couldn't get model from filename, check for default
if ',' in auto:
auto_model = auto.rsplit(',', 1)[1].strip()
validated = False
if len(auto_model) >= 3 and control.sdi_controlnet_models != None:
for m in control.sdi_controlnet_models:
if auto_model.lower() in m.lower():
auto_model = m
validated = True
break
if not validated:
auto_model = ''
else:
auto_model = ''
if auto_model == '':
# failed to get model or default, disable CN
use_controlnet = False
self.print('WARNING: automatic ControlNet model specified, but unable to determine valid CN model from input image filename: ' + cn_img + '; disabling ControlNet!')
else:
# we have a valid model, use it
self.command['controlnet_model'] = auto_model
# parameters to pass to SD instance
payload = {}
if self.command.get('input_image') != '':
#img2img
encoded = base64.b64encode(open(self.command.get('input_image'), "rb").read())
encodedString = str(encoded, encoding='utf-8')
img_payload = 'data:image/png;base64,' + encodedString
payload = {
"init_images": [img_payload],
"sampler_index": str(self.command.get('sampler')),
#"resize_mode": 0,
"denoising_strength": self.command.get('strength'),
"prompt": str(self.command.get('prompt')),
"seed": self.command.get('seed'),
"batch_size": self.command.get('batch_size'), # gpu makes this many at once
"n_iter": self.command.get('samples'), # number of iterations to run
"steps": self.command.get('steps'),
"cfg_scale": self.command.get('scale'),
"width": self.command.get('width'),
"height": self.command.get('height'),
#"restore_faces": False,
"tiling": self.command.get('tiling'),
"negative_prompt": str(self.command.get('neg_prompt')),
"alwayson_scripts": {}
}
else:
# txt2img
payload = {
"enable_hr": self.command.get('highres_fix'),
"denoising_strength": self.command.get('strength'),
"sampler_index": str(self.command.get('sampler')),
"prompt": str(self.command.get('prompt')),
"seed": self.command.get('seed'),
"batch_size": self.command.get('batch_size'), # gpu makes this many at once
"n_iter": self.command.get('samples'), # number of iterations to run
"steps": self.command.get('steps'),
"cfg_scale": self.command.get('scale'),
"width": self.command.get('width'),
"height": self.command.get('height'),
#"restore_faces": False,
"tiling": self.command.get('tiling'),
"negative_prompt": str(self.command.get('neg_prompt')),
"alwayson_scripts": {}
}
if self.command['highres_fix'] == 'yes':
if self.command.get('highres_upscaler') != '':
payload["hr_upscaler"] = str(self.command.get('highres_upscaler'))
if self.command.get('highres_ckpt_file') != '':
payload["hr_checkpoint_name"] = str(self.command.get('highres_ckpt_file'))
if self.command.get('highres_sampler') != '':
payload["hr_sampler_name"] = str(self.command.get('highres_sampler'))
if self.command.get('highres_prompt') != '':
if self.command.get('highres_prompt').lower().strip() == '<remove loras>':
# use the main prompt with loras/hypernets stripped out
mp = str(self.command.get('prompt'))
while '<lora:' in mp and '>' in mp:
p = mp
before = p.split('<lora:', 1)[0]
after = p.split('<lora:', 1)[1]
if '>' in after:
after = after.split('>', 1)[1]
mp = (before + after).strip()
else:
mp = before.strip()
while '<hypernet:' in mp and '>' in mp:
p = mp
before = p.split('<hypernet:', 1)[0]
after = p.split('<hypernet:', 1)[1]
if '>' in after:
after = after.split('>', 1)[1]
mp = (before + after).strip()
else:
mp = before.strip()
payload["hr_prompt"] = str(mp)
else:
if '<prompt>' in self.command.get('highres_prompt'):
self.command['highres_prompt'] = self.command.get('highres_prompt').replace('<prompt>', self.command.get('prompt'))
payload["hr_prompt"] = str(self.command.get('highres_prompt'))
if self.command.get('highres_neg_prompt') != '':
if '<neg_prompt>' in self.command.get('highres_neg_prompt'):
self.command['highres_neg_prompt'] = self.command.get('highres_neg_prompt').replace('<neg_prompt>', self.command.get('neg_prompt'))
payload["hr_negative_prompt"] = str(self.command.get('highres_neg_prompt'))
if self.command.get('highres_steps') != '':
payload["hr_second_pass_steps"] = self.command.get('highres_steps')
# add upscaling factor if necessary
if control.config.get('hires_fix_mode') == 'advanced':
if self.command.get('highres_scale_factor') == '':
# set default so we'll have it in metadata
self.command['highres_scale_factor'] = 2.0
payload["hr_scale"] = self.command.get('highres_scale_factor')
else:
# remove these so they don't go into metadata when HR fix is disabled
self.command['highres_scale_factor'] = ''
self.command['highres_upscaler'] = ''
self.command['highres_ckpt_file'] = ''
self.command['highres_sampler'] = ''
self.command['highres_steps'] = ''
self.command['highres_prompt'] = ''
self.command['highres_neg_prompt'] = ''
# add styles to payload if present
if self.command.get('styles') != None and len(self.command.get('styles')) > 0:
payload["styles"] = self.command.get('styles')
# add refiner to payload if present
if self.command.get('refiner_ckpt_file') != '':
payload["refiner_checkpoint"] = str(self.command.get('refiner_ckpt_file'))
if self.command.get('refiner_switch') != '':
payload["refiner_switch_at"] = self.command.get('refiner_switch')
# add CN params to existing payload if ControlNet is enabled
# https://github.com/Mikubill/sd-webui-controlnet/wiki/API
if use_controlnet:
cn_payload = {
"ControlNet": {
"args": [{
"input_image": cn_img_payload,
"mask": "",
"module": str(self.command.get('controlnet_pre')),
"model": str(self.command.get('controlnet_model')),
"weight": float(self.command.get('controlnet_weight')),
#"resize_mode": "Scale to Fit (Inner Fit)",
"lowvram": self.command.get('controlnet_lowvram'),
#"processor_res": cn_params[0],
#"threshold_a": cn_params[1],
#"threshold_b": cn_params[2],
"guidance_start": 0,
"guidance_end": 1,
"control_mode": str(self.command.get('controlnet_controlmode')),
"pixel_perfect": self.command.get('controlnet_pixelperfect')
#"guessmode": self.command.get('controlnet_guessmode') # removed in CN extension v 1.1.09
}]
}
}
#payload["alwayson_scripts"] = cn_payload
payload["alwayson_scripts"].update(cn_payload)
# add ADetailer params to existing payload if ADetailer is enabled
# https://github.com/Bing-su/adetailer/wiki/API
if use_adetailer:
ad_payload = utils.build_adetailer_payload(self.command, True)
if self.command.get('input_image') != '':
ad_payload = utils.build_adetailer_payload(self.command, False)
payload["alwayson_scripts"].update(ad_payload)
# handle override settings here: clip_skip, vae, etc
override_settings = {}
if self.command.get('clip_skip') != '':
override_settings["CLIP_stop_at_last_layers"] = int(self.command.get('clip_skip'))
if self.command.get('input_image') == '' and self.command['highres_fix'] == 'yes' and self.command.get('highres_vae') != '':
# BK 2023-09-26 revert, no separate Auto1111 VAE API setting
#override_settings["sd_vae"] = str(self.command.get('highres_vae'))
pass
else:
if self.command.get('vae') != '':
override_settings["sd_vae"] = self.command.get('vae')
self.command['highres_vae'] = ''
if override_settings != {}:
payload["override_settings"] = override_settings
else:
# !MODE=process -specific stuff here
process_mode = True
original_exif = metadata.read_exif(self.command.get('input_image'))
original_iptc = metadata.read_iptc(self.command.get('input_image'))
if self.command['use_upscale'] == 'yes' and (self.command['upscale_model'] == 'sd' or self.command['upscale_model'] == 'ultimate'):
# get original image parameters if we're doing a SD upscale
original_details = ''
if original_exif != None:
try:
original_details = original_exif[0x9c9c].decode('utf16')
except KeyError as e:
pass
else:
original_command = utils.extract_params_from_command(original_details)
original_filename = utils.filename_from_abspath(self.command.get('input_image')).lower().strip()
# remove extension
original_filename = original_filename[:-4]
# check for !OUTPUT_DIR, create if necessary
if self.command.get('output_dir') != '':
if not os.path.exists(self.command.get('output_dir')):
try:
# attempt to create output directory
Path(self.command.get('output_dir')).mkdir(parents=True, exist_ok=True)
except:
# error creating specified output_dir, fallback to default
self.print("Specified OUTPUT_DIR could not be created: " + self.command.get('output_dir'))
self.print("Using default output directory instead...")
self.command['output_dir'] = ''
# !MODE = process enters here:
command = utils.create_command(self.command, self.command.get('prompt_file'), self.worker['id'])
if not process_mode:
self.print("starting job #" + str(self.worker['jobs_done']+1) + ": " + command)
else:
self.print("starting job #" + str(self.worker['jobs_done']+1) + ": batch processing...")
start_time = time.time()
self.worker['job_start_time'] = start_time
self.worker['job_prompt_info'] = self.command
output_dir = command.split(" --outdir ",1)[1].strip('\"')
#output_dir = output_dir.replace("../","")
if "cuda:" in self.worker['id']:
gpu_id = self.worker['id'].replace('cuda:', '')
else:
gpu_id = self.worker['id']
#samples_dir = os.path.join(output_dir, "gpu_" + str(gpu_id))
samples_dir = output_dir + '/' + "gpu_" + str(gpu_id)
#self.worker['sdi_instance'].last_job_success = True
if control.config.get('debug_test_mode') and not process_mode:
# simulate SD work
work_time = round(random.uniform(2, 6), 2)
time.sleep(work_time)
else:
# invoke SD
if not process_mode:
if self.command.get('input_image') != '':
if use_controlnet:
#self.worker['sdi_instance'].do_controlnet_img2img(payload, samples_dir)
self.worker['sdi_instance'].do_img2img(payload, samples_dir)
else:
self.worker['sdi_instance'].do_img2img(payload, samples_dir)
else:
if use_controlnet:
#self.worker['sdi_instance'].do_controlnet_txt2img(payload, samples_dir)
self.worker['sdi_instance'].do_txt2img(payload, samples_dir)
else:
self.worker['sdi_instance'].do_txt2img(payload, samples_dir)
while self.worker['sdi_instance'].busy and self.worker['sdi_instance'].isRunning:
time.sleep(0.25)
# upscale here if requested
if (self.worker['sdi_instance'].last_job_success or process_mode) and self.worker['sdi_instance'].isRunning:
# only if we're not shutting down
use_upscale = False
if self.command['use_upscale'] == 'yes':
use_upscale = True
if use_upscale or use_adetailer:
if use_upscale:
self.worker['work_state'] = 'upscaling'
elif use_adetailer:
self.worker['work_state'] = 'adetailer'
else:
self.worker['work_state'] = 'processing'
gpu_id = self.worker['id'].replace("cuda:", "")
if control.config.get('debug_test_mode'):
# simulate upscaling work
work_time = round(random.uniform(0.5, 2), 2)
time.sleep(work_time)
else:
new_files = []
if not process_mode:
# upscale all newly-generated images for non-process mode
new_files = os.listdir(samples_dir)
else:
# if process mode, upscale the designated image
new_files.append(self.command.get('input_image'))
if len(new_files) > 0:
# invoke ESRGAN on entire directory
#utils.upscale(self.command['upscale_amount'], samples_dir, self.command['upscale_face_enh'], gpu_id)
# upscale each image
if not process_mode:
self.worker['sdi_instance'].log('upscaling images...')
else:
if use_upscale:
self.worker['sdi_instance'].log('upscaling ' + self.command.get('input_image') + '...')
elif use_adetailer:
self.worker['sdi_instance'].log('adetailer: ' + self.command.get('input_image') + '...')
else:
self.worker['sdi_instance'].log('processing ' + self.command.get('input_image') + '...')
for file in new_files:
encoded = None
if not process_mode:
encoded = base64.b64encode(open(os.path.join(samples_dir, file), "rb").read())
else:
# this whole process_mode thread is pretty hacky...
encoded = base64.b64encode(open(self.command.get('input_image'), "rb").read())
encodedString = str(encoded, encoding='utf-8')
img_payload = 'data:image/png;base64,' + encodedString
if use_upscale:
if self.command['upscale_model'] != 'sd' and self.command['upscale_model'] != 'ultimate':
# normal upscale
payload = {
#"resize_mode": 0,
#"show_extras_results": true,
"gfpgan_visibility": self.command['upscale_gfpgan_amount'],
"codeformer_visibility": self.command['upscale_codeformer_amount'],
#"codeformer_weight": 0,
"upscaling_resize": self.command['upscale_amount'],
#"upscaling_resize_w": 512,
#"upscaling_resize_h": 512,
#"upscaling_crop": true,
"upscaler_1": self.command['upscale_model'],
#"upscaler_2": "None",
#"extras_upscaler_2_visibility": 0,
#"upscale_first": false,
"image": img_payload
}
self.worker['sdi_instance'].do_upscale(payload, samples_dir)
else:
# SD upscale uses img2img
# use whatever params we can find in original image
sd_sampler = str(self.command.get('sampler'))
if "sampler" in original_command:
sd_sampler = original_command['sampler']
# validate sampler in case we're upscaling very old images
if control.prompt_manager != None:
# TODO: should instantiate new prompt_manager if we don't have one yet
sd_sampler = control.prompt_manager.validate_sampler(sd_sampler, True)
sd_vae = str(self.command.get('vae'))
if "vae" in original_command:
sd_vae = original_command['vae']
sd_prompt = str(self.command.get('prompt'))
if "prompt" in original_command:
sd_prompt = original_command['prompt']
sd_neg_prompt = str(self.command.get('neg_prompt'))
if "neg_prompt" in original_command:
sd_neg_prompt = original_command['neg_prompt']
sd_seed = str(self.command.get('seed'))
if "seed" in original_command:
try:
sd_seed = int(original_command['seed'])
except:
pass
sd_steps = self.command.get('steps')
if "steps" in original_command:
try:
sd_steps = int(original_command['steps'])
except:
pass
sd_scale = self.command.get('scale')
if "scale" in original_command:
try:
sd_scale = float(original_command['scale'])
except:
pass
sd_tiling = self.command.get('tiling')
if "tiling" in original_command:
if original_command['tiling'] == 'yes':
sd_tiling = True
else:
sd_tiling = False
# grab styles from original command and put into list
styles = []
if "styles" in original_command:
if original_command['styles'] != '':
temp = original_command['styles'].split(',')
for t in temp:
styles.append(t.strip())
# calculate max output size for sd_upscale
orig_width = 0
orig_height = 0
sd_width = 512
sd_height = 512
if self.command['upscale_model'] == 'sd':
with Image.open(self.command.get('input_image')) as img:
orig_width, orig_height = img.size
set_max_output_size = control.config.get('max_output_size')
# check for overrides in process mode directives
if self.command.get('override_max_output_size') != 0:
set_max_output_size = int(self.command.get('override_max_output_size'))
new_dimensions = utils.get_largest_possible_image_size([orig_width, orig_height], set_max_output_size, True)
if new_dimensions != []:
sd_width = new_dimensions[0]
sd_height = new_dimensions[1]
self.command['width'] = sd_width
self.command['height'] = sd_height
else:
control.print('Error: SD upscale unable to find appropriate upscale size under MAX_OUTPUT_SIZE for ' + str(self.command.get('input_image')) + '!')
if self.command.get('override_steps') != 0:
sd_steps = self.command.get('override_steps')
if self.command.get('override_sampler') != '':
sd_sampler = self.command.get('override_sampler')
# check if a model change is needed before upscaling
override_model = ''
sd_model = str(self.command.get('ckpt_file'))
if "ckpt_file" in original_command:
sd_model = original_command['ckpt_file']
sd_model = control.validate_model(sd_model)
# check if we're overriding the model for upscaling
if self.command.get('override_ckpt_file') != '':
override_model = control.validate_model(self.command.get('override_ckpt_file'))
if override_model != '':
sd_model = override_model
# check if a refiner model is available if necessary
if override_model == '':
if control.config.get('auto_use_refiner'):
refiner_model = original_command['ckpt_file'].replace('.safetensors', '').replace('.ckpt', '')
if '[' in refiner_model:
refiner_model = refiner_model.split('[', 1)[0].strip()
refiner_model = refiner_model + '_refiner'
refiner_model = control.validate_model(refiner_model)
if refiner_model != '':
sd_model = refiner_model
if sd_model != '' and (sd_model != self.worker['sdi_instance'].model_loaded):
self.worker['sdi_instance'].load_model(sd_model)
while self.worker['sdi_instance'].options_change_in_progress:
# wait for model change to complete
time.sleep(0.25)
payload = {
"init_images": [img_payload],
"sampler_index": str(sd_sampler),
#"resize_mode": 0,
"denoising_strength": self.command.get('upscale_sd_strength'),
"prompt": str(sd_prompt),
"seed": str(sd_seed),
"batch_size": 1,
"n_iter": 1,
"steps": sd_steps,
"cfg_scale": sd_scale,
"width": sd_width,
"height": sd_height,
#"restore_faces": False,
"tiling": sd_tiling,
"negative_prompt": sd_neg_prompt,
"alwayson_scripts": {}
}
# add styles to payload if present
if styles != []:
payload["styles"] = styles
override_settings = {}
if self.command.get('clip_skip') != '':
override_settings["CLIP_stop_at_last_layers"] = int(self.command.get('clip_skip'))
if self.command.get('override_vae') != '':
override_settings["sd_vae"] = self.command.get('override_vae')
else:
if override_model == '':
if sd_vae != '':
override_settings["sd_vae"] = sd_vae
if override_settings != {}:
payload["override_settings"] = override_settings
# add additional sd_ultimate_upscale params if necessary
if self.command['upscale_model'] == 'ultimate':
up_index = control.get_upscale_model_index(self.command['upscale_ult_model'])
if up_index == -1:
up_index = control.get_upscale_model_index('ESRGAN_4x')
if up_index == -1:
up_index = 0
custom_scale = 2.0
if 'upscale_amount' in self.command and float(self.command['upscale_amount']) > 1.0:
custom_scale = self.command['upscale_amount']
custom_scale = float(custom_scale)
# docs: https://github.com/Coyote-A/ultimate-upscale-for-automatic1111
payload["script_name"] = "ultimate sd upscale"
payload["script_args"] = [
"", # (not used)
512, # tile_width
512, # tile_height
8, # mask_blur
32, # padding
64, # seams_fix_width
0.35, # seams_fix_denoise
32, # seams_fix_padding
up_index, # upscaler_index
True, # save_upscaled_image a.k.a Upscaled
0, # redraw_mode
False, # save_seams_fix_image a.k.a Seams fix
8, # seams_fix_mask_blur
0, # seams_fix_type
2, # target_size_type (0 = From img2img2 settings, 1 = Custom size, 2 = Scale from image size)
2048, # custom_width
2048, # custom_height
custom_scale # custom_scale
]
# add adetailer if specified
if use_adetailer:
ad_payload = utils.build_adetailer_payload(self.command, True)
payload["alwayson_scripts"].update(ad_payload)
self.worker['sdi_instance'].do_img2img(payload, samples_dir)
else:
# We're just doing ADetailer; no upscale...
payload = {
"init_images": [img_payload],
"alwayson_scripts": {}
}
ad_payload = utils.build_adetailer_payload(self.command, True)
payload["alwayson_scripts"].update(ad_payload)
self.worker['sdi_instance'].do_img2img(payload, samples_dir)
while self.worker['sdi_instance'].busy and self.worker['sdi_instance'].isRunning:
time.sleep(0.25)
# remove originals if upscaled version present
if not process_mode:
new_files = os.listdir(samples_dir)
for f in new_files:
if (".png" in f):
basef = f.replace(".png", "")
if basef[-2:] == "_u":
# this is an upscaled image, delete the original
# or save it in /original if desired
if exists(samples_dir + "/" + basef[:-2] + ".png"):
if self.command['upscale_keep_org'] == 'yes':
# move the original to /original
orig_dir = output_dir + "/original"
Path(orig_dir).mkdir(parents=True, exist_ok=True)
os.replace(samples_dir + "/" + basef[:-2] + ".png", \
orig_dir + "/" + basef[:-2] + ".png")
else:
os.remove(samples_dir + "/" + basef[:-2] + ".png")
# find the new image(s) that SD created: re-name, process, and move them
if self.worker['sdi_instance'].last_job_success and self.worker['sdi_instance'].isRunning:
# only if we're not shutting down
self.worker['work_state'] = "+exif data"
if control.config.get('debug_test_mode'):
# simulate metadata work
work_time = round(random.uniform(1, 2), 2)
time.sleep(work_time)
else:
new_files = []
if exists(samples_dir):
new_files = os.listdir(samples_dir)
nf_count = 0
for f in new_files:
if (".png" in f):
# save just the essential prompt params to metadata
meta_prompt = command.split(" --prompt ",1)[1]
meta_prompt = meta_prompt.split(" --outdir ",1)[0]
if 'seed_' in f:
# grab seed from filename
# filename = seed_3542762265.png or seed_3542762265_u.png
actual_seed = f.replace('seed_', '')
actual_seed = actual_seed.replace('_u', '')