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Merge branch 'beta' into yaml

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10
CHANGES.md
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@ -5,7 +5,7 @@
- **Nearly twice as fast** - significantly faster speed of image generation. We're now pretty close to automatic1111's speed. Code contributions are welcome to make our project even faster: https://github.com/easydiffusion/sdkit/#is-it-fast
- **Full support for Stable Diffusion 2.1 (including CPU)** - supports loading v1.4 or v2.0 or v2.1 models seamlessly. No need to enable "Test SD2", and no need to add `sd2_` to your SD 2.0 model file names. Works on CPU as well.
- **Memory optimized Stable Diffusion 2.1** - you can now use Stable Diffusion 2.1 models, with the same low VRAM optimizations that we've always had for SD 1.4. Please note, the SD 2.0 and 2.1 models require more GPU and System RAM, as compared to the SD 1.4 and 1.5 models.
- **6 new samplers!** - explore the new samplers, some of which can generate great images in less than 10 inference steps!
- **11 new samplers!** - explore the new samplers, some of which can generate great images in less than 10 inference steps! We've added the Karras and UniPC samplers.
- **Model Merging** - You can now merge two models (`.ckpt` or `.safetensors`) and output `.ckpt` or `.safetensors` models, optionally in `fp16` precision. Details: https://github.com/cmdr2/stable-diffusion-ui/wiki/Model-Merging
- **Fast loading/unloading of VAEs** - No longer needs to reload the entire Stable Diffusion model, each time you change the VAE
- **Database of known models** - automatically picks the right configuration for known models. E.g. we automatically detect and apply "v" parameterization (required for some SD 2.0 models), and "fp32" attention precision (required for some SD 2.1 models).
@ -19,6 +19,14 @@
Our focus continues to remain on an easy installation experience, and an easy user-interface. While still remaining pretty powerful, in terms of features and speed.
### Detailed changelog
* 2.5.20 - 18 Feb 2023 - Upgrade the version of transformers used.
* 2.5.19 - 17 Feb 2023 - Initial support for server-side plugins. Currently supports overriding the `get_cond_and_uncond()` function.
* 2.5.18 - 17 Feb 2023 - 5 new samplers! UniPC samplers, some of which produce images in less than 15 steps. Thanks @Schorny.
* 2.5.16 - 13 Feb 2023 - Searchable dropdown for models. This is useful if you have a LOT of models. You can type part of the model name, to auto-search through your models. Thanks @patriceac for the feature, and @AssassinJN for help in UI tweaks!
* 2.5.16 - 13 Feb 2023 - Lots of fixes and improvements to the installer. First round of changes to add Mac support. Thanks @JeLuf.
* 2.5.16 - 13 Feb 2023 - UI bug fixes for the inpainter editor. Thanks @patriceac.
* 2.5.16 - 13 Feb 2023 - Fix broken task reorder. Thanks @JeLuf.
* 2.5.16 - 13 Feb 2023 - Remove a task if all the images inside it have been removed. Thanks @AssassinJN.
* 2.5.16 - 10 Feb 2023 - Embed metadata into the JPG/PNG images, if selected in the "Settings" tab (under "Metadata format"). Thanks @patriceac.
* 2.5.16 - 10 Feb 2023 - Sort models alphabetically in the models dropdown. Thanks @ogmaresca.
* 2.5.16 - 10 Feb 2023 - Support multiple GFPGAN models. Download new GFPGAN models into the `models/gfpgan` folder, and refresh the UI to use it. Thanks @JeLuf.

4
scripts/bootstrap.sh
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@ -29,7 +29,9 @@ if ! which tar; then fail "'tar' not found. Please install tar."; fi
if ! which bzip2; then fail "'bzip2' not found. Please install bzip2."; fi
if pwd | grep ' '; then fail "The installation directory's path contains a space character. Conda will fail to install. Please change the directory."; fi
if ! cat /proc/cpuinfo | grep avx | uniq; then fail "Your CPU doesn't support AVX."; fi
if [ -f /proc/cpuinfo ]; then
if ! cat /proc/cpuinfo | grep avx | uniq; then fail "Your CPU doesn't support AVX."; fi
fi
# https://mamba.readthedocs.io/en/latest/installation.html
if [ "$OS_NAME" == "linux" ] && [ "$OS_ARCH" == "arm64" ]; then OS_ARCH="aarch64"; fi

4
scripts/on_sd_start.bat
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@ -92,7 +92,7 @@ if "%ERRORLEVEL%" EQU "0" (
set PYTHONNOUSERSITE=1
set PYTHONPATH=%INSTALL_ENV_DIR%\lib\site-packages
call python -m pip install --upgrade sdkit==1.0.36 -q || (
call python -m pip install --upgrade sdkit==1.0.40 -q || (
echo "Error updating sdkit"
)
)
@ -113,7 +113,7 @@ if "%ERRORLEVEL%" EQU "0" (
call python -c "from importlib.metadata import version; print('sdkit version:', version('sdkit'))"
@rem upgrade stable-diffusion-sdkit
call python -m pip install --upgrade stable-diffusion-sdkit -q || (
call python -m pip install --upgrade stable-diffusion-sdkit==2.1.3 -q || (
echo "Error updating stable-diffusion-sdkit"
)
call python -c "from importlib.metadata import version; print('stable-diffusion version:', version('stable-diffusion-sdkit'))"

4
scripts/on_sd_start.sh
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@ -81,7 +81,7 @@ if python ../scripts/check_modules.py sdkit sdkit.models ldm transformers numpy
export PYTHONNOUSERSITE=1
export PYTHONPATH="$INSTALL_ENV_DIR/lib/python3.8/site-packages"
python -m pip install --upgrade sdkit==1.0.36 -q
python -m pip install --upgrade sdkit==1.0.40 -q
fi
else
echo "Installing sdkit: https://pypi.org/project/sdkit/"
@ -99,7 +99,7 @@ fi
python -c "from importlib.metadata import version; print('sdkit version:', version('sdkit'))"
# upgrade stable-diffusion-sdkit
python -m pip install --upgrade stable-diffusion-sdkit -q
python -m pip install --upgrade stable-diffusion-sdkit==2.1.3 -q
python -c "from importlib.metadata import version; print('stable-diffusion version:', version('stable-diffusion-sdkit'))"
# install rich

160
ui/easydiffusion/app.py
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@ -10,7 +10,7 @@ yaml = YAML()
from rich.logging import RichHandler
from sdkit.utils import log as sdkit_log # hack, so we can overwrite the log config
from sdkit.utils import log as sdkit_log # hack, so we can overwrite the log config
from easydiffusion import task_manager
from easydiffusion.utils import log
@ -19,43 +19,54 @@ from easydiffusion.utils import log
for handler in logging.root.handlers[:]:
logging.root.removeHandler(handler)
LOG_FORMAT = '%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s'
LOG_FORMAT = "%(asctime)s.%(msecs)03d %(levelname)s %(threadName)s %(message)s"
logging.basicConfig(
level=logging.INFO,
format=LOG_FORMAT,
datefmt="%X",
handlers=[RichHandler(markup=True, rich_tracebacks=False, show_time=False, show_level=False)],
level=logging.INFO,
format=LOG_FORMAT,
datefmt="%X",
handlers=[RichHandler(markup=True, rich_tracebacks=False, show_time=False, show_level=False)],
)
SD_DIR = os.getcwd()
SD_UI_DIR = os.getenv('SD_UI_PATH', None)
SD_UI_DIR = os.getenv("SD_UI_PATH", None)
CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "..", "scripts"))
MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "models"))
USER_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, "..", "plugins"))
CORE_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, "plugins"))
USER_UI_PLUGINS_DIR = os.path.join(USER_PLUGINS_DIR, "ui")
CORE_UI_PLUGINS_DIR = os.path.join(CORE_PLUGINS_DIR, "ui")
USER_SERVER_PLUGINS_DIR = os.path.join(USER_PLUGINS_DIR, "server")
UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, "core"), (USER_UI_PLUGINS_DIR, "user"))
sys.path.append(os.path.dirname(SD_UI_DIR))
sys.path.append(USER_SERVER_PLUGINS_DIR)
CONFIG_DIR = os.path.abspath(os.path.join(SD_UI_DIR, '..', 'scripts'))
MODELS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'models'))
USER_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_DIR, '..', 'plugins', 'ui'))
CORE_UI_PLUGINS_DIR = os.path.abspath(os.path.join(SD_UI_DIR, 'plugins', 'ui'))
UI_PLUGINS_SOURCES = ((CORE_UI_PLUGINS_DIR, 'core'), (USER_UI_PLUGINS_DIR, 'user'))
OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
PRESERVE_CONFIG_VARS = ['FORCE_FULL_PRECISION']
TASK_TTL = 15 * 60 # Discard last session's task timeout
OUTPUT_DIRNAME = "Stable Diffusion UI" # in the user's home folder
PRESERVE_CONFIG_VARS = ["FORCE_FULL_PRECISION"]
TASK_TTL = 15 * 60 # Discard last session's task timeout
APP_CONFIG_DEFAULTS = {
# auto: selects the cuda device with the most free memory, cuda: use the currently active cuda device.
'render_devices': 'auto', # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
'update_branch': 'main',
'ui': {
'open_browser_on_start': True,
}
"render_devices": "auto", # valid entries: 'auto', 'cpu' or 'cuda:N' (where N is a GPU index)
"update_branch": "main",
"ui": {
"open_browser_on_start": True,
},
}
def init():
os.makedirs(USER_UI_PLUGINS_DIR, exist_ok=True)
os.makedirs(USER_SERVER_PLUGINS_DIR, exist_ok=True)
load_server_plugins()
update_render_threads()
def getConfig(default_val=APP_CONFIG_DEFAULTS):
config_yaml_path = os.path.join(CONFIG_DIR, 'config.yaml')
if os.path.isfile(config_yaml_path):
@ -95,6 +106,7 @@ def getConfig(default_val=APP_CONFIG_DEFAULTS):
log.warn(traceback.format_exc())
return default_val
def setConfig(config):
try: # config.yaml
config_yaml_path = os.path.join(CONFIG_DIR, 'config.yaml')
@ -104,15 +116,15 @@ def setConfig(config):
except:
log.error(traceback.format_exc())
try: # config.bat
config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
try: # config.bat
config_bat_path = os.path.join(CONFIG_DIR, "config.bat")
config_bat = []
if 'update_branch' in config:
if "update_branch" in config:
config_bat.append(f"@set update_branch={config['update_branch']}")
config_bat.append(f"@set SD_UI_BIND_PORT={config['net']['listen_port']}")
bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
bind_ip = "0.0.0.0" if config["net"]["listen_to_network"] else "127.0.0.1"
config_bat.append(f"@set SD_UI_BIND_IP={bind_ip}")
# Preserve these variables if they are set
@ -121,20 +133,20 @@ def setConfig(config):
config_bat.append(f"@set {var}={os.getenv(var)}")
if len(config_bat) > 0:
with open(config_bat_path, 'w', encoding='utf-8') as f:
f.write('\r\n'.join(config_bat))
with open(config_bat_path, "w", encoding="utf-8") as f:
f.write("\n".join(config_bat))
except:
log.error(traceback.format_exc())
try: # config.sh
config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
config_sh = ['#!/bin/bash']
try: # config.sh
config_sh_path = os.path.join(CONFIG_DIR, "config.sh")
config_sh = ["#!/bin/bash"]
if 'update_branch' in config:
if "update_branch" in config:
config_sh.append(f"export update_branch={config['update_branch']}")
config_sh.append(f"export SD_UI_BIND_PORT={config['net']['listen_port']}")
bind_ip = '0.0.0.0' if config['net']['listen_to_network'] else '127.0.0.1'
bind_ip = "0.0.0.0" if config["net"]["listen_to_network"] else "127.0.0.1"
config_sh.append(f"export SD_UI_BIND_IP={bind_ip}")
# Preserve these variables if they are set
@ -143,47 +155,86 @@ def setConfig(config):
config_bat.append(f'export {var}="{shlex.quote(os.getenv(var))}"')
if len(config_sh) > 1:
with open(config_sh_path, 'w', encoding='utf-8') as f:
f.write('\n'.join(config_sh))
with open(config_sh_path, "w", encoding="utf-8") as f:
f.write("\n".join(config_sh))
except:
log.error(traceback.format_exc())
def save_to_config(ckpt_model_name, vae_model_name, hypernetwork_model_name, vram_usage_level):
config = getConfig()
if 'model' not in config:
config['model'] = {}
if "model" not in config:
config["model"] = {}
config['model']['stable-diffusion'] = ckpt_model_name
config['model']['vae'] = vae_model_name
config['model']['hypernetwork'] = hypernetwork_model_name
config["model"]["stable-diffusion"] = ckpt_model_name
config["model"]["vae"] = vae_model_name
config["model"]["hypernetwork"] = hypernetwork_model_name
if vae_model_name is None or vae_model_name == "":
del config['model']['vae']
del config["model"]["vae"]
if hypernetwork_model_name is None or hypernetwork_model_name == "":
del config['model']['hypernetwork']
del config["model"]["hypernetwork"]
config['vram_usage_level'] = vram_usage_level
config["vram_usage_level"] = vram_usage_level
setConfig(config)
def update_render_threads():
config = getConfig()
render_devices = config.get('render_devices', 'auto')
active_devices = task_manager.get_devices()['active'].keys()
render_devices = config.get("render_devices", "auto")
active_devices = task_manager.get_devices()["active"].keys()
log.debug(f'requesting for render_devices: {render_devices}')
log.debug(f"requesting for render_devices: {render_devices}")
task_manager.update_render_threads(render_devices, active_devices)
def getUIPlugins():
plugins = []
for plugins_dir, dir_prefix in UI_PLUGINS_SOURCES:
for file in os.listdir(plugins_dir):
if file.endswith('.plugin.js'):
plugins.append(f'/plugins/{dir_prefix}/{file}')
if file.endswith(".plugin.js"):
plugins.append(f"/plugins/{dir_prefix}/{file}")
return plugins
def load_server_plugins():
if not os.path.exists(USER_SERVER_PLUGINS_DIR):
return
import importlib
def load_plugin(file):
mod_path = file.replace(".py", "")
return importlib.import_module(mod_path)
def apply_plugin(file, plugin):
if hasattr(plugin, "get_cond_and_uncond"):
import sdkit.generate.image_generator
sdkit.generate.image_generator.get_cond_and_uncond = plugin.get_cond_and_uncond
log.info(f"Overridden get_cond_and_uncond with the one in the server plugin: {file}")
for file in os.listdir(USER_SERVER_PLUGINS_DIR):
file_path = os.path.join(USER_SERVER_PLUGINS_DIR, file)
if (not os.path.isdir(file_path) and not file_path.endswith("_plugin.py")) or (
os.path.isdir(file_path) and not file_path.endswith("_plugin")
):
continue
try:
log.info(f"Loading server plugin: {file}")
mod = load_plugin(file)
log.info(f"Applying server plugin: {file}")
apply_plugin(file, mod)
except:
log.warn(f"Error while loading a server plugin")
log.warn(traceback.format_exc())
def getIPConfig():
try:
ips = socket.gethostbyname_ex(socket.gethostname())
@ -193,10 +244,13 @@ def getIPConfig():
log.exception(e)
return []
def open_browser():
config = getConfig()
ui = config.get('ui', {})
net = config.get('net', {'listen_port':9000})
port = net.get('listen_port', 9000)
if ui.get('open_browser_on_start', True):
import webbrowser; webbrowser.open(f"http://localhost:{port}")
ui = config.get("ui", {})
net = config.get("net", {"listen_port": 9000})
port = net.get("listen_port", 9000)
if ui.get("open_browser_on_start", True):
import webbrowser
webbrowser.open(f"http://localhost:{port}")

134
ui/easydiffusion/device_manager.py
View File

@ -5,45 +5,54 @@ import re
from easydiffusion.utils import log
'''
"""
Set `FORCE_FULL_PRECISION` in the environment variables, or in `config.bat`/`config.sh` to set full precision (i.e. float32).
Otherwise the models will load at half-precision (i.e. float16).
Half-precision is fine most of the time. Full precision is only needed for working around GPU bugs (like NVIDIA 16xx GPUs).
'''
"""
COMPARABLE_GPU_PERCENTILE = 0.65 # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
COMPARABLE_GPU_PERCENTILE = (
0.65 # if a GPU's free_mem is within this % of the GPU with the most free_mem, it will be picked
)
mem_free_threshold = 0
def get_device_delta(render_devices, active_devices):
'''
"""
render_devices: 'cpu', or 'auto' or ['cuda:N'...]
active_devices: ['cpu', 'cuda:N'...]
'''
"""
if render_devices in ('cpu', 'auto'):
if render_devices in ("cpu", "auto"):
render_devices = [render_devices]
elif render_devices is not None:
if isinstance(render_devices, str):
render_devices = [render_devices]
if isinstance(render_devices, list) and len(render_devices) > 0:
render_devices = list(filter(lambda x: x.startswith('cuda:'), render_devices))
render_devices = list(filter(lambda x: x.startswith("cuda:"), render_devices))
if len(render_devices) == 0:
raise Exception('Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}')
raise Exception(
'Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}'
)
render_devices = list(filter(lambda x: is_device_compatible(x), render_devices))
if len(render_devices) == 0:
raise Exception('Sorry, none of the render_devices configured in config.json are compatible with Stable Diffusion')
raise Exception(
"Sorry, none of the render_devices configured in config.json are compatible with Stable Diffusion"
)
else:
raise Exception('Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}')
raise Exception(
'Invalid render_devices value in config.json. Valid: {"render_devices": ["cuda:0", "cuda:1"...]}, or {"render_devices": "cpu"} or {"render_devices": "auto"}'
)
else:
render_devices = ['auto']
render_devices = ["auto"]
if 'auto' in render_devices:
if "auto" in render_devices:
render_devices = auto_pick_devices(active_devices)
if 'cpu' in render_devices:
log.warn('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
if "cpu" in render_devices:
log.warn("WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!")
active_devices = set(active_devices)
render_devices = set(render_devices)
@ -53,19 +62,21 @@ def get_device_delta(render_devices, active_devices):
return devices_to_start, devices_to_stop
def auto_pick_devices(currently_active_devices):
global mem_free_threshold
if not torch.cuda.is_available(): return ['cpu']
if not torch.cuda.is_available():
return ["cpu"]
device_count = torch.cuda.device_count()
if device_count == 1:
return ['cuda:0'] if is_device_compatible('cuda:0') else ['cpu']
return ["cuda:0"] if is_device_compatible("cuda:0") else ["cpu"]
log.debug('Autoselecting GPU. Using most free memory.')
log.debug("Autoselecting GPU. Using most free memory.")
devices = []
for device in range(device_count):
device = f'cuda:{device}'
device = f"cuda:{device}"
if not is_device_compatible(device):
continue
@ -73,11 +84,13 @@ def auto_pick_devices(currently_active_devices):
mem_free /= float(10**9)
mem_total /= float(10**9)
device_name = torch.cuda.get_device_name(device)
log.debug(f'{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb')
devices.append({'device': device, 'device_name': device_name, 'mem_free': mem_free})
log.debug(
f"{device} detected: {device_name} - Memory (free/total): {round(mem_free, 2)}Gb / {round(mem_total, 2)}Gb"
)
devices.append({"device": device, "device_name": device_name, "mem_free": mem_free})
devices.sort(key=lambda x:x['mem_free'], reverse=True)
max_mem_free = devices[0]['mem_free']
devices.sort(key=lambda x: x["mem_free"], reverse=True)
max_mem_free = devices[0]["mem_free"]
curr_mem_free_threshold = COMPARABLE_GPU_PERCENTILE * max_mem_free
mem_free_threshold = max(curr_mem_free_threshold, mem_free_threshold)
@ -87,23 +100,26 @@ def auto_pick_devices(currently_active_devices):
# always be very low (since their VRAM contains the model).
# These already-running devices probably aren't terrible, since they were picked in the past.
# Worst case, the user can restart the program and that'll get rid of them.
devices = list(filter((lambda x: x['mem_free'] > mem_free_threshold or x['device'] in currently_active_devices), devices))
devices = list(map(lambda x: x['device'], devices))
devices = list(
filter((lambda x: x["mem_free"] > mem_free_threshold or x["device"] in currently_active_devices), devices)
)
devices = list(map(lambda x: x["device"], devices))
return devices
def device_init(context, device):
'''
"""
This function assumes the 'device' has already been verified to be compatible.
`get_device_delta()` has already filtered out incompatible devices.
'''
"""
validate_device_id(device, log_prefix='device_init')
validate_device_id(device, log_prefix="device_init")
if device == 'cpu':
context.device = 'cpu'
if device == "cpu":
context.device = "cpu"
context.device_name = get_processor_name()
context.half_precision = False
log.debug(f'Render device CPU available as {context.device_name}')
log.debug(f"Render device CPU available as {context.device_name}")
return
context.device_name = torch.cuda.get_device_name(device)
@ -111,7 +127,7 @@ def device_init(context, device):
# Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
if needs_to_force_full_precision(context):
log.warn(f'forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}')
log.warn(f"forcing full precision on this GPU, to avoid green images. GPU detected: {context.device_name}")
# Apply force_full_precision now before models are loaded.
context.half_precision = False
@ -120,72 +136,90 @@ def device_init(context, device):
return
def needs_to_force_full_precision(context):
if 'FORCE_FULL_PRECISION' in os.environ:
if "FORCE_FULL_PRECISION" in os.environ:
return True
device_name = context.device_name.lower()
return (('nvidia' in device_name or 'geforce' in device_name or 'quadro' in device_name) and (' 1660' in device_name or ' 1650' in device_name or ' t400' in device_name or ' t550' in device_name or ' t600' in device_name or ' t1000' in device_name or ' t1200' in device_name or ' t2000' in device_name))
return ("nvidia" in device_name or "geforce" in device_name or "quadro" in device_name) and (
" 1660" in device_name
or " 1650" in device_name
or " t400" in device_name
or " t550" in device_name
or " t600" in device_name
or " t1000" in device_name
or " t1200" in device_name
or " t2000" in device_name
)
def get_max_vram_usage_level(device):
if device != 'cpu':
if device != "cpu":
_, mem_total = torch.cuda.mem_get_info(device)
mem_total /= float(10**9)
if mem_total < 4.5:
return 'low'
return "low"
elif mem_total < 6.5:
return 'balanced'
return "balanced"
return 'high'
return "high"
def validate_device_id(device, log_prefix=''):
def validate_device_id(device, log_prefix=""):
def is_valid():
if not isinstance(device, str):
return False
if device == 'cpu':
if device == "cpu":
return True
if not device.startswith('cuda:') or not device[5:].isnumeric():
if not device.startswith("cuda:") or not device[5:].isnumeric():
return False
return True
if not is_valid():
raise EnvironmentError(f"{log_prefix}: device id should be 'cpu', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}")
raise EnvironmentError(
f"{log_prefix}: device id should be 'cpu', or 'cuda:N' (where N is an integer index for the GPU). Got: {device}"
)
def is_device_compatible(device):
'''
"""
Returns True/False, and prints any compatibility errors
'''
# static variable "history".
is_device_compatible.history = getattr(is_device_compatible, 'history', {})
"""
# static variable "history".
is_device_compatible.history = getattr(is_device_compatible, "history", {})
try:
validate_device_id(device, log_prefix='is_device_compatible')
validate_device_id(device, log_prefix="is_device_compatible")
except:
log.error(str(e))
return False
if device == 'cpu': return True
if device == "cpu":
return True
# Memory check
try:
_, mem_total = torch.cuda.mem_get_info(device)
mem_total /= float(10**9)
if mem_total < 3.0:
if is_device_compatible.history.get(device) == None:
log.warn(f'GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion')
is_device_compatible.history[device] = 1
log.warn(f"GPU {device} with less than 3 GB of VRAM is not compatible with Stable Diffusion")
is_device_compatible.history[device] = 1
return False
except RuntimeError as e:
log.error(str(e))
return False
return True
def get_processor_name():
try:
import platform, subprocess
if platform.system() == "Windows":
return platform.processor()
elif platform.system() == "Darwin":
os.environ['PATH'] = os.environ['PATH'] + os.pathsep + '/usr/sbin'
os.environ["PATH"] = os.environ["PATH"] + os.pathsep + "/usr/sbin"
command = "sysctl -n machdep.cpu.brand_string"
return subprocess.check_output(command).strip()
elif platform.system() == "Linux":

159
ui/easydiffusion/model_manager.py
View File

@ -8,29 +8,31 @@ from sdkit import Context
from sdkit.models import load_model, unload_model, get_model_info_from_db, scan_model
from sdkit.utils import hash_file_quick
KNOWN_MODEL_TYPES = ['stable-diffusion', 'vae', 'hypernetwork', 'gfpgan', 'realesrgan']
KNOWN_MODEL_TYPES = ["stable-diffusion", "vae", "hypernetwork", "gfpgan", "realesrgan"]
MODEL_EXTENSIONS = {
'stable-diffusion': ['.ckpt', '.safetensors'],
'vae': ['.vae.pt', '.ckpt', '.safetensors'],
'hypernetwork': ['.pt', '.safetensors'],
'gfpgan': ['.pth'],
'realesrgan': ['.pth'],
"stable-diffusion": [".ckpt", ".safetensors"],
"vae": [".vae.pt", ".ckpt", ".safetensors"],
"hypernetwork": [".pt", ".safetensors"],
"gfpgan": [".pth"],
"realesrgan": [".pth"],
}
DEFAULT_MODELS = {
'stable-diffusion': [ # needed to support the legacy installations
'custom-model', # only one custom model file was supported initially, creatively named 'custom-model'
'sd-v1-4', # Default fallback.
"stable-diffusion": [ # needed to support the legacy installations
"custom-model", # only one custom model file was supported initially, creatively named 'custom-model'
"sd-v1-4", # Default fallback.
],
'gfpgan': ['GFPGANv1.3'],
'realesrgan': ['RealESRGAN_x4plus'],
"gfpgan": ["GFPGANv1.3"],
"realesrgan": ["RealESRGAN_x4plus"],
}
MODELS_TO_LOAD_ON_START = ['stable-diffusion', 'vae', 'hypernetwork']
MODELS_TO_LOAD_ON_START = ["stable-diffusion", "vae", "hypernetwork"]
known_models = {}
def init():
make_model_folders()
getModels() # run this once, to cache the picklescan results
getModels() # run this once, to cache the picklescan results
def load_default_models(context: Context):
set_vram_optimizations(context)
@ -39,27 +41,28 @@ def load_default_models(context: Context):
for model_type in MODELS_TO_LOAD_ON_START:
context.model_paths[model_type] = resolve_model_to_use(model_type=model_type)
try:
load_model(context, model_type)
load_model(context, model_type)
except Exception as e:
log.error(f'[red]Error while loading {model_type} model: {context.model_paths[model_type]}[/red]')
log.error(f'[red]Error: {e}[/red]')
log.error(f'[red]Consider removing the model from the model folder.[red]')
log.error(f"[red]Error while loading {model_type} model: {context.model_paths[model_type]}[/red]")
log.error(f"[red]Error: {e}[/red]")
log.error(f"[red]Consider removing the model from the model folder.[red]")
def unload_all(context: Context):
for model_type in KNOWN_MODEL_TYPES:
unload_model(context, model_type)
def resolve_model_to_use(model_name:str=None, model_type:str=None):
def resolve_model_to_use(model_name: str = None, model_type: str = None):
model_extensions = MODEL_EXTENSIONS.get(model_type, [])
default_models = DEFAULT_MODELS.get(model_type, [])
config = app.getConfig()
model_dirs = [os.path.join(app.MODELS_DIR, model_type), app.SD_DIR]
if not model_name: # When None try user configured model.
if not model_name: # When None try user configured model.
# config = getConfig()
if 'model' in config and model_type in config['model']:
model_name = config['model'][model_type]
if "model" in config and model_type in config["model"]:
model_name = config["model"][model_type]
if model_name:
# Check models directory
@ -84,41 +87,54 @@ def resolve_model_to_use(model_name:str=None, model_type:str=None):
for model_extension in model_extensions:
if os.path.exists(default_model_path + model_extension):
if model_name is not None:
log.warn(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
log.warn(
f"Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}"
)
return default_model_path + model_extension
return None
def reload_models_if_necessary(context: Context, task_data: TaskData):
model_paths_in_req = {
'stable-diffusion': task_data.use_stable_diffusion_model,
'vae': task_data.use_vae_model,
'hypernetwork': task_data.use_hypernetwork_model,
'gfpgan': task_data.use_face_correction,
'realesrgan': task_data.use_upscale,
"stable-diffusion": task_data.use_stable_diffusion_model,
"vae": task_data.use_vae_model,
"hypernetwork": task_data.use_hypernetwork_model,
"gfpgan": task_data.use_face_correction,
"realesrgan": task_data.use_upscale,
}
models_to_reload = {
model_type: path
for model_type, path in model_paths_in_req.items()
if context.model_paths.get(model_type) != path
}
models_to_reload = {model_type: path for model_type, path in model_paths_in_req.items() if context.model_paths.get(model_type) != path}
if set_vram_optimizations(context): # reload SD
models_to_reload['stable-diffusion'] = model_paths_in_req['stable-diffusion']
if set_vram_optimizations(context): # reload SD
models_to_reload["stable-diffusion"] = model_paths_in_req["stable-diffusion"]
for model_type, model_path_in_req in models_to_reload.items():
context.model_paths[model_type] = model_path_in_req
action_fn = unload_model if context.model_paths[model_type] is None else load_model
action_fn(context, model_type, scan_model=False) # we've scanned them already
action_fn(context, model_type, scan_model=False) # we've scanned them already
def resolve_model_paths(task_data: TaskData):
task_data.use_stable_diffusion_model = resolve_model_to_use(task_data.use_stable_diffusion_model, model_type='stable-diffusion')
task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type='vae')
task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type='hypernetwork')
task_data.use_stable_diffusion_model = resolve_model_to_use(
task_data.use_stable_diffusion_model, model_type="stable-diffusion"
)
task_data.use_vae_model = resolve_model_to_use(task_data.use_vae_model, model_type="vae")
task_data.use_hypernetwork_model = resolve_model_to_use(task_data.use_hypernetwork_model, model_type="hypernetwork")
if task_data.use_face_correction:
task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, "gfpgan")
if task_data.use_upscale:
task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, "realesrgan")
if task_data.use_face_correction: task_data.use_face_correction = resolve_model_to_use(task_data.use_face_correction, 'gfpgan')
if task_data.use_upscale: task_data.use_upscale = resolve_model_to_use(task_data.use_upscale, 'realesrgan')
def set_vram_optimizations(context: Context):
config = app.getConfig()
vram_usage_level = config.get('vram_usage_level', 'balanced')
vram_usage_level = config.get("vram_usage_level", "balanced")
if vram_usage_level != context.vram_usage_level:
context.vram_usage_level = vram_usage_level
@ -126,42 +142,51 @@ def set_vram_optimizations(context: Context):
return False
def make_model_folders():
for model_type in KNOWN_MODEL_TYPES:
model_dir_path = os.path.join(app.MODELS_DIR, model_type)
os.makedirs(model_dir_path, exist_ok=True)
help_file_name = f'Place your {model_type} model files here.txt'
help_file_name = f"Place your {model_type} model files here.txt"
help_file_contents = f'Supported extensions: {" or ".join(MODEL_EXTENSIONS.get(model_type))}'
with open(os.path.join(model_dir_path, help_file_name), 'w', encoding='utf-8') as f:
with open(os.path.join(model_dir_path, help_file_name), "w", encoding="utf-8") as f:
f.write(help_file_contents)
def is_malicious_model(file_path):
try:
scan_result = scan_model(file_path)
if scan_result.issues_count > 0 or scan_result.infected_files > 0:
log.warn(":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
log.warn(
":warning: [bold red]Scan %s: %d scanned, %d issue, %d infected.[/bold red]"
% (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files)
)
return True
else:
log.debug("Scan %s: [green]%d scanned, %d issue, %d infected.[/green]" % (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files))
log.debug(
"Scan %s: [green]%d scanned, %d issue, %d infected.[/green]"
% (file_path, scan_result.scanned_files, scan_result.issues_count, scan_result.infected_files)
)
return False
except Exception as e:
log.error(f'error while scanning: {file_path}, error: {e}')
log.error(f"error while scanning: {file_path}, error: {e}")
return False
def getModels():
models = {
'active': {
'stable-diffusion': 'sd-v1-4',
'vae': '',
'hypernetwork': '',
"active": {
"stable-diffusion": "sd-v1-4",
"vae": "",
"hypernetwork": "",
},
'options': {
'stable-diffusion': ['sd-v1-4'],
'vae': [],
'hypernetwork': [],
"options": {
"stable-diffusion": ["sd-v1-4"],
"vae": [],
"hypernetwork": [],
},
}
@ -171,13 +196,16 @@ def getModels():
"Raised when picklescan reports a problem with a model"
pass
def scan_directory(directory, suffixes, directoriesFirst:bool=True):
def scan_directory(directory, suffixes, directoriesFirst: bool = True):
nonlocal models_scanned
tree = []
for entry in sorted(os.scandir(directory), key = lambda entry: (entry.is_file() == directoriesFirst, entry.name.lower())):
for entry in sorted(
os.scandir(directory), key=lambda entry: (entry.is_file() == directoriesFirst, entry.name.lower())
):
if entry.is_file():
matching_suffix = list(filter(lambda s: entry.name.endswith(s), suffixes))
if len(matching_suffix) == 0: continue
if len(matching_suffix) == 0:
continue
matching_suffix = matching_suffix[0]
mtime = entry.stat().st_mtime
@ -187,12 +215,12 @@ def getModels():
if is_malicious_model(entry.path):
raise MaliciousModelException(entry.path)
known_models[entry.path] = mtime
tree.append(entry.name[:-len(matching_suffix)])
tree.append(entry.name[: -len(matching_suffix)])
elif entry.is_dir():
scan=scan_directory(entry.path, suffixes, directoriesFirst=False)
scan = scan_directory(entry.path, suffixes, directoriesFirst=False)
if len(scan) != 0:
tree.append( (entry.name, scan ) )
tree.append((entry.name, scan))
return tree
def listModels(model_type):
@ -204,21 +232,22 @@ def getModels():
os.makedirs(models_dir)
try:
models['options'][model_type] = scan_directory(models_dir, model_extensions)
models["options"][model_type] = scan_directory(models_dir, model_extensions)
except MaliciousModelException as e:
models['scan-error'] = e
models["scan-error"] = e
# custom models
listModels(model_type='stable-diffusion')
listModels(model_type='vae')
listModels(model_type='hypernetwork')
listModels(model_type='gfpgan')
listModels(model_type="stable-diffusion")
listModels(model_type="vae")
listModels(model_type="hypernetwork")
listModels(model_type="gfpgan")
if models_scanned > 0: log.info(f'[green]Scanned {models_scanned} models. Nothing infected[/]')
if models_scanned > 0:
log.info(f"[green]Scanned {models_scanned} models. Nothing infected[/]")
# legacy
custom_weight_path = os.path.join(app.SD_DIR, 'custom-model.ckpt')
custom_weight_path = os.path.join(app.SD_DIR, "custom-model.ckpt")
if os.path.exists(custom_weight_path):
models['options']['stable-diffusion'].append('custom-model')
models["options"]["stable-diffusion"].append("custom-model")
return models

80
ui/easydiffusion/renderer.py
View File

@ -12,22 +12,26 @@ from sdkit.generate import generate_images
from sdkit.filter import apply_filters
from sdkit.utils import img_to_buffer, img_to_base64_str, latent_samples_to_images, gc
context = Context() # thread-local
'''
context = Context() # thread-local
"""
runtime data (bound locally to this thread), for e.g. device, references to loaded models, optimization flags etc
'''
"""
def init(device):
'''
"""
Initializes the fields that will be bound to this runtime's context, and sets the current torch device
'''
"""
context.stop_processing = False
context.temp_images = {}
context.partial_x_samples = None
device_manager.device_init(context, device)
def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
def make_images(
req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback
):
context.stop_processing = False
print_task_info(req, task_data)
@ -36,18 +40,24 @@ def make_images(req: GenerateImageRequest, task_data: TaskData, data_queue: queu
res = Response(req, task_data, images=construct_response(images, seeds, task_data, base_seed=req.seed))
res = res.json()
data_queue.put(json.dumps(res))
log.info('Task completed')
log.info("Task completed")
return res
def print_task_info(req: GenerateImageRequest, task_data: TaskData):
req_str = pprint.pformat(get_printable_request(req)).replace("[","\[")
task_str = pprint.pformat(task_data.dict()).replace("[","\[")
log.info(f'request: {req_str}')
log.info(f'task data: {task_str}')
def make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback):
images, user_stopped = generate_images_internal(req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress)
def print_task_info(req: GenerateImageRequest, task_data: TaskData):
req_str = pprint.pformat(get_printable_request(req)).replace("[", "\[")
task_str = pprint.pformat(task_data.dict()).replace("[", "\[")
log.info(f"request: {req_str}")
log.info(f"task data: {task_str}")
def make_images_internal(
req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback
):
images, user_stopped = generate_images_internal(
req, task_data, data_queue, task_temp_images, step_callback, task_data.stream_image_progress
)
filtered_images = filter_images(task_data, images, user_stopped)
if task_data.save_to_disk_path is not None:
@ -59,13 +69,22 @@ def make_images_internal(req: GenerateImageRequest, task_data: TaskData, data_qu
else:
return images + filtered_images, seeds + seeds
def generate_images_internal(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
def generate_images_internal(
req: GenerateImageRequest,
task_data: TaskData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
stream_image_progress: bool,
):
context.temp_images.clear()
callback = make_step_callback(req, task_data, data_queue, task_temp_images, step_callback, stream_image_progress)
try:
if req.init_image is not None: req.sampler_name = 'ddim'
if req.init_image is not None:
req.sampler_name = "ddim"
images = generate_images(context, callback=callback, **req.dict())
user_stopped = False
@ -75,31 +94,44 @@ def generate_images_internal(req: GenerateImageRequest, task_data: TaskData, dat
if context.partial_x_samples is not None:
images = latent_samples_to_images(context, context.partial_x_samples)
finally:
if hasattr(context, 'partial_x_samples') and context.partial_x_samples is not None:
if hasattr(context, "partial_x_samples") and context.partial_x_samples is not None:
del context.partial_x_samples
context.partial_x_samples = None
return images, user_stopped
def filter_images(task_data: TaskData, images: list, user_stopped):
if user_stopped or (task_data.use_face_correction is None and task_data.use_upscale is None):
return images
filters_to_apply = []
if task_data.use_face_correction and 'gfpgan' in task_data.use_face_correction.lower(): filters_to_apply.append('gfpgan')
if task_data.use_upscale and 'realesrgan' in task_data.use_upscale.lower(): filters_to_apply.append('realesrgan')
if task_data.use_face_correction and "gfpgan" in task_data.use_face_correction.lower():
filters_to_apply.append("gfpgan")
if task_data.use_upscale and "realesrgan" in task_data.use_upscale.lower():
filters_to_apply.append("realesrgan")
return apply_filters(context, filters_to_apply, images, scale=task_data.upscale_amount)
def construct_response(images: list, seeds: list, task_data: TaskData, base_seed: int):
return [
ResponseImage(
data=img_to_base64_str(img, task_data.output_format, task_data.output_quality),
seed=seed,
) for img, seed in zip(images, seeds)
)
for img, seed in zip(images, seeds)
]
def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queue: queue.Queue, task_temp_images: list, step_callback, stream_image_progress: bool):
def make_step_callback(
req: GenerateImageRequest,
task_data: TaskData,
data_queue: queue.Queue,
task_temp_images: list,
step_callback,
stream_image_progress: bool,
):
n_steps = req.num_inference_steps if req.init_image is None else int(req.num_inference_steps * req.prompt_strength)
last_callback_time = -1
@ -107,11 +139,11 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
partial_images = []
images = latent_samples_to_images(context, x_samples)
for i, img in enumerate(images):
buf = img_to_buffer(img, output_format='JPEG')
buf = img_to_buffer(img, output_format="JPEG")
context.temp_images[f"{task_data.request_id}/{i}"] = buf
task_temp_images[i] = buf
partial_images.append({'path': f"/image/tmp/{task_data.request_id}/{i}"})
partial_images.append({"path": f"/image/tmp/{task_data.request_id}/{i}"})
del images
return partial_images
@ -125,7 +157,7 @@ def make_step_callback(req: GenerateImageRequest, task_data: TaskData, data_queu
progress = {"step": i, "step_time": step_time, "total_steps": n_steps}
if stream_image_progress and i % 5 == 0:
progress['output'] = update_temp_img(x_samples, task_temp_images)
progress["output"] = update_temp_img(x_samples, task_temp_images)
data_queue.put(json.dumps(progress))

235
ui/easydiffusion/server.py
View File

@ -16,21 +16,25 @@ from easydiffusion import app, model_manager, task_manager
from easydiffusion.types import TaskData, GenerateImageRequest, MergeRequest
from easydiffusion.utils import log
log.info(f'started in {app.SD_DIR}')
log.info(f'started at {datetime.datetime.now():%x %X}')
log.info(f"started in {app.SD_DIR}")
log.info(f"started at {datetime.datetime.now():%x %X}")
server_api = FastAPI()
NOCACHE_HEADERS={"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"}
NOCACHE_HEADERS = {"Cache-Control": "no-cache, no-store, must-revalidate", "Pragma": "no-cache", "Expires": "0"}
class NoCacheStaticFiles(StaticFiles):
def is_not_modified(self, response_headers, request_headers) -> bool:
if 'content-type' in response_headers and ('javascript' in response_headers['content-type'] or 'css' in response_headers['content-type']):
if "content-type" in response_headers and (
"javascript" in response_headers["content-type"] or "css" in response_headers["content-type"]
):
response_headers.update(NOCACHE_HEADERS)
return False
return super().is_not_modified(response_headers, request_headers)
class SetAppConfigRequest(BaseModel):
update_branch: str = None
render_devices: Union[List[str], List[int], str, int] = None
@ -39,130 +43,142 @@ class SetAppConfigRequest(BaseModel):
listen_to_network: bool = None
listen_port: int = None
def init():
server_api.mount('/media', NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, 'media')), name="media")
server_api.mount("/media", NoCacheStaticFiles(directory=os.path.join(app.SD_UI_DIR, "media")), name="media")
for plugins_dir, dir_prefix in app.UI_PLUGINS_SOURCES:
server_api.mount(f'/plugins/{dir_prefix}', NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}")
server_api.mount(
f"/plugins/{dir_prefix}", NoCacheStaticFiles(directory=plugins_dir), name=f"plugins-{dir_prefix}"
)
@server_api.post('/app_config')
async def set_app_config(req : SetAppConfigRequest):
@server_api.post("/app_config")
async def set_app_config(req: SetAppConfigRequest):
return set_app_config_internal(req)
@server_api.get('/get/{key:path}')
def read_web_data(key:str=None):
@server_api.get("/get/{key:path}")
def read_web_data(key: str = None):
return read_web_data_internal(key)
@server_api.get('/ping') # Get server and optionally session status.
def ping(session_id:str=None):
@server_api.get("/ping") # Get server and optionally session status.
def ping(session_id: str = None):
return ping_internal(session_id)
@server_api.post('/render')
@server_api.post("/render")
def render(req: dict):
return render_internal(req)
@server_api.post('/model/merge')
@server_api.post("/model/merge")
def model_merge(req: dict):
print(req)
return model_merge_internal(req)
@server_api.get('/image/stream/{task_id:int}')
def stream(task_id:int):
@server_api.get("/image/stream/{task_id:int}")
def stream(task_id: int):
return stream_internal(task_id)
@server_api.get('/image/stop')
@server_api.get("/image/stop")
def stop(task: int):
return stop_internal(task)
@server_api.get('/image/tmp/{task_id:int}/{img_id:int}')
@server_api.get("/image/tmp/{task_id:int}/{img_id:int}")
def get_image(task_id: int, img_id: int):
return get_image_internal(task_id, img_id)
@server_api.get('/')
@server_api.get("/")
def read_root():
return FileResponse(os.path.join(app.SD_UI_DIR, 'index.html'), headers=NOCACHE_HEADERS)
return FileResponse(os.path.join(app.SD_UI_DIR, "index.html"), headers=NOCACHE_HEADERS)
@server_api.on_event("shutdown")
def shutdown_event(): # Signal render thread to close on shutdown
task_manager.current_state_error = SystemExit('Application shutting down.')
def shutdown_event(): # Signal render thread to close on shutdown
task_manager.current_state_error = SystemExit("Application shutting down.")
# API implementations
def set_app_config_internal(req : SetAppConfigRequest):
def set_app_config_internal(req: SetAppConfigRequest):
config = app.getConfig()
if req.update_branch is not None:
config['update_branch'] = req.update_branch
config["update_branch"] = req.update_branch
if req.render_devices is not None:
update_render_devices_in_config(config, req.render_devices)
if req.ui_open_browser_on_start is not None:
if 'ui' not in config:
config['ui'] = {}
config['ui']['open_browser_on_start'] = req.ui_open_browser_on_start
if "ui" not in config:
config["ui"] = {}
config["ui"]["open_browser_on_start"] = req.ui_open_browser_on_start
if req.listen_to_network is not None:
if 'net' not in config:
config['net'] = {}
config['net']['listen_to_network'] = bool(req.listen_to_network)
if "net" not in config:
config["net"] = {}
config["net"]["listen_to_network"] = bool(req.listen_to_network)
if req.listen_port is not None:
if 'net' not in config:
config['net'] = {}
config['net']['listen_port'] = int(req.listen_port)
if "net" not in config:
config["net"] = {}
config["net"]["listen_port"] = int(req.listen_port)
try:
app.setConfig(config)
if req.render_devices:
app.update_render_threads()
return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS)
return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
except Exception as e:
log.error(traceback.format_exc())
raise HTTPException(status_code=500, detail=str(e))
def update_render_devices_in_config(config, render_devices):
if render_devices not in ('cpu', 'auto') and not render_devices.startswith('cuda:'):
raise HTTPException(status_code=400, detail=f'Invalid render device requested: {render_devices}')
if render_devices not in ("cpu", "auto") and not render_devices.startswith("cuda:"):
raise HTTPException(status_code=400, detail=f"Invalid render device requested: {render_devices}")
if render_devices.startswith('cuda:'):
render_devices = render_devices.split(',')
if render_devices.startswith("cuda:"):
render_devices = render_devices.split(",")
config['render_devices'] = render_devices
config["render_devices"] = render_devices
def read_web_data_internal(key:str=None):
if not key: # /get without parameters, stable-diffusion easter egg.
raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot
elif key == 'app_config':
def read_web_data_internal(key: str = None):
if not key: # /get without parameters, stable-diffusion easter egg.
raise HTTPException(status_code=418, detail="StableDiffusion is drawing a teapot!") # HTTP418 I'm a teapot
elif key == "app_config":
return JSONResponse(app.getConfig(), headers=NOCACHE_HEADERS)
elif key == 'system_info':
elif key == "system_info":
config = app.getConfig()
output_dir = config.get('force_save_path', os.path.join(os.path.expanduser("~"), app.OUTPUT_DIRNAME))
output_dir = config.get("force_save_path", os.path.join(os.path.expanduser("~"), app.OUTPUT_DIRNAME))
system_info = {
'devices': task_manager.get_devices(),
'hosts': app.getIPConfig(),
'default_output_dir': output_dir,
'enforce_output_dir': ('force_save_path' in config),
"devices": task_manager.get_devices(),
"hosts": app.getIPConfig(),
"default_output_dir": output_dir,
"enforce_output_dir": ("force_save_path" in config),
}
system_info['devices']['config'] = config.get('render_devices', "auto")
system_info["devices"]["config"] = config.get("render_devices", "auto")
return JSONResponse(system_info, headers=NOCACHE_HEADERS)
elif key == 'models':
elif key == "models":
return JSONResponse(model_manager.getModels(), headers=NOCACHE_HEADERS)
elif key == 'modifiers': return FileResponse(os.path.join(app.SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS)
elif key == 'ui_plugins': return JSONResponse(app.getUIPlugins(), headers=NOCACHE_HEADERS)
elif key == "modifiers":
return FileResponse(os.path.join(app.SD_UI_DIR, "modifiers.json"), headers=NOCACHE_HEADERS)
elif key == "ui_plugins":
return JSONResponse(app.getUIPlugins(), headers=NOCACHE_HEADERS)
else:
raise HTTPException(status_code=404, detail=f'Request for unknown {key}') # HTTP404 Not Found
raise HTTPException(status_code=404, detail=f"Request for unknown {key}") # HTTP404 Not Found
def ping_internal(session_id:str=None):
if task_manager.is_alive() <= 0: # Check that render threads are alive.
if task_manager.current_state_error: raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
raise HTTPException(status_code=500, detail='Render thread is dead.')
if task_manager.current_state_error and not isinstance(task_manager.current_state_error, StopAsyncIteration): raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
def ping_internal(session_id: str = None):
if task_manager.is_alive() <= 0: # Check that render threads are alive.
if task_manager.current_state_error:
raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
raise HTTPException(status_code=500, detail="Render thread is dead.")
if task_manager.current_state_error and not isinstance(task_manager.current_state_error, StopAsyncIteration):
raise HTTPException(status_code=500, detail=str(task_manager.current_state_error))
# Alive
response = {'status': str(task_manager.current_state)}
response = {"status": str(task_manager.current_state)}
if session_id:
session = task_manager.get_cached_session(session_id, update_ttl=True)
response['tasks'] = {id(t): t.status for t in session.tasks}
response['devices'] = task_manager.get_devices()
response["tasks"] = {id(t): t.status for t in session.tasks}
response["devices"] = task_manager.get_devices()
return JSONResponse(response, headers=NOCACHE_HEADERS)
def render_internal(req: dict):
try:
# separate out the request data into rendering and task-specific data
@ -171,80 +187,99 @@ def render_internal(req: dict):
# Overwrite user specified save path
config = app.getConfig()
if 'force_save_path' in config:
task_data.save_to_disk_path = config['force_save_path']
if "force_save_path" in config:
task_data.save_to_disk_path = config["force_save_path"]
render_req.init_image_mask = req.get('mask') # hack: will rename this in the HTTP API in a future revision
render_req.init_image_mask = req.get("mask") # hack: will rename this in the HTTP API in a future revision
app.save_to_config(task_data.use_stable_diffusion_model, task_data.use_vae_model, task_data.use_hypernetwork_model, task_data.vram_usage_level)
app.save_to_config(
task_data.use_stable_diffusion_model,
task_data.use_vae_model,
task_data.use_hypernetwork_model,
task_data.vram_usage_level,
)
# enqueue the task
new_task = task_manager.render(render_req, task_data)
response = {
'status': str(task_manager.current_state),
'queue': len(task_manager.tasks_queue),
'stream': f'/image/stream/{id(new_task)}',
'task': id(new_task)
"status": str(task_manager.current_state),
"queue": len(task_manager.tasks_queue),
"stream": f"/image/stream/{id(new_task)}",
"task": id(new_task),
}
return JSONResponse(response, headers=NOCACHE_HEADERS)
except ChildProcessError as e: # Render thread is dead
raise HTTPException(status_code=500, detail=f'Rendering thread has died.') # HTTP500 Internal Server Error
except ConnectionRefusedError as e: # Unstarted task pending limit reached, deny queueing too many.
raise HTTPException(status_code=503, detail=str(e)) # HTTP503 Service Unavailable
except ChildProcessError as e: # Render thread is dead
raise HTTPException(status_code=500, detail=f"Rendering thread has died.") # HTTP500 Internal Server Error
except ConnectionRefusedError as e: # Unstarted task pending limit reached, deny queueing too many.
raise HTTPException(status_code=503, detail=str(e)) # HTTP503 Service Unavailable
except Exception as e:
log.error(traceback.format_exc())
raise HTTPException(status_code=500, detail=str(e))
def model_merge_internal(req: dict):
try:
from sdkit.train import merge_models
from easydiffusion.utils.save_utils import filename_regex
mergeReq: MergeRequest = MergeRequest.parse_obj(req)
merge_models(model_manager.resolve_model_to_use(mergeReq.model0,'stable-diffusion'),
model_manager.resolve_model_to_use(mergeReq.model1,'stable-diffusion'),
mergeReq.ratio,
os.path.join(app.MODELS_DIR, 'stable-diffusion', filename_regex.sub('_', mergeReq.out_path)),
mergeReq.use_fp16
merge_models(
model_manager.resolve_model_to_use(mergeReq.model0, "stable-diffusion"),
model_manager.resolve_model_to_use(mergeReq.model1, "stable-diffusion"),
mergeReq.ratio,
os.path.join(app.MODELS_DIR, "stable-diffusion", filename_regex.sub("_", mergeReq.out_path)),
mergeReq.use_fp16,
)
return JSONResponse({'status':'OK'}, headers=NOCACHE_HEADERS)
return JSONResponse({"status": "OK"}, headers=NOCACHE_HEADERS)
except Exception as e:
log.error(traceback.format_exc())
raise HTTPException(status_code=500, detail=str(e))
def stream_internal(task_id:int):
#TODO Move to WebSockets ??
def stream_internal(task_id: int):
# TODO Move to WebSockets ??
task = task_manager.get_cached_task(task_id, update_ttl=True)
if not task: raise HTTPException(status_code=404, detail=f'Request {task_id} not found.') # HTTP404 NotFound
#if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict
if not task:
raise HTTPException(status_code=404, detail=f"Request {task_id} not found.") # HTTP404 NotFound
# if (id(task) != task_id): raise HTTPException(status_code=409, detail=f'Wrong task id received. Expected:{id(task)}, Received:{task_id}') # HTTP409 Conflict
if task.buffer_queue.empty() and not task.lock.locked():
if task.response:
#log.info(f'Session {session_id} sending cached response')
# log.info(f'Session {session_id} sending cached response')
return JSONResponse(task.response, headers=NOCACHE_HEADERS)
raise HTTPException(status_code=425, detail='Too Early, task not started yet.') # HTTP425 Too Early
#log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
return StreamingResponse(task.read_buffer_generator(), media_type='application/json')
raise HTTPException(status_code=425, detail="Too Early, task not started yet.") # HTTP425 Too Early
# log.info(f'Session {session_id} opened live render stream {id(task.buffer_queue)}')
return StreamingResponse(task.read_buffer_generator(), media_type="application/json")
def stop_internal(task: int):
if not task:
if task_manager.current_state == task_manager.ServerStates.Online or task_manager.current_state == task_manager.ServerStates.Unavailable:
raise HTTPException(status_code=409, detail='Not currently running any tasks.') # HTTP409 Conflict
task_manager.current_state_error = StopAsyncIteration('')
return {'OK'}
if (
task_manager.current_state == task_manager.ServerStates.Online
or task_manager.current_state == task_manager.ServerStates.Unavailable
):
raise HTTPException(status_code=409, detail="Not currently running any tasks.") # HTTP409 Conflict
task_manager.current_state_error = StopAsyncIteration("")
return {"OK"}
task_id = task
task = task_manager.get_cached_task(task_id, update_ttl=False)
if not task: raise HTTPException(status_code=404, detail=f'Task {task_id} was not found.') # HTTP404 Not Found
if isinstance(task.error, StopAsyncIteration): raise HTTPException(status_code=409, detail=f'Task {task_id} is already stopped.') # HTTP409 Conflict
task.error = StopAsyncIteration(f'Task {task_id} stop requested.')
return {'OK'}
if not task:
raise HTTPException(status_code=404, detail=f"Task {task_id} was not found.") # HTTP404 Not Found
if isinstance(task.error, StopAsyncIteration):
raise HTTPException(status_code=409, detail=f"Task {task_id} is already stopped.") # HTTP409 Conflict
task.error = StopAsyncIteration(f"Task {task_id} stop requested.")
return {"OK"}
def get_image_internal(task_id: int, img_id: int):
task = task_manager.get_cached_task(task_id, update_ttl=True)
if not task: raise HTTPException(status_code=410, detail=f'Task {task_id} could not be found.') # HTTP404 NotFound
if not task.temp_images[img_id]: raise HTTPException(status_code=425, detail='Too Early, task data is not available yet.') # HTTP425 Too Early
if not task:
raise HTTPException(status_code=410, detail=f"Task {task_id} could not be found.") # HTTP404 NotFound
if not task.temp_images[img_id]:
raise HTTPException(status_code=425, detail="Too Early, task data is not available yet.") # HTTP425 Too Early
try:
img_data = task.temp_images[img_id]
img_data.seek(0)
return StreamingResponse(img_data, media_type='image/jpeg')
return StreamingResponse(img_data, media_type="image/jpeg")
except KeyError as e:
raise HTTPException(status_code=500, detail=str(e))

296
ui/easydiffusion/task_manager.py
View File

@ -7,7 +7,7 @@ Notes:
import json
import traceback
TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
TASK_TTL = 15 * 60 # seconds, Discard last session's task timeout
import torch
import queue, threading, time, weakref
@ -19,71 +19,98 @@ from easydiffusion.utils import log
from sdkit.utils import gc
THREAD_NAME_PREFIX = ''
ERR_LOCK_FAILED = ' failed to acquire lock within timeout.'
LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
THREAD_NAME_PREFIX = ""
ERR_LOCK_FAILED = " failed to acquire lock within timeout."
LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
class SymbolClass(type): # Print nicely formatted Symbol names.
def __repr__(self):
return self.__qualname__
def __str__(self):
return self.__name__
class Symbol(metaclass=SymbolClass):
pass
class SymbolClass(type): # Print nicely formatted Symbol names.
def __repr__(self): return self.__qualname__
def __str__(self): return self.__name__
class Symbol(metaclass=SymbolClass): pass
class ServerStates:
class Init(Symbol): pass
class LoadingModel(Symbol): pass
class Online(Symbol): pass
class Rendering(Symbol): pass
class Unavailable(Symbol): pass
class Init(Symbol):
pass
class RenderTask(): # Task with output queue and completion lock.
class LoadingModel(Symbol):
pass
class Online(Symbol):
pass
class Rendering(Symbol):
pass
class Unavailable(Symbol):
pass
class RenderTask: # Task with output queue and completion lock.
def __init__(self, req: GenerateImageRequest, task_data: TaskData):
task_data.request_id = id(self)
self.render_request: GenerateImageRequest = req # Initial Request
self.task_data: TaskData = task_data
self.response: Any = None # Copy of the last reponse
self.render_device = None # Select the task affinity. (Not used to change active devices).
self.temp_images:list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
self.response: Any = None # Copy of the last reponse
self.render_device = None # Select the task affinity. (Not used to change active devices).
self.temp_images: list = [None] * req.num_outputs * (1 if task_data.show_only_filtered_image else 2)
self.error: Exception = None
self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
self.buffer_queue: queue.Queue = queue.Queue() # Queue of JSON string segments
self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
self.buffer_queue: queue.Queue = queue.Queue() # Queue of JSON string segments
async def read_buffer_generator(self):
try:
while not self.buffer_queue.empty():
res = self.buffer_queue.get(block=False)
self.buffer_queue.task_done()
yield res
except queue.Empty as e: yield
except queue.Empty as e:
yield
@property
def status(self):
if self.lock.locked():
return 'running'
return "running"
if isinstance(self.error, StopAsyncIteration):
return 'stopped'
return "stopped"
if self.error:
return 'error'
return "error"
if not self.buffer_queue.empty():
return 'buffer'
return "buffer"
if self.response:
return 'completed'
return 'pending'
return "completed"
return "pending"
@property
def is_pending(self):
return bool(not self.response and not self.error)
# Temporary cache to allow to query tasks results for a short time after they are completed.
class DataCache():
class DataCache:
def __init__(self):
self._base = dict()
self._lock: threading.Lock = threading.Lock()
def _get_ttl_time(self, ttl: int) -> int:
return int(time.time()) + ttl
def _is_expired(self, timestamp: int) -> bool:
return int(time.time()) >= timestamp
def clean(self) -> None:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.clean' + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.clean" + ERR_LOCK_FAILED)
try:
# Create a list of expired keys to delete
to_delete = []
@ -95,20 +122,26 @@ class DataCache():
for key in to_delete:
(_, val) = self._base[key]
if isinstance(val, RenderTask):
log.debug(f'RenderTask {key} expired. Data removed.')
log.debug(f"RenderTask {key} expired. Data removed.")
elif isinstance(val, SessionState):
log.debug(f'Session {key} expired. Data removed.')
log.debug(f"Session {key} expired. Data removed.")
else:
log.debug(f'Key {key} expired. Data removed.')
log.debug(f"Key {key} expired. Data removed.")
del self._base[key]
finally:
self._lock.release()
def clear(self) -> None:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.clear' + ERR_LOCK_FAILED)
try: self._base.clear()
finally: self._lock.release()
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.clear" + ERR_LOCK_FAILED)
try:
self._base.clear()
finally:
self._lock.release()
def delete(self, key: Hashable) -> bool:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.delete' + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.delete" + ERR_LOCK_FAILED)
try:
if key not in self._base:
return False
@ -116,8 +149,10 @@ class DataCache():
return True
finally:
self._lock.release()
def keep(self, key: Hashable, ttl: int) -> bool:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.keep' + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.keep" + ERR_LOCK_FAILED)
try:
if key in self._base:
_, value = self._base.get(key)
@ -126,12 +161,12 @@ class DataCache():
return False
finally:
self._lock.release()
def put(self, key: Hashable, value: Any, ttl: int) -> bool:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.put' + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.put" + ERR_LOCK_FAILED)
try:
self._base[key] = (
self._get_ttl_time(ttl), value
)
self._base[key] = (self._get_ttl_time(ttl), value)
except Exception as e:
log.error(traceback.format_exc())
return False
@ -139,35 +174,41 @@ class DataCache():
return True
finally:
self._lock.release()
def tryGet(self, key: Hashable) -> Any:
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('DataCache.tryGet' + ERR_LOCK_FAILED)
if not self._lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("DataCache.tryGet" + ERR_LOCK_FAILED)
try:
ttl, value = self._base.get(key, (None, None))
if ttl is not None and self._is_expired(ttl):
log.debug(f'Session {key} expired. Discarding data.')
log.debug(f"Session {key} expired. Discarding data.")
del self._base[key]
return None
return value
finally:
self._lock.release()
manager_lock = threading.RLock()
render_threads = []
current_state = ServerStates.Init
current_state_error:Exception = None
current_state_error: Exception = None
tasks_queue = []
session_cache = DataCache()
task_cache = DataCache()
weak_thread_data = weakref.WeakKeyDictionary()
idle_event: threading.Event = threading.Event()
class SessionState():
class SessionState:
def __init__(self, id: str):
self._id = id
self._tasks_ids = []
@property
def id(self):
return self._id
@property
def tasks(self):
tasks = []
@ -176,6 +217,7 @@ class SessionState():
if task:
tasks.append(task)
return tasks
def put(self, task, ttl=TASK_TTL):
task_id = id(task)
self._tasks_ids.append(task_id)
@ -185,10 +227,12 @@ class SessionState():
self._tasks_ids.pop(0)
return True
def thread_get_next_task():
from easydiffusion import renderer
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
log.warn(f'Render thread on device: {renderer.context.device} failed to acquire manager lock.')
log.warn(f"Render thread on device: {renderer.context.device} failed to acquire manager lock.")
return None
if len(tasks_queue) <= 0:
manager_lock.release()
@ -202,10 +246,10 @@ def thread_get_next_task():
continue # requested device alive, skip current one.
else:
# Requested device is not active, return error to UI.
queued_task.error = Exception(queued_task.render_device + ' is not currently active.')
queued_task.error = Exception(queued_task.render_device + " is not currently active.")
task = queued_task
break
if not queued_task.render_device and renderer.context.device == 'cpu' and is_alive() > 1:
if not queued_task.render_device and renderer.context.device == "cpu" and is_alive() > 1:
# not asking for any specific devices, cpu want to grab task but other render devices are alive.
continue # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
task = queued_task
@ -216,17 +260,19 @@ def thread_get_next_task():
finally:
manager_lock.release()
def thread_render(device):
global current_state, current_state_error
from easydiffusion import renderer, model_manager
try:
renderer.init(device)
weak_thread_data[threading.current_thread()] = {
'device': renderer.context.device,
'device_name': renderer.context.device_name,
'alive': True
"device": renderer.context.device,
"device_name": renderer.context.device_name,
"alive": True,
}
current_state = ServerStates.LoadingModel
@ -235,17 +281,14 @@ def thread_render(device):
current_state = ServerStates.Online
except Exception as e:
log.error(traceback.format_exc())
weak_thread_data[threading.current_thread()] = {
'error': e,
'alive': False
}
weak_thread_data[threading.current_thread()] = {"error": e, "alive": False}
return
while True:
session_cache.clean()
task_cache.clean()
if not weak_thread_data[threading.current_thread()]['alive']:
log.info(f'Shutting down thread for device {renderer.context.device}')
if not weak_thread_data[threading.current_thread()]["alive"]:
log.info(f"Shutting down thread for device {renderer.context.device}")
model_manager.unload_all(renderer.context)
return
if isinstance(current_state_error, SystemExit):
@ -258,39 +301,47 @@ def thread_render(device):
continue
if task.error is not None:
log.error(task.error)
task.response = {"status": 'failed', "detail": str(task.error)}
task.response = {"status": "failed", "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
continue
if current_state_error:
task.error = current_state_error
task.response = {"status": 'failed', "detail": str(task.error)}
task.response = {"status": "failed", "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
continue
log.info(f'Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}')
if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
log.info(f"Session {task.task_data.session_id} starting task {id(task)} on {renderer.context.device_name}")
if not task.lock.acquire(blocking=False):
raise Exception("Got locked task from queue.")
try:
def step_callback():
global current_state_error
if isinstance(current_state_error, SystemExit) or isinstance(current_state_error, StopAsyncIteration) or isinstance(task.error, StopAsyncIteration):
if (
isinstance(current_state_error, SystemExit)
or isinstance(current_state_error, StopAsyncIteration)
or isinstance(task.error, StopAsyncIteration)
):
renderer.context.stop_processing = True
if isinstance(current_state_error, StopAsyncIteration):
task.error = current_state_error
current_state_error = None
log.info(f'Session {task.task_data.session_id} sent cancel signal for task {id(task)}')
log.info(f"Session {task.task_data.session_id} sent cancel signal for task {id(task)}")
current_state = ServerStates.LoadingModel
model_manager.resolve_model_paths(task.task_data)
model_manager.reload_models_if_necessary(renderer.context, task.task_data)
current_state = ServerStates.Rendering
task.response = renderer.make_images(task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback)
task.response = renderer.make_images(
task.render_request, task.task_data, task.buffer_queue, task.temp_images, step_callback
)
# Before looping back to the generator, mark cache as still alive.
task_cache.keep(id(task), TASK_TTL)
session_cache.keep(task.task_data.session_id, TASK_TTL)
except Exception as e:
task.error = str(e)
task.response = {"status": 'failed', "detail": str(task.error)}
task.response = {"status": "failed", "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response))
log.error(traceback.format_exc())
finally:
@ -299,21 +350,25 @@ def thread_render(device):
task_cache.keep(id(task), TASK_TTL)
session_cache.keep(task.task_data.session_id, TASK_TTL)
if isinstance(task.error, StopAsyncIteration):
log.info(f'Session {task.task_data.session_id} task {id(task)} cancelled!')
log.info(f"Session {task.task_data.session_id} task {id(task)} cancelled!")
elif task.error is not None:
log.info(f'Session {task.task_data.session_id} task {id(task)} failed!')
log.info(f"Session {task.task_data.session_id} task {id(task)} failed!")
else:
log.info(f'Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}.')
log.info(
f"Session {task.task_data.session_id} task {id(task)} completed by {renderer.context.device_name}."
)
current_state = ServerStates.Online
def get_cached_task(task_id:str, update_ttl:bool=False):
def get_cached_task(task_id: str, update_ttl: bool = False):
# By calling keep before tryGet, wont discard if was expired.
if update_ttl and not task_cache.keep(task_id, TASK_TTL):
# Failed to keep task, already gone.
return None
return task_cache.tryGet(task_id)
def get_cached_session(session_id:str, update_ttl:bool=False):
def get_cached_session(session_id: str, update_ttl: bool = False):
if update_ttl:
session_cache.keep(session_id, TASK_TTL)
session = session_cache.tryGet(session_id)
@ -322,64 +377,68 @@ def get_cached_session(session_id:str, update_ttl:bool=False):
session_cache.put(session_id, session, TASK_TTL)
return session
def get_devices():
devices = {
'all': {},
'active': {},
"all": {},
"active": {},
}
def get_device_info(device):
if device == 'cpu':
return {'name': device_manager.get_processor_name()}
if device == "cpu":
return {"name": device_manager.get_processor_name()}
mem_free, mem_total = torch.cuda.mem_get_info(device)
mem_free /= float(10**9)
mem_total /= float(10**9)
return {
'name': torch.cuda.get_device_name(device),
'mem_free': mem_free,
'mem_total': mem_total,
'max_vram_usage_level': device_manager.get_max_vram_usage_level(device),
"name": torch.cuda.get_device_name(device),
"mem_free": mem_free,
"mem_total": mem_total,
"max_vram_usage_level": device_manager.get_max_vram_usage_level(device),
}
# list the compatible devices
gpu_count = torch.cuda.device_count()
for device in range(gpu_count):
device = f'cuda:{device}'
device = f"cuda:{device}"
if not device_manager.is_device_compatible(device):
continue
devices['all'].update({device: get_device_info(device)})
devices["all"].update({device: get_device_info(device)})
devices['all'].update({'cpu': get_device_info('cpu')})
devices["all"].update({"cpu": get_device_info("cpu")})
# list the activated devices
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('get_devices' + ERR_LOCK_FAILED)
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("get_devices" + ERR_LOCK_FAILED)
try:
for rthread in render_threads:
if not rthread.is_alive():
continue
weak_data = weak_thread_data.get(rthread)
if not weak_data or not 'device' in weak_data or not 'device_name' in weak_data:
if not weak_data or not "device" in weak_data or not "device_name" in weak_data:
continue
device = weak_data['device']
devices['active'].update({device: get_device_info(device)})
device = weak_data["device"]
devices["active"].update({device: get_device_info(device)})
finally:
manager_lock.release()
return devices
def is_alive(device=None):
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('is_alive' + ERR_LOCK_FAILED)
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("is_alive" + ERR_LOCK_FAILED)
nbr_alive = 0
try:
for rthread in render_threads:
if device is not None:
weak_data = weak_thread_data.get(rthread)
if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
if weak_data is None or not "device" in weak_data or weak_data["device"] is None:
continue
thread_device = weak_data['device']
thread_device = weak_data["device"]
if thread_device != device:
continue
if rthread.is_alive():
@ -388,11 +447,13 @@ def is_alive(device=None):
finally:
manager_lock.release()
def start_render_thread(device):
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('start_render_thread' + ERR_LOCK_FAILED)
log.info(f'Start new Rendering Thread on device: {device}')
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("start_render_thread" + ERR_LOCK_FAILED)
log.info(f"Start new Rendering Thread on device: {device}")
try:
rthread = threading.Thread(target=thread_render, kwargs={'device': device})
rthread = threading.Thread(target=thread_render, kwargs={"device": device})
rthread.daemon = True
rthread.name = THREAD_NAME_PREFIX + device
rthread.start()
@ -400,8 +461,8 @@ def start_render_thread(device):
finally:
manager_lock.release()
timeout = DEVICE_START_TIMEOUT
while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
if rthread in weak_thread_data and 'error' in weak_thread_data[rthread]:
while not rthread.is_alive() or not rthread in weak_thread_data or not "device" in weak_thread_data[rthread]:
if rthread in weak_thread_data and "error" in weak_thread_data[rthread]:
log.error(f"{rthread}, {device}, error: {weak_thread_data[rthread]['error']}")
return False
if timeout <= 0:
@ -410,25 +471,27 @@ def start_render_thread(device):
time.sleep(1)
return True
def stop_render_thread(device):
try:
device_manager.validate_device_id(device, log_prefix='stop_render_thread')
device_manager.validate_device_id(device, log_prefix="stop_render_thread")
except:
log.error(traceback.format_exc())
return False
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('stop_render_thread' + ERR_LOCK_FAILED)
log.info(f'Stopping Rendering Thread on device: {device}')
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT):
raise Exception("stop_render_thread" + ERR_LOCK_FAILED)
log.info(f"Stopping Rendering Thread on device: {device}")
try:
thread_to_remove = None
for rthread in render_threads:
weak_data = weak_thread_data.get(rthread)
if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
if weak_data is None or not "device" in weak_data or weak_data["device"] is None:
continue
thread_device = weak_data['device']
thread_device = weak_data["device"]
if thread_device == device:
weak_data['alive'] = False
weak_data["alive"] = False
thread_to_remove = rthread
break
if thread_to_remove is not None:
@ -439,44 +502,51 @@ def stop_render_thread(device):
return False
def update_render_threads(render_devices, active_devices):
devices_to_start, devices_to_stop = device_manager.get_device_delta(render_devices, active_devices)
log.debug(f'devices_to_start: {devices_to_start}')
log.debug(f'devices_to_stop: {devices_to_stop}')
log.debug(f"devices_to_start: {devices_to_start}")
log.debug(f"devices_to_stop: {devices_to_stop}")
for device in devices_to_stop:
if is_alive(device) <= 0:
log.debug(f'{device} is not alive')
log.debug(f"{device} is not alive")
continue
if not stop_render_thread(device):
log.warn(f'{device} could not stop render thread')
log.warn(f"{device} could not stop render thread")
for device in devices_to_start:
if is_alive(device) >= 1:
log.debug(f'{device} already registered.')
log.debug(f"{device} already registered.")
continue
if not start_render_thread(device):
log.warn(f'{device} failed to start.')
log.warn(f"{device} failed to start.")
if is_alive() <= 0: # No running devices, probably invalid user config.
raise EnvironmentError('ERROR: No active render devices! Please verify the "render_devices" value in config.json')
if is_alive() <= 0: # No running devices, probably invalid user config.
raise EnvironmentError(
'ERROR: No active render devices! Please verify the "render_devices" value in config.json'
)
log.debug(f"active devices: {get_devices()['active']}")
def shutdown_event(): # Signal render thread to close on shutdown
def shutdown_event(): # Signal render thread to close on shutdown
global current_state_error
current_state_error = SystemExit('Application shutting down.')
current_state_error = SystemExit("Application shutting down.")
def render(render_req: GenerateImageRequest, task_data: TaskData):
current_thread_count = is_alive()
if current_thread_count <= 0: # Render thread is dead
raise ChildProcessError('Rendering thread has died.')
raise ChildProcessError("Rendering thread has died.")
# Alive, check if task in cache
session = get_cached_session(task_data.session_id, update_ttl=True)
pending_tasks = list(filter(lambda t: t.is_pending, session.tasks))
if current_thread_count < len(pending_tasks):
raise ConnectionRefusedError(f'Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}.')
raise ConnectionRefusedError(
f"Session {task_data.session_id} already has {len(pending_tasks)} pending tasks out of {current_thread_count}."
)
new_task = RenderTask(render_req, task_data)
if session.put(new_task, TASK_TTL):
@ -489,4 +559,4 @@ def render(render_req: GenerateImageRequest, task_data: TaskData):
return new_task
finally:
manager_lock.release()
raise RuntimeError('Failed to add task to cache.')
raise RuntimeError("Failed to add task to cache.")

24
ui/easydiffusion/types.py
View File

@ -1,6 +1,7 @@
from pydantic import BaseModel
from typing import Any
class GenerateImageRequest(BaseModel):
prompt: str = ""
negative_prompt: str = ""
@ -18,29 +19,31 @@ class GenerateImageRequest(BaseModel):
prompt_strength: float = 0.8
preserve_init_image_color_profile = False
sampler_name: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
sampler_name: str = None # "ddim", "plms", "heun", "euler", "euler_a", "dpm2", "dpm2_a", "lms"
hypernetwork_strength: float = 0
class TaskData(BaseModel):
request_id: str = None
session_id: str = "session"
save_to_disk_path: str = None
vram_usage_level: str = "balanced" # or "low" or "medium"
vram_usage_level: str = "balanced" # or "low" or "medium"
use_face_correction: str = None # or "GFPGANv1.3"
use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
upscale_amount: int = 4 # or 2
use_face_correction: str = None # or "GFPGANv1.3"
use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
upscale_amount: int = 4 # or 2
use_stable_diffusion_model: str = "sd-v1-4"
# use_stable_diffusion_config: str = "v1-inference"
use_vae_model: str = None
use_hypernetwork_model: str = None
show_only_filtered_image: bool = False
output_format: str = "jpeg" # or "png"
output_format: str = "jpeg" # or "png"
output_quality: int = 75
metadata_output_format: str = "txt" # or "json"
metadata_output_format: str = "txt" # or "json"
stream_image_progress: bool = False
class MergeRequest(BaseModel):
model0: str = None
model1: str = None
@ -48,8 +51,9 @@ class MergeRequest(BaseModel):
out_path: str = "mix"
use_fp16 = True
class Image:
data: str # base64
data: str # base64
seed: int
is_nsfw: bool
path_abs: str = None
@ -65,6 +69,7 @@ class Image:
"path_abs": self.path_abs,
}
class Response:
render_request: GenerateImageRequest
task_data: TaskData
@ -80,7 +85,7 @@ class Response:
del self.render_request.init_image_mask
res = {
"status": 'succeeded',
"status": "succeeded",
"render_request": self.render_request.dict(),
"task_data": self.task_data.dict(),
"output": [],
@ -91,5 +96,6 @@ class Response:
return res
class UserInitiatedStop(Exception):
pass

4
ui/easydiffusion/utils/__init__.py
View File

@ -1,8 +1,8 @@
import logging
log = logging.getLogger('easydiffusion')
log = logging.getLogger("easydiffusion")
from .save_utils import (
save_images_to_disk,
get_printable_request,
)
)

133
ui/easydiffusion/utils/save_utils.py
View File

@ -7,89 +7,126 @@ from easydiffusion.types import TaskData, GenerateImageRequest
from sdkit.utils import save_images, save_dicts
filename_regex = re.compile('[^a-zA-Z0-9._-]')
filename_regex = re.compile("[^a-zA-Z0-9._-]")
# keep in sync with `ui/media/js/dnd.js`
TASK_TEXT_MAPPING = {
'prompt': 'Prompt',
'width': 'Width',
'height': 'Height',
'seed': 'Seed',
'num_inference_steps': 'Steps',
'guidance_scale': 'Guidance Scale',
'prompt_strength': 'Prompt Strength',
'use_face_correction': 'Use Face Correction',
'use_upscale': 'Use Upscaling',
'upscale_amount': 'Upscale By',
'sampler_name': 'Sampler',
'negative_prompt': 'Negative Prompt',
'use_stable_diffusion_model': 'Stable Diffusion model',
'use_vae_model': 'VAE model',
'use_hypernetwork_model': 'Hypernetwork model',
'hypernetwork_strength': 'Hypernetwork Strength'
"prompt": "Prompt",
"width": "Width",
"height": "Height",
"seed": "Seed",
"num_inference_steps": "Steps",
"guidance_scale": "Guidance Scale",
"prompt_strength": "Prompt Strength",
"use_face_correction": "Use Face Correction",
"use_upscale": "Use Upscaling",
"upscale_amount": "Upscale By",
"sampler_name": "Sampler",
"negative_prompt": "Negative Prompt",
"use_stable_diffusion_model": "Stable Diffusion model",
"use_vae_model": "VAE model",
"use_hypernetwork_model": "Hypernetwork model",
"hypernetwork_strength": "Hypernetwork Strength",
}
def save_images_to_disk(images: list, filtered_images: list, req: GenerateImageRequest, task_data: TaskData):
now = time.time()
save_dir_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub('_', task_data.session_id))
save_dir_path = os.path.join(task_data.save_to_disk_path, filename_regex.sub("_", task_data.session_id))
metadata_entries = get_metadata_entries_for_request(req, task_data)
make_filename = make_filename_callback(req, now=now)
if task_data.show_only_filtered_image or filtered_images is images:
save_images(filtered_images, save_dir_path, file_name=make_filename, output_format=task_data.output_format, output_quality=task_data.output_quality)
if task_data.metadata_output_format.lower() in ['json', 'txt', 'embed']:
save_dicts(metadata_entries, save_dir_path, file_name=make_filename, output_format=task_data.metadata_output_format, file_format=task_data.output_format)
save_images(
filtered_images,
save_dir_path,
file_name=make_filename,
output_format=task_data.output_format,
output_quality=task_data.output_quality,
)
if task_data.metadata_output_format.lower() in ["json", "txt", "embed"]:
save_dicts(
metadata_entries,
save_dir_path,
file_name=make_filename,
output_format=task_data.metadata_output_format,
file_format=task_data.output_format,
)
else:
make_filter_filename = make_filename_callback(req, now=now, suffix='filtered')
make_filter_filename = make_filename_callback(req, now=now, suffix="filtered")
save_images(
images,
save_dir_path,
file_name=make_filename,
output_format=task_data.output_format,
output_quality=task_data.output_quality,
)
save_images(
filtered_images,
save_dir_path,
file_name=make_filter_filename,
output_format=task_data.output_format,
output_quality=task_data.output_quality,
)
if task_data.metadata_output_format.lower() in ["json", "txt", "embed"]:
save_dicts(
metadata_entries,
save_dir_path,
file_name=make_filter_filename,
output_format=task_data.metadata_output_format,
file_format=task_data.output_format,
)
save_images(images, save_dir_path, file_name=make_filename, output_format=task_data.output_format, output_quality=task_data.output_quality)
save_images(filtered_images, save_dir_path, file_name=make_filter_filename, output_format=task_data.output_format, output_quality=task_data.output_quality)
if task_data.metadata_output_format.lower() in ['json', 'txt', 'embed']:
save_dicts(metadata_entries, save_dir_path, file_name=make_filter_filename, output_format=task_data.metadata_output_format, file_format=task_data.output_format)
def get_metadata_entries_for_request(req: GenerateImageRequest, task_data: TaskData):
metadata = get_printable_request(req)
metadata.update({
'use_stable_diffusion_model': task_data.use_stable_diffusion_model,
'use_vae_model': task_data.use_vae_model,
'use_hypernetwork_model': task_data.use_hypernetwork_model,
'use_face_correction': task_data.use_face_correction,
'use_upscale': task_data.use_upscale,
})
if metadata['use_upscale'] is not None:
metadata['upscale_amount'] = task_data.upscale_amount
if (task_data.use_hypernetwork_model is None):
del metadata['hypernetwork_strength']
metadata.update(
{
"use_stable_diffusion_model": task_data.use_stable_diffusion_model,
"use_vae_model": task_data.use_vae_model,
"use_hypernetwork_model": task_data.use_hypernetwork_model,
"use_face_correction": task_data.use_face_correction,
"use_upscale": task_data.use_upscale,
}
)
if metadata["use_upscale"] is not None:
metadata["upscale_amount"] = task_data.upscale_amount
if task_data.use_hypernetwork_model is None:
del metadata["hypernetwork_strength"]
# if text, format it in the text format expected by the UI
is_txt_format = (task_data.metadata_output_format.lower() == 'txt')
is_txt_format = task_data.metadata_output_format.lower() == "txt"
if is_txt_format:
metadata = {TASK_TEXT_MAPPING[key]: val for key, val in metadata.items() if key in TASK_TEXT_MAPPING}
entries = [metadata.copy() for _ in range(req.num_outputs)]
for i, entry in enumerate(entries):
entry['Seed' if is_txt_format else 'seed'] = req.seed + i
entry["Seed" if is_txt_format else "seed"] = req.seed + i
return entries
def get_printable_request(req: GenerateImageRequest):
metadata = req.dict()
del metadata['init_image']
del metadata['init_image_mask']
if (req.init_image is None):
del metadata['prompt_strength']
del metadata["init_image"]
del metadata["init_image_mask"]
if req.init_image is None:
del metadata["prompt_strength"]
return metadata
def make_filename_callback(req: GenerateImageRequest, suffix=None, now=None):
if now is None:
now = time.time()
def make_filename(i):
img_id = base64.b64encode(int(now+i).to_bytes(8, 'big')).decode() # Generate unique ID based on time.
img_id = img_id.translate({43:None, 47:None, 61:None})[-8:] # Remove + / = and keep last 8 chars.
prompt_flattened = filename_regex.sub('_', req.prompt)[:50]
def make_filename(i):
img_id = base64.b64encode(int(now + i).to_bytes(8, "big")).decode() # Generate unique ID based on time.
img_id = img_id.translate({43: None, 47: None, 61: None})[-8:] # Remove + / = and keep last 8 chars.
prompt_flattened = filename_regex.sub("_", req.prompt)[:50]
name = f"{prompt_flattened}_{img_id}"
name = name if suffix is None else f'{name}_{suffix}'
name = name if suffix is None else f"{name}_{suffix}"
return name
return make_filename

11
ui/index.html
View File

@ -26,7 +26,7 @@
<div id="logo">
<h1>
Easy Diffusion
<small>v2.5.16 <span id="updateBranchLabel"></span></small>
<small>v2.5.20 <span id="updateBranchLabel"></span></small>
</h1>
</div>
<div id="server-status">
@ -155,6 +155,11 @@
<option value="dpmpp_sde">DPM++ SDE</option>
<option value="dpm_fast">DPM Fast</option>
<option value="dpm_adaptive">DPM Adaptive</option>
<option value="unipc_snr">UniPC SNR</option>
<option value="unipc_tu">UniPC TU</option>
<option value="unipc_snr_2">UniPC SNR 2</option>
<option value="unipc_tu_2">UniPC TC 2</option>
<option value="unipc_tq">UniPC TQ</option>
</select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip top-left">Click to learn more about samplers</span></i></a>
</td></tr>
@ -228,7 +233,7 @@
<div><ul>
<li><b class="settings-subheader">Render Settings</b></li>
<li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slower images)</small></label></li>
<li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes</label> <small><input id="gfpgan_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" /></small></li>
<li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox"> <label for="use_face_correction">Fix incorrect faces and eyes</label> <div style="display:inline-block;"><input id="gfpgan_model" type="text" spellcheck="false" autocomplete="off" class="model-filter" data-path="" /></div></li>
<li class="pl-5">
<input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Scale up by</label>
<select id="upscale_amount" name="upscale_amount">
@ -277,9 +282,11 @@
and selecting the desired modifiers.<br/><br/>
Click "Image Settings" for additional settings like seed, image size, number of images to generate etc.<br/><br/>Enjoy! :)
</div>
<div id="preview-content">
<div id="preview-tools">
<button id="clear-all-previews" class="secondaryButton"><i class="fa-solid fa-trash-can"></i> Clear All</button>
<button id="save-all-images" class="primaryButton"><i class="fa-solid fa-download"></i> Download All Images</button>
</div>
</div>
</div>

4
ui/media/css/main.css
View File

@ -468,6 +468,7 @@ div.img-preview img {
background: var(--accent-color);
border: var(--primary-button-border);
color: rgb(255, 221, 255);
padding: 3pt 6pt;
}
.secondaryButton {
background: rgb(132, 8, 0);
@ -750,9 +751,8 @@ input::file-selector-button {
right: calc(var(--input-border-size) + var(--input-switch-padding));
opacity: 1;
}
.model-filter {
width: calc(100% - 40px);
width: calc(100% - 20px);
padding-right: 20px;
white-space: nowrap;
overflow: hidden;

1
ui/media/css/searchable-models.css
View File

@ -75,6 +75,7 @@
padding-top: 3px;
cursor: pointer;
font-size: 8pt;
transition: none;
}
.model-input {

4
ui/media/js/dnd.js
View File

@ -375,6 +375,10 @@ function readUI() {
}
function getModelPath(filename, extensions)
{
if (filename === null) {
return
}
let pathIdx
if (filename.includes('/models/stable-diffusion/')) {
pathIdx = filename.indexOf('/models/stable-diffusion/') + 25 // Linux, Mac paths

51
ui/media/js/main.js
View File

@ -33,7 +33,7 @@ let promptStrengthField = document.querySelector('#prompt_strength')
let samplerField = document.querySelector('#sampler_name')
let samplerSelectionContainer = document.querySelector("#samplerSelection")
let useFaceCorrectionField = document.querySelector("#use_face_correction")
let gfpganModelField = new ModelDropdown(document.querySelector("#gfpgan_model"), 'gfpgan', 'None')
let gfpganModelField = new ModelDropdown(document.querySelector("#gfpgan_model"), 'gfpgan')
let useUpscalingField = document.querySelector("#use_upscale")
let upscaleModelField = document.querySelector("#upscale_model")
let upscaleAmountField = document.querySelector("#upscale_amount")
@ -61,6 +61,7 @@ let promptStrengthContainer = document.querySelector('#prompt_strength_container
let initialText = document.querySelector("#initial-text")
let previewTools = document.querySelector("#preview-tools")
let clearAllPreviewsBtn = document.querySelector("#clear-all-previews")
let saveAllImagesBtn = document.querySelector("#save-all-images")
let maskSetting = document.querySelector('#enable_mask')
@ -269,6 +270,22 @@ function showImages(reqBody, res, outputContainer, livePreview) {
</div>
`
outputContainer.appendChild(imageItemElem)
const imageRemoveBtn = imageItemElem.querySelector('.imgPreviewItemClearBtn')
let parentTaskContainer = imageRemoveBtn.closest('.imageTaskContainer')
imageRemoveBtn.addEventListener('click', (e) => {
shiftOrConfirm(e, "Remove the image from the results?", () => {
imageItemElem.style.display = 'none'
let allHidden = true;
let children = parentTaskContainer.querySelectorAll('.imgItem');
for(let x = 0; x < children.length; x++) {
let child = children[x];
if(child.style.display != "none") {
allHidden = false;
}
}
if(allHidden === true) {parentTaskContainer.classList.add("displayNone")}
})
})
}
const imageElem = imageItemElem.querySelector('img')
imageElem.src = imageData
@ -278,23 +295,6 @@ function showImages(reqBody, res, outputContainer, livePreview) {
imageElem.setAttribute('data-steps', imageInferenceSteps)
imageElem.setAttribute('data-guidance', imageGuidanceScale)
const imageRemoveBtn = imageItemElem.querySelector('.imgPreviewItemClearBtn')
let parentTaskContainer = imageRemoveBtn.closest('.imageTaskContainer')
imageRemoveBtn.addEventListener('click', (e) => {
console.log(e)
shiftOrConfirm(e, "Remove the image from the results?", () => {
imageItemElem.style.display = 'none'
let allHidden = true;
let children = parentTaskContainer.querySelectorAll('.imgItem');
for(let x = 0; x < children.length; x++) {
let child = children[x];
if(child.style.display != "none") {
allHidden = false;
}
}
if(allHidden === true) {parentTaskContainer.classList.add("displayNone")}
})
})
const imageInfo = imageItemElem.querySelector('.imgItemInfo')
imageInfo.style.visibility = (livePreview ? 'hidden' : 'visible')
@ -1160,6 +1160,21 @@ clearAllPreviewsBtn.addEventListener('click', (e) => { shiftOrConfirm(e, "Clear
taskEntries.forEach(removeTask)
})})
saveAllImagesBtn.addEventListener('click', (e) => {
document.querySelectorAll(".imageTaskContainer").forEach(container => {
let req = htmlTaskMap.get(container)
container.querySelectorAll(".imgContainer img").forEach(img => {
if (img.closest('.imgItem').style.display === 'none') {
// console.log('skipping hidden image', img)
return
}
onDownloadImageClick(req, img)
// console.log(req)
})
})
})
stopImageBtn.addEventListener('click', (e) => { shiftOrConfirm(e, "Stop all the tasks?", async function(e) {
await stopAllTasks()
})})

232
ui/media/js/searchable-models.js
View File

@ -53,6 +53,15 @@ class ModelDropdown
this.modelFilter.dataset.path = path
this.selectEntry(path)
}
get disabled() {
return this.modelFilter.disabled
}
set disabled(state) {
this.modelFilter.disabled = state
if (this.modelFilterArrow) {
this.modelFilterArrow.style.color = state ? 'dimgray' : ''
}
}
addEventListener(type, listener, options) {
return this.modelFilter.addEventListener(type, listener, options)
}
@ -350,13 +359,15 @@ class ModelDropdown
toggleModelList(e) {
e.preventDefault()
if (this.modelList.style.display != 'block') {
this.showModelList()
}
else
{
this.hideModelList()
this.modelFilter.select()
if (!this.modelFilter.disabled) {
if (this.modelList.style.display != 'block') {
this.showModelList()
}
else
{
this.hideModelList()
this.modelFilter.select()
}
}
}
@ -484,44 +495,11 @@ class ModelDropdown
return { width, height }
}
flattenModelList(models, path) {
models.forEach(entry => {
if (Array.isArray(entry)) {
this.flattenModelList(entry[1], path + '/' + entry[0])
}
else
{
this.flatModelList.push(path == '' ? entry : path + '/' + entry)
}
})
}
// sort models
getFolder(model) {
return model.substring(0, model.lastIndexOf('/') + 1)
}
sortModels(models) {
// sort the models in alphabetical order, root folder models last
models.sort((a, b) => a.toLowerCase().localeCompare(b.toLowerCase()))
/*
// sort the models in alphabetical order, root folder models first
models = models.sort()
let found
do {
found = false
for (let i = 0; i < models.length - 1; i++) {
if (
(this.getFolder(models[i]) === this.getFolder(models[i+1]) && models[i].toLowerCase().localeCompare(models[i+1].toLowerCase()) > 0) // same folder, sort by alphabetical order
|| (this.getFolder(models[i]).toLowerCase().localeCompare(this.getFolder(models[i+1]).toLowerCase()) > 0) // L1 folder > L2 folder
) {
[models[i], models[i+1]] = [models[i+1], models[i]]
found = true
}
}
} while (found)
*/
/**
* @param {Array<string>} models
*/
sortStringArray(models) {
models.sort((a, b) => a.localeCompare(b, undefined, { sensitivity: 'base' }))
}
populateModels() {
@ -539,14 +517,21 @@ class ModelDropdown
}
createDropdown() {
// prepare to sort the models
this.flattenModelList(this.inputModels, '')
this.sortModels(this.flatModelList)
// create dropdown entries
this.modelFilter.insertAdjacentHTML('afterend', this.parseModels(this.flatModelList))
this.modelFilter.insertAdjacentElement('afterend', this.createRootModelList(this.inputModels))
this.modelFilter.insertAdjacentElement(
'afterend',
this.createElement(
'i',
{ id: `${this.modelFilter.id}-model-filter-arrow` },
['model-selector-arrow', 'fa-solid', 'fa-angle-down'],
),
)
this.modelFilter.classList.add('model-selector')
this.modelFilterArrow = document.querySelector(`#${this.modelFilter.id}-model-filter-arrow`)
if (this.modelFilterArrow) {
this.modelFilterArrow.style.color = this.modelFilter.disabled ? 'dimgray' : ''
}
this.modelList = document.querySelector(`#${this.modelFilter.id}-model-list`)
this.modelResult = document.querySelector(`#${this.modelFilter.id}-model-result`)
this.modelNoResult = document.querySelector(`#${this.modelFilter.id}-model-no-result`)
@ -567,47 +552,122 @@ class ModelDropdown
this.selectEntry(this.activeModel)
}
parseModels(models) {
let html = `<i id="${this.modelFilter.id}-model-filter-arrow" class="model-selector-arrow fa-solid fa-angle-down"></i>
<ul id="${this.modelFilter.id}-model-list" class="model-list">
<li id="${this.modelFilter.id}-model-no-result" class="model-no-result">No result</li>
<li id="${this.modelFilter.id}-model-result" class="model-result">
<ul>
`
if (this.noneEntry != '') {
html += `<li data-path='' class='model-file in-root-folder'>${this.noneEntry}</li>`
/**
*
* @param {string} tag
* @param {object} attributes
* @param {Array<string>} classes
* @returns {HTMLElement}
*/
createElement(tagName, attributes, classes, text) {
const element = document.createElement(tagName)
if (attributes) {
Object.entries(attributes).forEach(([key, value]) => {
element.setAttribute(key, value)
})
}
let currentFolder = ''
models.forEach(entry => {
const folder = entry.substring(0, 1) == '/' ? entry.substring(1, entry.lastIndexOf('/')) : ''
if (folder !== '' && folder !== currentFolder) {
if (currentFolder != '') {
html += '</ul></li>'
if (classes) {
classes.forEach(className => element.classList.add(className))
}
if (text) {
element.appendChild(document.createTextNode(text))
}
return element
}
/**
* @param {Array<string | object} modelTree
* @param {string} folderName
* @param {boolean} isRootFolder
* @returns {HTMLElement}
*/
createModelNodeList(folderName, modelTree, isRootFolder) {
const listElement = this.createElement('ul')
const foldersMap = new Map()
const modelsMap = new Map()
modelTree.forEach(model => {
if (Array.isArray(model)) {
const [childFolderName, childModels] = model
foldersMap.set(
childFolderName,
this.createModelNodeList(
`${folderName || ''}/${childFolderName}`,
childModels,
false,
),
)
} else {
const classes = ['model-file']
if (isRootFolder) {
classes.push('in-root-folder')
}
html += `<li class='model-folder'>/${folder}<ul>`
currentFolder = folder
// Remove the leading slash from the model path
const fullPath = folderName ? `${folderName.substring(1)}/${model}` : model
modelsMap.set(
model,
this.createElement('li', { 'data-path': fullPath }, classes, model),
)
}
else if (folder == '' && currentFolder !== '') {
currentFolder = ''
html += '</ul></li>'
}
const modelName = entry.substring(entry.lastIndexOf('/') + 1)
if (entry.substring(0, 1) == '/') {
entry = entry.substring(1)
}
html += `<li data-path='${entry}' class='model-file${currentFolder == '' ? ' in-root-folder' : ''}'>${modelName}</li>`
})
if (currentFolder != '') {
html += '</ul></li>'
const childFolderNames = Array.from(foldersMap.keys())
this.sortStringArray(childFolderNames)
const folderElements = childFolderNames.map(name => foldersMap.get(name))
const modelNames = Array.from(modelsMap.keys())
this.sortStringArray(modelNames)
const modelElements = modelNames.map(name => modelsMap.get(name))
if (modelElements.length && folderName) {
listElement.appendChild(this.createElement('li', undefined, ['model-folder'], folderName))
}
html += `
</ul>
</li>
</ul>
`
return html
const allModelElements = isRootFolder ? [...folderElements, ...modelElements] : [...modelElements, ...folderElements]
allModelElements.forEach(e => listElement.appendChild(e))
return listElement
}
/**
* @param {object} modelTree
* @returns {HTMLElement}
*/
createRootModelList(modelTree) {
const rootList = this.createElement(
'ul',
{ id: `${this.modelFilter.id}-model-list` },
['model-list'],
)
rootList.appendChild(
this.createElement(
'li',
{ id: `${this.modelFilter.id}-model-no-result` },
['model-no-result'],
'No result'
),
)
if (this.noneEntry) {
rootList.appendChild(
this.createElement(
'li',
{ 'data-path': '' },
['model-file', 'in-root-folder'],
this.noneEntry,
),
)
}
const containerListItem = this.createElement(
'li',
{ id: `${this.modelFilter.id}-model-result` },
['model-result'],
)
containerListItem.appendChild(this.createModelNodeList(undefined, modelTree, true))
rootList.appendChild(containerListItem)
return rootList
}
}

13
ui/media/js/utils.js
View File

@ -20,19 +20,6 @@ function getNextSibling(elem, selector) {
}
}
function findClosestAncestor(element, selector) {
if (!element || !element.parentNode) {
// reached the top of the DOM tree, return null
return null;
} else if (element.parentNode.matches(selector)) {
// found an ancestor that matches the selector, return it
return element.parentNode;
} else {
// continue searching upwards
return findClosestAncestor(element.parentNode, selector);
}
}
/* Panel Stuff */

13
ui/plugins/ui/merge.plugin.js
View File

@ -334,15 +334,10 @@
linkTabContents(tabSettingsSingle)
linkTabContents(tabSettingsBatch)
/////////////////////// Event Listener
document.addEventListener('tabClick', (e) => {
if (e.detail.name == 'merge') {
console.log('Activate')
let mergeModelAField = new ModelDropdown(document.querySelector('#mergeModelA'), 'stable-diffusion')
let mergeModelBField = new ModelDropdown(document.querySelector('#mergeModelB'), 'stable-diffusion')
updateChart()
}
})
console.log('Activate')
let mergeModelAField = new ModelDropdown(document.querySelector('#mergeModelA'), 'stable-diffusion')
let mergeModelBField = new ModelDropdown(document.querySelector('#mergeModelB'), 'stable-diffusion')
updateChart()
// slider
const singleMergeRatioField = document.querySelector('#single-merge-ratio')