BatchTagger / FixImage.py
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Upload FixImage.py
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import os
import random
import sys
import json
import argparse
import contextlib
from typing import Sequence, Mapping, Any, Union
import torch
from random import randrange
def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
"""Returns the value at the given index of a sequence or mapping.
If the object is a sequence (like list or string), returns the value at the given index.
If the object is a mapping (like a dictionary), returns the value at the index-th key.
Some return a dictionary, in these cases, we look for the "results" key
Args:
obj (Union[Sequence, Mapping]): The object to retrieve the value from.
index (int): The index of the value to retrieve.
Returns:
Any: The value at the given index.
Raises:
IndexError: If the index is out of bounds for the object and the object is not a mapping.
"""
try:
return obj[index]
except KeyError:
return obj["result"][index]
def find_path(name: str, path: str = None) -> str:
"""
Recursively looks at parent folders starting from the given path until it finds the given name.
Returns the path as a Path object if found, or None otherwise.
"""
# If no path is given, use the current working directory
if path is None:
if args is None or args.comfyui_directory is None:
path = os.getcwd()
else:
path = args.comfyui_directory
# Check if the current directory contains the name
if name in os.listdir(path):
path_name = os.path.join(path, name)
print(f"{name} found: {path_name}")
return path_name
# Get the parent directory
parent_directory = os.path.dirname(path)
# If the parent directory is the same as the current directory, we've reached the root and stop the search
if parent_directory == path:
return None
# Recursively call the function with the parent directory
return find_path(name, parent_directory)
def add_comfyui_directory_to_sys_path() -> None:
"""
Add 'ComfyUI' to the sys.path
"""
comfyui_path = find_path("ComfyUI")
if comfyui_path is not None and os.path.isdir(comfyui_path):
sys.path.append(comfyui_path)
manager_path = os.path.join(
comfyui_path, "custom_nodes", "ComfyUI-Manager", "glob"
)
if os.path.isdir(manager_path) and os.listdir(manager_path):
sys.path.append(manager_path)
global has_manager
has_manager = True
import __main__
if getattr(__main__, "__file__", None) is None:
__main__.__file__ = os.path.join(comfyui_path, "main.py")
print(f"'{comfyui_path}' added to sys.path")
def add_extra_model_paths() -> None:
"""
Parse the optional extra_model_paths.yaml file and add the parsed paths to the sys.path.
"""
from comfy.options import enable_args_parsing
enable_args_parsing()
from utils.extra_config import load_extra_path_config
extra_model_paths = find_path("extra_model_paths.yaml")
if extra_model_paths is not None:
load_extra_path_config(extra_model_paths)
else:
print("Could not find the extra_model_paths config file.")
def import_custom_nodes() -> None:
"""Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS
This function sets up a new asyncio event loop, initializes the PromptServer,
creates a PromptQueue, and initializes the custom nodes.
"""
if has_manager:
try:
import manager_core as manager
except ImportError:
print("Could not import manager_core, proceeding without it.")
return
else:
if hasattr(manager, "get_config"):
print("Patching manager_core.get_config to enforce offline mode.")
try:
get_config = manager.get_config
def _get_config(*args, **kwargs):
config = get_config(*args, **kwargs)
config["network_mode"] = "offline"
return config
manager.get_config = _get_config
except Exception as e:
print("Failed to patch manager_core.get_config:", e)
import asyncio
import execution
from nodes import init_extra_nodes
import server
# Creating a new event loop and setting it as the default loop
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
async def inner():
# Creating an instance of PromptServer with the loop
server_instance = server.PromptServer(loop)
execution.PromptQueue(server_instance)
# Initializing custom nodes
await init_extra_nodes(init_custom_nodes=True)
loop.run_until_complete(inner())
def save_image_wrapper(context, cls):
if args.output is None:
return cls
from PIL import Image, ImageOps, ImageSequence
from PIL.PngImagePlugin import PngInfo
import numpy as np
class WrappedSaveImage(cls):
counter = 0
def save_images(
self, images, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None
):
if args.output is None:
return super().save_images(
images, filename_prefix, prompt, extra_pnginfo
)
else:
if len(images) > 1 and args.output == "-":
raise ValueError("Cannot save multiple images to stdout")
filename_prefix += self.prefix_append
results = list()
for batch_number, image in enumerate(images):
i = 255.0 * image.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
metadata = None
if not args.disable_metadata:
metadata = PngInfo()
if prompt is not None:
metadata.add_text("prompt", json.dumps(prompt))
if extra_pnginfo is not None:
for x in extra_pnginfo:
metadata.add_text(x, json.dumps(extra_pnginfo[x]))
if args.output == "-":
# Hack to briefly restore stdout
if context is not None:
context.__exit__(None, None, None)
try:
img.save(
sys.stdout.buffer,
format="png",
pnginfo=metadata,
compress_level=self.compress_level,
)
finally:
if context is not None:
context.__enter__()
else:
subfolder = ""
if len(images) == 1:
if os.path.isdir(args.output):
subfolder = args.output
file = "output.png"
else:
subfolder, file = os.path.split(args.output)
if subfolder == "":
subfolder = os.getcwd()
else:
if os.path.isdir(args.output):
subfolder = args.output
file = filename_prefix
else:
subfolder, file = os.path.split(args.output)
if subfolder == "":
subfolder = os.getcwd()
files = os.listdir(subfolder)
file_pattern = file
while True:
filename_with_batch_num = file_pattern.replace(
"%batch_num%", str(batch_number)
)
file = (
f"{filename_with_batch_num}_{self.counter:05}.png"
)
self.counter += 1
if file not in files:
break
img.save(
os.path.join(subfolder, file),
pnginfo=metadata,
compress_level=self.compress_level,
)
print("Saved image to", os.path.join(subfolder, file))
results.append(
{
"filename": file,
"subfolder": subfolder,
"type": self.type,
}
)
return {"ui": {"images": results}}
return WrappedSaveImage
def parse_arg(s: Any, default: Any = None) -> Any:
"""Parses a JSON string, returning it unchanged if the parsing fails."""
if __name__ == "__main__" or not isinstance(s, str):
return s
try:
return json.loads(s)
except json.JSONDecodeError:
return s
parser = argparse.ArgumentParser(
description="A converted ComfyUI workflow. Node inputs listed below. Values passed should be valid JSON (assumes string if not valid JSON)."
)
parser.add_argument(
"--ckpt_name1",
default="SDXLCheckpoint.safetensors",
help='Argument 0, input `ckpt_name` for node "Load Checkpoint" id 14 (autogenerated)',
)
parser.add_argument(
"--text2",
default="Xx_negative_xX",
help='Argument 0, input `text` for node "CLIP Text Encode (Prompt)" id 7 (autogenerated)',
)
parser.add_argument(
"--text3",
default="Xx_positive_xX",
help='Argument 0, input `text` for node "CLIPTextEncode with BREAK syntax" id 15 (autogenerated)',
)
parser.add_argument(
"--image4",
default="Fast_00076_.png [output]",
help='Argument 0, input `image` for node "Load Image (from Outputs)" id 24 (autogenerated)',
)
parser.add_argument(
"--seed5",
default=550873067544100,
help='Argument 1, input `seed` for node "KSampler" id 3 (autogenerated)',
)
parser.add_argument(
"--steps6",
default=28,
help='Argument 2, input `steps` for node "KSampler" id 3 (autogenerated)',
)
parser.add_argument(
"--cfg7",
default=4.5,
help='Argument 3, input `cfg` for node "KSampler" id 3 (autogenerated)',
)
parser.add_argument(
"--sampler_name8",
default="euler_ancestral",
help='Argument 4, input `sampler_name` for node "KSampler" id 3 (autogenerated)',
)
parser.add_argument(
"--scheduler9",
default="normal",
help='Argument 5, input `scheduler` for node "KSampler" id 3 (autogenerated)',
)
parser.add_argument(
"--denoise10",
default=0.87,
help='Argument 9, input `denoise` for node "KSampler" id 3 (autogenerated)',
)
parser.add_argument(
"--filename_prefix11",
default="Fixed",
help='Argument 1, input `filename_prefix` for node "Save Image" id 9 (autogenerated)',
)
parser.add_argument(
"--queue-size",
"-q",
type=int,
default=1,
help="How many times the workflow will be executed (default: 1)",
)
parser.add_argument(
"--comfyui-directory",
"-c",
default=None,
help="Where to look for ComfyUI (default: current directory)",
)
parser.add_argument(
"--output",
"-o",
default=None,
help="The location to save the output image. Either a file path, a directory, or - for stdout (default: the ComfyUI output directory)",
)
parser.add_argument(
"--disable-metadata",
action="store_true",
help="Disables writing workflow metadata to the outputs",
)
comfy_args = [sys.argv[0]]
if __name__ == "__main__" and "--" in sys.argv:
idx = sys.argv.index("--")
comfy_args += sys.argv[idx + 1 :]
sys.argv = sys.argv[:idx]
args = None
if __name__ == "__main__":
args = parser.parse_args()
sys.argv = comfy_args
if args is not None and args.output is not None and args.output == "-":
ctx = contextlib.redirect_stdout(sys.stderr)
else:
ctx = contextlib.nullcontext()
PROMPT_DATA = json.loads(
'{"3": {"inputs": {"seed": 550873067544100, "steps": 28, "cfg": 4.5, "sampler_name": "euler_ancestral", "scheduler": "normal", "denoise": 0.87, "model": ["14", 0], "positive": ["15", 0], "negative": ["7", 0], "latent_image": ["22", 0]}, "class_type": "KSampler", "_meta": {"title": "KSampler"}}, "7": {"inputs": {"text": "Xx_negative_xX", "clip": ["14", 1]}, "class_type": "CLIPTextEncode", "_meta": {"title": "CLIP Text Encode (Prompt)"}}, "8": {"inputs": {"samples": ["3", 0], "vae": ["14", 2]}, "class_type": "VAEDecode", "_meta": {"title": "VAE Decode"}}, "9": {"inputs": {"filename_prefix": "Fixed", "images": ["8", 0]}, "class_type": "SaveImage", "_meta": {"title": "Save Image"}}, "14": {"inputs": {"ckpt_name": "SDXLCheckpoint.safetensors"}, "class_type": "CheckpointLoaderSimple", "_meta": {"title": "Load Checkpoint"}}, "15": {"inputs": {"text": "Xx_positive_xX", "clip": ["14", 1]}, "class_type": "CLIPTextEncodeWithBreak", "_meta": {"title": "CLIPTextEncode with BREAK syntax"}}, "22": {"inputs": {"pixels": ["24", 0], "vae": ["14", 2]}, "class_type": "VAEEncode", "_meta": {"title": "VAE Encode"}}, "24": {"inputs": {"image": "Fast_00076_.png [output]", "refresh": "refresh"}, "class_type": "LoadImageOutput", "_meta": {"title": "Load Image (from Outputs)"}}}'
)
def import_custom_nodes() -> None:
"""Find all custom nodes in the custom_nodes folder and add those node objects to NODE_CLASS_MAPPINGS
This function sets up a new asyncio event loop, initializes the PromptServer,
creates a PromptQueue, and initializes the custom nodes.
"""
if has_manager:
try:
import manager_core as manager
except ImportError:
print("Could not import manager_core, proceeding without it.")
return
else:
if hasattr(manager, "get_config"):
print("Patching manager_core.get_config to enforce offline mode.")
try:
get_config = manager.get_config
def _get_config(*args, **kwargs):
config = get_config(*args, **kwargs)
config["network_mode"] = "offline"
return config
manager.get_config = _get_config
except Exception as e:
print("Failed to patch manager_core.get_config:", e)
import asyncio
import execution
from nodes import init_extra_nodes
import server
# Creating a new event loop and setting it as the default loop
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
async def inner():
# Creating an instance of PromptServer with the loop
server_instance = server.PromptServer(loop)
execution.PromptQueue(server_instance)
# Initializing custom nodes
await init_extra_nodes(init_custom_nodes=True)
loop.run_until_complete(inner())
_custom_nodes_imported = False
_custom_path_added = False
def main(*func_args, **func_kwargs):
global args, _custom_nodes_imported, _custom_path_added
if __name__ == "__main__":
if args is None:
args = parser.parse_args()
else:
defaults = dict(
(arg, parser.get_default(arg))
for arg in ["queue_size", "comfyui_directory", "output", "disable_metadata"]
+ [
"ckpt_name1",
"text2",
"text3",
"image4",
"seed5",
"steps6",
"cfg7",
"sampler_name8",
"scheduler9",
"denoise10",
"filename_prefix11",
]
)
all_args = dict()
all_args.update(defaults)
all_args.update(func_kwargs)
args = argparse.Namespace(**all_args)
with ctx:
if not _custom_path_added:
add_comfyui_directory_to_sys_path()
add_extra_model_paths()
_custom_path_added = True
if not _custom_nodes_imported:
import_custom_nodes()
_custom_nodes_imported = True
from nodes import NODE_CLASS_MAPPINGS
with torch.inference_mode(), ctx:
checkpointloadersimple = NODE_CLASS_MAPPINGS["CheckpointLoaderSimple"]()
checkpointloadersimple_14 = checkpointloadersimple.load_checkpoint(
ckpt_name=parse_arg(args.ckpt_name1)
)
cliptextencode = NODE_CLASS_MAPPINGS["CLIPTextEncode"]()
cliptextencode_7 = cliptextencode.encode(
text=parse_arg(args.text2),
clip=get_value_at_index(checkpointloadersimple_14, 1),
)
cliptextencodewithbreak = NODE_CLASS_MAPPINGS["CLIPTextEncodeWithBreak"]()
cliptextencodewithbreak_15 = cliptextencodewithbreak.encode(
text=parse_arg(args.text3),
clip=get_value_at_index(checkpointloadersimple_14, 1),
)
loadimageoutput = NODE_CLASS_MAPPINGS["LoadImageOutput"]()
loadimageoutput_24 = loadimageoutput.load_image(image=parse_arg(args.image4))
vaeencode = NODE_CLASS_MAPPINGS["VAEEncode"]()
vaeencode_22 = vaeencode.encode(
pixels=get_value_at_index(loadimageoutput_24, 0),
vae=get_value_at_index(checkpointloadersimple_14, 2),
)
ksampler = NODE_CLASS_MAPPINGS["KSampler"]()
vaedecode = NODE_CLASS_MAPPINGS["VAEDecode"]()
saveimage = save_image_wrapper(ctx, NODE_CLASS_MAPPINGS["SaveImage"])()
for q in range(args.queue_size):
ksampler_3 = ksampler.sample(
seed=randrange(1000000000),
steps=parse_arg(args.steps6),
cfg=parse_arg(args.cfg7),
sampler_name=parse_arg(args.sampler_name8),
scheduler=parse_arg(args.scheduler9),
denoise=parse_arg(args.denoise10),
model=get_value_at_index(checkpointloadersimple_14, 0),
positive=get_value_at_index(cliptextencodewithbreak_15, 0),
negative=get_value_at_index(cliptextencode_7, 0),
latent_image=get_value_at_index(vaeencode_22, 0),
)
vaedecode_8 = vaedecode.decode(
samples=get_value_at_index(ksampler_3, 0),
vae=get_value_at_index(checkpointloadersimple_14, 2),
)
if __name__ != "__main__":
return dict(
filename_prefix=parse_arg(args.filename_prefix11),
images=get_value_at_index(vaedecode_8, 0),
prompt=PROMPT_DATA,
)
else:
saveimage_9 = saveimage.save_images(
filename_prefix=parse_arg(args.filename_prefix11),
images=get_value_at_index(vaedecode_8, 0),
prompt=PROMPT_DATA,
)
if __name__ == "__main__":
main()