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import re
import numpy as np
from modules import scripts, shared
try:
from scripts.global_state import update_cn_models, cn_models_names, cn_preprocessor_modules
from scripts.external_code import ResizeMode, ControlMode
except (ImportError, NameError):
import_error = True
else:
import_error = False
DEBUG_MODE = False
def debug_info(func):
def debug_info_(*args, **kwargs):
if DEBUG_MODE:
print(f"Debug info: {func.__name__}, {args}")
return func(*args, **kwargs)
return debug_info_
def find_dict(dict_list, keyword, search_key="name", stop=False):
result = next((d for d in dict_list if d[search_key] == keyword), None)
if result or not stop:
return result
else:
raise ValueError(f"Dictionary with value '{keyword}' in key '{search_key}' not found.")
def flatten(lst):
result = []
for element in lst:
if isinstance(element, list):
result.extend(flatten(element))
else:
result.append(element)
return result
def is_all_included(target_list, check_list, allow_blank=False, stop=False):
for element in flatten(target_list):
if allow_blank and str(element) in ["None", ""]:
continue
elif element not in check_list:
if not stop:
return False
else:
raise ValueError(f"'{element}' is not included in check list.")
return True
class ListParser():
"""This class restores a broken list caused by the following process
in the xyz_grid module.
-> valslist = [x.strip() for x in chain.from_iterable(
csv.reader(StringIO(vals)))]
It also performs type conversion,
adjusts the number of elements in the list, and other operations.
This class directly modifies the received list.
"""
numeric_pattern = {
int: {
"range": r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*",
"count": r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*"
},
float: {
"range": r"\s*([+-]?\s*\d+(?:\.\d*)?)\s*-\s*([+-]?\s*\d+(?:\.\d*)?)(?:\s*\(([+-]\d+(?:\.\d*)?)\s*\))?\s*",
"count": r"\s*([+-]?\s*\d+(?:\.\d*)?)\s*-\s*([+-]?\s*\d+(?:\.\d*)?)(?:\s*\[(\d+(?:\.\d*)?)\s*\])?\s*"
}
}
################################################
#
# Initialization method from here.
#
################################################
def __init__(self, my_list, converter=None, allow_blank=True, exclude_list=None, run=True):
self.my_list = my_list
self.converter = converter
self.allow_blank = allow_blank
self.exclude_list = exclude_list
self.re_bracket_start = None
self.re_bracket_start_precheck = None
self.re_bracket_end = None
self.re_bracket_end_precheck = None
self.re_range = None
self.re_count = None
self.compile_regex()
if run:
self.auto_normalize()
def compile_regex(self):
exclude_pattern = "|".join(self.exclude_list) if self.exclude_list else None
if exclude_pattern is None:
self.re_bracket_start = re.compile(r"^\[")
self.re_bracket_end = re.compile(r"\]$")
else:
self.re_bracket_start = re.compile(fr"^\[(?!(?:{exclude_pattern})\])")
self.re_bracket_end = re.compile(fr"(?<!\[(?:{exclude_pattern}))\]$")
if self.converter not in self.numeric_pattern:
return self
# If the converter is either int or float.
self.re_range = re.compile(self.numeric_pattern[self.converter]["range"])
self.re_count = re.compile(self.numeric_pattern[self.converter]["count"])
self.re_bracket_start_precheck = None
self.re_bracket_end_precheck = self.re_count
return self
################################################
#
# Public method from here.
#
################################################
################################################
# This method is executed at the time of initialization.
#
def auto_normalize(self):
if not self.has_list_notation():
self.numeric_range_parser()
self.type_convert()
return self
else:
self.fix_structure()
self.numeric_range_parser()
self.type_convert()
self.fill_to_longest()
return self
def has_list_notation(self):
return any(self._search_bracket(s) for s in self.my_list)
def numeric_range_parser(self, my_list=None, depth=0):
if self.converter not in self.numeric_pattern:
return self
my_list = self.my_list if my_list is None else my_list
result = []
is_matched = False
for s in my_list:
if isinstance(s, list):
result.extend(self.numeric_range_parser(s, depth+1))
continue
match = self._numeric_range_to_list(s)
if s != match:
is_matched = True
result.extend(match if not depth else [match])
continue
else:
result.append(s)
continue
if depth:
return self._transpose(result) if is_matched else [result]
else:
my_list[:] = result
return self
def type_convert(self, my_list=None):
my_list = self.my_list if my_list is None else my_list
for i, s in enumerate(my_list):
if isinstance(s, list):
self.type_convert(s)
elif self.allow_blank and (str(s) in ["None", ""]):
my_list[i] = None
elif self.converter:
my_list[i] = self.converter(s)
else:
my_list[i] = s
return self
def fix_structure(self):
def is_same_length(list1, list2):
return len(list1) == len(list2)
start_indices, end_indices = [], []
for i, s in enumerate(self.my_list):
if is_same_length(start_indices, end_indices):
replace_string = self._search_bracket(s, "[", replace="")
if s != replace_string:
s = replace_string
start_indices.append(i)
if not is_same_length(start_indices, end_indices):
replace_string = self._search_bracket(s, "]", replace="")
if s != replace_string:
s = replace_string
end_indices.append(i + 1)
self.my_list[i] = s
if not is_same_length(start_indices, end_indices):
raise ValueError(f"Lengths of {start_indices} and {end_indices} are different.")
# Restore the structure of a list.
for i, j in zip(reversed(start_indices), reversed(end_indices)):
self.my_list[i:j] = [self.my_list[i:j]]
return self
def fill_to_longest(self, my_list=None, value=None, index=None):
my_list = self.my_list if my_list is None else my_list
if not self.sublist_exists(my_list):
return self
max_length = max(len(sub_list) for sub_list in my_list if isinstance(sub_list, list))
for i, sub_list in enumerate(my_list):
if isinstance(sub_list, list):
fill_value = value if index is None else sub_list[index]
my_list[i] = sub_list + [fill_value] * (max_length-len(sub_list))
return self
def sublist_exists(self, my_list=None):
my_list = self.my_list if my_list is None else my_list
return any(isinstance(item, list) for item in my_list)
def all_sublists(self, my_list=None): # Unused method
my_list = self.my_list if my_list is None else my_list
return all(isinstance(item, list) for item in my_list)
def get_list(self): # Unused method
return self.my_list
################################################
#
# Private method from here.
#
################################################
def _search_bracket(self, string, bracket="[", replace=None):
if bracket == "[":
pattern = self.re_bracket_start
precheck = self.re_bracket_start_precheck # None
elif bracket == "]":
pattern = self.re_bracket_end
precheck = self.re_bracket_end_precheck
else:
raise ValueError(f"Invalid argument provided. (bracket: {bracket})")
if precheck and precheck.fullmatch(string):
return None if replace is None else string
elif replace is None:
return pattern.search(string)
else:
return pattern.sub(replace, string)
def _numeric_range_to_list(self, string):
match = self.re_range.fullmatch(string)
if match is not None:
if self.converter == int:
start = int(match.group(1))
end = int(match.group(2)) + 1
step = int(match.group(3)) if match.group(3) is not None else 1
return list(range(start, end, step))
else: # float
start = float(match.group(1))
end = float(match.group(2))
step = float(match.group(3)) if match.group(3) is not None else 1
return np.arange(start, end + step, step).tolist()
match = self.re_count.fullmatch(string)
if match is not None:
if self.converter == int:
start = int(match.group(1))
end = int(match.group(2))
num = int(match.group(3)) if match.group(3) is not None else 1
return [int(x) for x in np.linspace(start=start, stop=end, num=num).tolist()]
else: # float
start = float(match.group(1))
end = float(match.group(2))
num = int(match.group(3)) if match.group(3) is not None else 1
return np.linspace(start=start, stop=end, num=num).tolist()
return string
def _transpose(self, my_list=None):
my_list = self.my_list if my_list is None else my_list
my_list = [item if isinstance(item, list) else [item] for item in my_list]
self.fill_to_longest(my_list, index=-1)
return np.array(my_list, dtype=object).T.tolist()
################################################
#
# The methods of ListParser class end here.
#
################################################
################################################################
################################################################
#
# Starting the main process of this module.
#
# functions are executed in this order:
# find_module
# add_axis_options
# identity
# enable_script_control
# apply_field
# confirm
# bool_
# choices_for
# make_excluded_list
# config lists for AxisOptions:
# validation_data
# extra_axis_options
################################################################
################################################################
def find_module(module_names):
if isinstance(module_names, str):
module_names = [s.strip() for s in module_names.split(",")]
for data in scripts.scripts_data:
if data.script_class.__module__ in module_names and hasattr(data, "module"):
return data.module
return None
def add_axis_options(xyz_grid):
################################################
#
# Define a function to pass to the AxisOption class from here.
#
################################################
################################################
# Set this function as the type attribute of the AxisOption class.
# To skip the following processing of xyz_grid module.
# -> valslist = [opt.type(x) for x in valslist]
# Perform type conversion using the function
# set to the confirm attribute instead.
#
def identity(x):
return x
def enable_script_control():
shared.opts.data["control_net_allow_script_control"] = True
def apply_field(field):
@debug_info
def apply_field_(p, x, xs):
enable_script_control()
setattr(p, field, x)
return apply_field_
################################################
# The confirm function defined in this module
# enables list notation and performs type conversion.
#
# Example:
# any = [any, any, any, ...]
# [any] = [any, None, None, ...]
# [None, None, any] = [None, None, any]
# [,,any] = [None, None, any]
# any, [,any,] = [any, any, any, ...], [None, any, None]
#
# Enabled Only:
# any = [any] = [any, None, None, ...]
# (any and [any] are considered equivalent)
#
def confirm(func_or_str):
@debug_info
def confirm_(p, xs):
if callable(func_or_str): # func_or_str is converter
ListParser(xs, func_or_str, allow_blank=True)
return
elif isinstance(func_or_str, str): # func_or_str is keyword
valid_data = find_dict(validation_data, func_or_str, stop=True)
converter = valid_data["type"]
exclude_list = valid_data["exclude"]() if valid_data["exclude"] else None
check_list = valid_data["check"]()
ListParser(xs, converter, allow_blank=True, exclude_list=exclude_list)
is_all_included(xs, check_list, allow_blank=True, stop=True)
return
else:
raise TypeError(f"Argument must be callable or str, not {type(func_or_str).__name__}.")
return confirm_
def bool_(string):
string = str(string)
if string in ["None", ""]:
return None
elif string.lower() in ["true", "1"]:
return True
elif string.lower() in ["false", "0"]:
return False
else:
raise ValueError(f"Could not convert string to boolean: {string}")
def choices_bool():
return ["False", "True"]
def choices_model():
update_cn_models()
return list(cn_models_names.values())
def choices_control_mode():
return [e.value for e in ControlMode]
def choices_resize_mode():
return [e.value for e in ResizeMode]
def choices_preprocessor():
return list(cn_preprocessor_modules)
def make_excluded_list():
pattern = re.compile(r"\[(\w+)\]")
return [match.group(1) for s in choices_model()
for match in pattern.finditer(s)]
validation_data = [
{"name": "model", "type": str, "check": choices_model, "exclude": make_excluded_list},
{"name": "control_mode", "type": str, "check": choices_control_mode, "exclude": None},
{"name": "resize_mode", "type": str, "check": choices_resize_mode, "exclude": None},
{"name": "preprocessor", "type": str, "check": choices_preprocessor, "exclude": None},
]
extra_axis_options = [
xyz_grid.AxisOption("[ControlNet] Enabled", identity, apply_field("control_net_enabled"), confirm=confirm(bool_), choices=choices_bool),
xyz_grid.AxisOption("[ControlNet] Model", identity, apply_field("control_net_model"), confirm=confirm("model"), choices=choices_model, cost=0.9),
xyz_grid.AxisOption("[ControlNet] Weight", identity, apply_field("control_net_weight"), confirm=confirm(float)),
xyz_grid.AxisOption("[ControlNet] Guidance Start", identity, apply_field("control_net_guidance_start"), confirm=confirm(float)),
xyz_grid.AxisOption("[ControlNet] Guidance End", identity, apply_field("control_net_guidance_end"), confirm=confirm(float)),
xyz_grid.AxisOption("[ControlNet] Control Mode", identity, apply_field("control_net_control_mode"), confirm=confirm("control_mode"), choices=choices_control_mode),
xyz_grid.AxisOption("[ControlNet] Resize Mode", identity, apply_field("control_net_resize_mode"), confirm=confirm("resize_mode"), choices=choices_resize_mode),
xyz_grid.AxisOption("[ControlNet] Preprocessor", identity, apply_field("control_net_module"), confirm=confirm("preprocessor"), choices=choices_preprocessor),
xyz_grid.AxisOption("[ControlNet] Pre Resolution", identity, apply_field("control_net_pres"), confirm=confirm(int)),
xyz_grid.AxisOption("[ControlNet] Pre Threshold A", identity, apply_field("control_net_pthr_a"), confirm=confirm(float)),
xyz_grid.AxisOption("[ControlNet] Pre Threshold B", identity, apply_field("control_net_pthr_b"), confirm=confirm(float)),
]
xyz_grid.axis_options.extend(extra_axis_options)
def run():
xyz_grid = find_module("xyz_grid.py, xy_grid.py")
if xyz_grid:
add_axis_options(xyz_grid)
if not import_error:
run()
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