import os import sys import traceback import modules.ui as ui import gradio as gr from modules.processing import StableDiffusionProcessing from modules import shared class Script: filename = None args_from = None args_to = None # The title of the script. This is what will be displayed in the dropdown menu. def title(self): raise NotImplementedError() # How the script is displayed in the UI. See https://gradio.app/docs/#components # for the different UI components you can use and how to create them. # Most UI components can return a value, such as a boolean for a checkbox. # The returned values are passed to the run method as parameters. def ui(self, is_img2img): pass # Determines when the script should be shown in the dropdown menu via the # returned value. As an example: # is_img2img is True if the current tab is img2img, and False if it is txt2img. # Thus, return is_img2img to only show the script on the img2img tab. def show(self, is_img2img): return True # This is where the additional processing is implemented. The parameters include # self, the model object "p" (a StableDiffusionProcessing class, see # processing.py), and the parameters returned by the ui method. # Custom functions can be defined here, and additional libraries can be imported # to be used in processing. The return value should be a Processed object, which is # what is returned by the process_images method. def run(self, *args): raise NotImplementedError() # The description method is currently unused. # To add a description that appears when hovering over the title, amend the "titles" # dict in script.js to include the script title (returned by title) as a key, and # your description as the value. def describe(self): return "" scripts_data = [] def load_scripts(basedir): if not os.path.exists(basedir): return for filename in os.listdir(basedir): path = os.path.join(basedir, filename) if not os.path.isfile(path): continue try: with open(path, "r", encoding="utf8") as file: text = file.read() from types import ModuleType compiled = compile(text, path, 'exec') module = ModuleType(filename) exec(compiled, module.__dict__) for key, script_class in module.__dict__.items(): if type(script_class) == type and issubclass(script_class, Script): scripts_data.append((script_class, path)) except Exception: print(f"Error loading script: {filename}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) def wrap_call(func, filename, funcname, *args, default=None, **kwargs): try: res = func(*args, **kwargs) return res except Exception: print(f"Error calling: {filename}/{funcname}", file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) return default class ScriptRunner: def __init__(self): self.scripts = [] def setup_ui(self, is_img2img): for script_class, path in scripts_data: script = script_class() script.filename = path if not script.show(is_img2img): continue self.scripts.append(script) titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.scripts] dropdown = gr.Dropdown(label="Script", choices=["None"] + titles, value="None", type="index") inputs = [dropdown] for script in self.scripts: script.args_from = len(inputs) script.args_to = len(inputs) controls = wrap_call(script.ui, script.filename, "ui", is_img2img) if controls is None: continue for control in controls: control.visible = False inputs += controls script.args_to = len(inputs) def select_script(script_index): if 0 < script_index <= len(self.scripts): script = self.scripts[script_index-1] args_from = script.args_from args_to = script.args_to else: args_from = 0 args_to = 0 return [ui.gr_show(True if i == 0 else args_from <= i < args_to) for i in range(len(inputs))] dropdown.change( fn=select_script, inputs=[dropdown], outputs=inputs ) return inputs def run(self, p: StableDiffusionProcessing, *args): script_index = args[0] if script_index == 0: return None script = self.scripts[script_index-1] if script is None: return None script_args = args[script.args_from:script.args_to] processed = script.run(p, *script_args) shared.total_tqdm.clear() return processed scripts_txt2img = ScriptRunner() scripts_img2img = ScriptRunner()