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