stable-diffusion-webui/modules/scripts.py
AUTOMATIC 91bfc71261 A big rework, just what you were secretly hoping for!
SD upscale moved to scripts
Batch processing script removed
Batch processing added to main img2img and now works with scripts
img2img page UI reworked to use tabs
2022-09-22 12:11:48 +03:00

166 lines
5.2 KiB
Python

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()