mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2024-12-09 07:10:16 +08:00
153 lines
4.4 KiB
Python
153 lines
4.4 KiB
Python
import os
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import gradio as gr
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from modules import errors, shared
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class PostprocessedImage:
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def __init__(self, image):
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self.image = image
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self.info = {}
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class ScriptPostprocessing:
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filename = None
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controls = None
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args_from = None
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args_to = None
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order = 1000
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"""scripts will be ordred by this value in postprocessing UI"""
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name = None
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"""this function should return the title of the script."""
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group = None
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"""A gr.Group component that has all script's UI inside it"""
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def ui(self):
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"""
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This function should create gradio UI elements. See https://gradio.app/docs/#components
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The return value should be a dictionary that maps parameter names to components used in processing.
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Values of those components will be passed to process() function.
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"""
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pass
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def process(self, pp: PostprocessedImage, **args):
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"""
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This function is called to postprocess the image.
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args contains a dictionary with all values returned by components from ui()
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"""
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pass
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def image_changed(self):
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pass
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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 as e:
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errors.display(e, f"calling {filename}/{funcname}")
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return default
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class ScriptPostprocessingRunner:
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def __init__(self):
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self.scripts = None
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self.ui_created = False
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def initialize_scripts(self, scripts_data):
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self.scripts = []
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for script_class, path, basedir, script_module in scripts_data:
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script: ScriptPostprocessing = script_class()
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script.filename = path
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if script.name == "Simple Upscale":
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continue
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self.scripts.append(script)
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def create_script_ui(self, script, inputs):
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script.args_from = len(inputs)
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script.args_to = len(inputs)
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script.controls = wrap_call(script.ui, script.filename, "ui")
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for control in script.controls.values():
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control.custom_script_source = os.path.basename(script.filename)
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inputs += list(script.controls.values())
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script.args_to = len(inputs)
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def scripts_in_preferred_order(self):
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if self.scripts is None:
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import modules.scripts
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self.initialize_scripts(modules.scripts.postprocessing_scripts_data)
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scripts_order = shared.opts.postprocessing_operation_order
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def script_score(name):
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for i, possible_match in enumerate(scripts_order):
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if possible_match == name:
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return i
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return len(self.scripts)
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script_scores = {script.name: (script_score(script.name), script.order, script.name, original_index) for original_index, script in enumerate(self.scripts)}
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return sorted(self.scripts, key=lambda x: script_scores[x.name])
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def setup_ui(self):
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inputs = []
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for script in self.scripts_in_preferred_order():
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with gr.Row() as group:
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self.create_script_ui(script, inputs)
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script.group = group
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self.ui_created = True
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return inputs
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def run(self, pp: PostprocessedImage, args):
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for script in self.scripts_in_preferred_order():
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shared.state.job = script.name
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script_args = args[script.args_from:script.args_to]
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process_args = {}
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for (name, component), value in zip(script.controls.items(), script_args):
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process_args[name] = value
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script.process(pp, **process_args)
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def create_args_for_run(self, scripts_args):
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if not self.ui_created:
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with gr.Blocks(analytics_enabled=False):
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self.setup_ui()
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scripts = self.scripts_in_preferred_order()
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args = [None] * max([x.args_to for x in scripts])
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for script in scripts:
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script_args_dict = scripts_args.get(script.name, None)
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if script_args_dict is not None:
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for i, name in enumerate(script.controls):
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args[script.args_from + i] = script_args_dict.get(name, None)
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return args
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def image_changed(self):
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for script in self.scripts_in_preferred_order():
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script.image_changed()
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