157 lines
4.4 KiB
Python
157 lines
4.4 KiB
Python
import os
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import threading
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import time
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import importlib
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import signal
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import threading
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from fastapi import FastAPI
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from fastapi.middleware.gzip import GZipMiddleware
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from modules.paths import script_path
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from modules import devices, sd_samplers, upscaler
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import modules.codeformer_model as codeformer
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import modules.extras
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import modules.face_restoration
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import modules.gfpgan_model as gfpgan
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import modules.img2img
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import modules.lowvram
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import modules.paths
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import modules.scripts
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import modules.sd_hijack
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import modules.sd_models
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import modules.shared as shared
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import modules.txt2img
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import modules.ui
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from modules import devices
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from modules import modelloader
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from modules.paths import script_path
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from modules.shared import cmd_opts
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import modules.hypernetworks.hypernetwork
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queue_lock = threading.Lock()
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def wrap_queued_call(func):
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def f(*args, **kwargs):
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with queue_lock:
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res = func(*args, **kwargs)
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return res
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return f
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def wrap_gradio_gpu_call(func, extra_outputs=None):
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def f(*args, **kwargs):
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shared.state.begin()
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with queue_lock:
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res = func(*args, **kwargs)
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shared.state.end()
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return res
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return modules.ui.wrap_gradio_call(f, extra_outputs=extra_outputs)
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def initialize():
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if cmd_opts.ui_debug_mode:
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shared.sd_upscalers = upscaler.UpscalerLanczos().scalers
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modules.scripts.load_scripts()
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return
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modelloader.cleanup_models()
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modules.sd_models.setup_model()
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codeformer.setup_model(cmd_opts.codeformer_models_path)
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gfpgan.setup_model(cmd_opts.gfpgan_models_path)
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shared.face_restorers.append(modules.face_restoration.FaceRestoration())
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modelloader.load_upscalers()
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modules.scripts.load_scripts()
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modules.sd_models.load_model()
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shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
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shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
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shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)
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# make the program just exit at ctrl+c without waiting for anything
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def sigint_handler(sig, frame):
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print(f'Interrupted with signal {sig} in {frame}')
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os._exit(0)
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signal.signal(signal.SIGINT, sigint_handler)
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def create_api(app):
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from modules.api.api import Api
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api = Api(app, queue_lock)
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return api
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def wait_on_server(demo=None):
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while 1:
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time.sleep(0.5)
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if demo and getattr(demo, 'do_restart', False):
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time.sleep(0.5)
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demo.close()
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time.sleep(0.5)
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break
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def api_only():
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initialize()
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app = FastAPI()
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app.add_middleware(GZipMiddleware, minimum_size=1000)
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api = create_api(app)
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api.launch(server_name="0.0.0.0" if cmd_opts.listen else "127.0.0.1", port=cmd_opts.port if cmd_opts.port else 7861)
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def webui():
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launch_api = cmd_opts.api
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initialize()
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while 1:
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demo = modules.ui.create_ui(wrap_gradio_gpu_call=wrap_gradio_gpu_call)
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app, local_url, share_url = demo.launch(
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share=cmd_opts.share,
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server_name="0.0.0.0" if cmd_opts.listen else None,
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server_port=cmd_opts.port,
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debug=cmd_opts.gradio_debug,
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auth=[tuple(cred.split(':')) for cred in cmd_opts.gradio_auth.strip('"').split(',')] if cmd_opts.gradio_auth else None,
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inbrowser=cmd_opts.autolaunch,
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prevent_thread_lock=True
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)
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# after initial launch, disable --autolaunch for subsequent restarts
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cmd_opts.autolaunch = False
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app.add_middleware(GZipMiddleware, minimum_size=1000)
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if (launch_api):
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create_api(app)
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wait_on_server(demo)
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sd_samplers.set_samplers()
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print('Reloading Custom Scripts')
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modules.scripts.reload_scripts()
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print('Reloading modules: modules.ui')
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importlib.reload(modules.ui)
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print('Refreshing Model List')
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modules.sd_models.list_models()
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print('Restarting Gradio')
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task = []
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if __name__ == "__main__":
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if cmd_opts.nowebui:
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api_only()
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else:
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webui()
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