de5bfdf917
* handles exceptions if jpeg jfif data not present * removes further non-comment related exif data.
138 lines
3.9 KiB
Python
138 lines
3.9 KiB
Python
import os
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import threading
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from modules.paths import script_path
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import torch
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from omegaconf import OmegaConf
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import signal
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from ldm.util import instantiate_from_config
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from modules.shared import opts, cmd_opts, state
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import modules.shared as shared
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import modules.ui
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import modules.scripts
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import modules.sd_hijack
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import modules.codeformer_model
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import modules.gfpgan_model
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import modules.face_restoration
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import modules.realesrgan_model as realesrgan
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import modules.esrgan_model as esrgan
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import modules.extras
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import modules.lowvram
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import modules.txt2img
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import modules.img2img
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modules.codeformer_model.setup_codeformer()
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modules.gfpgan_model.setup_gfpgan()
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shared.face_restorers.append(modules.face_restoration.FaceRestoration())
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esrgan.load_models(cmd_opts.esrgan_models_path)
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realesrgan.setup_realesrgan()
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def load_model_from_config(config, ckpt, verbose=False):
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print(f"Loading model [{shared.sd_model_hash}] from {ckpt}")
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pl_sd = torch.load(ckpt, map_location="cpu")
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if "global_step" in pl_sd:
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print(f"Global Step: {pl_sd['global_step']}")
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sd = pl_sd["state_dict"]
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model = instantiate_from_config(config.model)
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m, u = model.load_state_dict(sd, strict=False)
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if len(m) > 0 and verbose:
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print("missing keys:")
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print(m)
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if len(u) > 0 and verbose:
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print("unexpected keys:")
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print(u)
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if cmd_opts.opt_channelslast:
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model = model.to(memory_format=torch.channels_last)
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model.eval()
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return model
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queue_lock = threading.Lock()
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def wrap_gradio_gpu_call(func):
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def f(*args, **kwargs):
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shared.state.sampling_step = 0
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shared.state.job_count = -1
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shared.state.job_no = 0
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shared.state.current_latent = None
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shared.state.current_image = None
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shared.state.current_image_sampling_step = 0
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with queue_lock:
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res = func(*args, **kwargs)
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shared.state.job = ""
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shared.state.job_count = 0
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return res
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return modules.ui.wrap_gradio_call(f)
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modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
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try:
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# this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.
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from transformers import logging
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logging.set_verbosity_error()
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except Exception:
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pass
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with open(cmd_opts.ckpt, "rb") as file:
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import hashlib
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m = hashlib.sha256()
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file.seek(0x100000)
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m.update(file.read(0x10000))
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shared.sd_model_hash = m.hexdigest()[0:8]
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sd_config = OmegaConf.load(cmd_opts.config)
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shared.sd_model = load_model_from_config(sd_config, cmd_opts.ckpt)
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shared.sd_model = (shared.sd_model if cmd_opts.no_half else shared.sd_model.half())
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if cmd_opts.lowvram or cmd_opts.medvram:
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modules.lowvram.setup_for_low_vram(shared.sd_model, cmd_opts.medvram)
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else:
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shared.sd_model = shared.sd_model.to(shared.device)
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modules.sd_hijack.model_hijack.hijack(shared.sd_model)
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def webui():
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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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demo = modules.ui.create_ui(
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txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
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img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
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run_extras=wrap_gradio_gpu_call(modules.extras.run_extras),
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run_image_info=modules.extras.run_image_info
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)
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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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)
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if __name__ == "__main__":
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webui()
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