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import os
import threading
from modules.paths import script_path
import torch
import numpy as np
from omegaconf import OmegaConf
from PIL import Image
import signal
from ldm.util import instantiate_from_config
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
import modules.ui
from modules.ui import plaintext_to_html
import modules.scripts
import modules.processing as processing
import modules.sd_hijack
import modules.gfpgan_model as gfpgan
import modules.realesrgan_model as realesrgan
import modules.esrgan_model as esrgan
import modules.images as images
import modules.lowvram
import modules.txt2img
import modules.img2img
esrgan.load_models(cmd_opts.esrgan_models_path)
realesrgan.setup_realesrgan()
gfpgan.setup_gfpgan()
def load_model_from_config(config, ckpt, verbose=False):
print(f"Loading model from {ckpt}")
pl_sd = torch.load(ckpt, map_location="cpu")
if "global_step" in pl_sd:
print(f"Global Step: {pl_sd['global_step']}")
sd = pl_sd["state_dict"]
model = instantiate_from_config(config.model)
m, u = model.load_state_dict(sd, strict=False)
if len(m) > 0 and verbose:
print("missing keys:")
print(m)
if len(u) > 0 and verbose:
print("unexpected keys:")
print(u)
model.eval()
return model
cached_images = {}
def run_extras(image, gfpgan_strength, upscaling_resize, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility):
processing.torch_gc()
image = image.convert("RGB")
outpath = opts.outdir_samples or opts.outdir_extras_samples
if gfpgan.have_gfpgan is not None and gfpgan_strength > 0:
restored_img = gfpgan.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
res = Image.fromarray(restored_img)
if gfpgan_strength < 1.0:
res = Image.blend(image, res, gfpgan_strength)
image = res
if upscaling_resize != 1.0:
def upscale(image, scaler_index, resize):
small = image.crop((image.width // 2, image.height // 2, image.width // 2 + 10, image.height // 2 + 10))
pixels = tuple(np.array(small).flatten().tolist())
key = (resize, scaler_index, image.width, image.height) + pixels
c = cached_images.get(key)
if c is None:
upscaler = shared.sd_upscalers[scaler_index]
c = upscaler.upscale(image, image.width * resize, image.height * resize)
cached_images[key] = c
return c
res = upscale(image, extras_upscaler_1, upscaling_resize)
if extras_upscaler_2 != 0 and extras_upscaler_2_visibility>0:
res2 = upscale(image, extras_upscaler_2, upscaling_resize)
res = Image.blend(res, res2, extras_upscaler_2_visibility)
image = res
while len(cached_images) > 2:
del cached_images[next(iter(cached_images.keys()))]
images.save_image(image, outpath, "", None, '', opts.samples_format, short_filename=True, no_prompt=True)
return image, '', ''
def run_pnginfo(image):
info = ''
for key, text in image.info.items():
info += f"""
<div>
<p><b>{plaintext_to_html(str(key))}</b></p>
<p>{plaintext_to_html(str(text))}</p>
</div>
""".strip()+"\n"
if len(info) == 0:
message = "Nothing found in the image."
info = f"<div><p>{message}<p></div>"
return '', '', info
queue_lock = threading.Lock()
def wrap_gradio_gpu_call(func):
def f(*args, **kwargs):
shared.state.sampling_step = 0
shared.state.job_count = -1
shared.state.job_no = 0
with queue_lock:
res = func(*args, **kwargs)
shared.state.job = ""
shared.state.job_count = 0
return res
return modules.ui.wrap_gradio_call(f)
try:
# this silences the annoying "Some weights of the model checkpoint were not used when initializing..." message at start.
from transformers import logging
logging.set_verbosity_error()
except Exception:
pass
sd_config = OmegaConf.load(cmd_opts.config)
shared.sd_model = load_model_from_config(sd_config, cmd_opts.ckpt)
shared.sd_model = (shared.sd_model if cmd_opts.no_half else shared.sd_model.half())
if cmd_opts.lowvram or cmd_opts.medvram:
modules.lowvram.setup_for_low_vram(shared.sd_model, cmd_opts.medvram)
else:
shared.sd_model = shared.sd_model.to(shared.device)
modules.sd_hijack.model_hijack.hijack(shared.sd_model)
modules.scripts.load_scripts(os.path.join(script_path, "scripts"))
if __name__ == "__main__":
# make the program just exit at ctrl+c without waiting for anything
def sigint_handler(sig, frame):
print(f'Interrupted with singal {sig} in {frame}')
os._exit(0)
signal.signal(signal.SIGINT, sigint_handler)
demo = modules.ui.create_ui(
txt2img=wrap_gradio_gpu_call(modules.txt2img.txt2img),
img2img=wrap_gradio_gpu_call(modules.img2img.img2img),
run_extras=wrap_gradio_gpu_call(run_extras),
run_pnginfo=run_pnginfo
)
demo.launch(share=cmd_opts.share, server_name="0.0.0.0" if cmd_opts.listen else None)
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