mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2025-08-04 11:12:35 +00:00
added detailed installation instructions
fixed bug with missing same dir for a new install added ctrl+c hander to immediately stop the program instead of waiting
This commit is contained in:
68
webui.py
68
webui.py
@@ -1,8 +1,18 @@
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import argparse
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import os
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import sys
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from collections import namedtuple
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from contextlib import nullcontext
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script_path = os.path.dirname(os.path.realpath(__file__))
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sd_path = os.path.dirname(script_path)
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# add parent directory to path; this is where Stable diffusion repo should be
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path_dirs = [(sd_path, 'ldm', 'Stable Diffusion'), ('../../taming-transformers', 'taming', 'Taming Transformers')]
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for d, must_exist, what in path_dirs:
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must_exist_path = os.path.abspath(os.path.join(script_path, d, must_exist))
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if not os.path.exists(must_exist_path):
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print(f"Warning: {what} not found at path {must_exist_path}", file=sys.stderr)
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else:
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sys.path.append(os.path.join(script_path, d))
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import torch
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import torch.nn as nn
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@@ -19,6 +29,9 @@ import html
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import time
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import json
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import traceback
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from collections import namedtuple
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from contextlib import nullcontext
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import signal
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import k_diffusion.sampling
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from ldm.util import instantiate_from_config
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@@ -33,7 +46,6 @@ gradio.utils.get_local_ip_address = lambda: '127.0.0.1'
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mimetypes.init()
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mimetypes.add_type('application/javascript', '.js')
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script_path = os.path.dirname(os.path.realpath(__file__))
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# some of those options should not be changed at all because they would break the model, so I removed them from options.
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opt_C = 4
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@@ -44,9 +56,10 @@ invalid_filename_chars = '<>:"/\\|?*\n'
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config_filename = "config.json"
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parser = argparse.ArgumentParser()
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parser.add_argument("--config", type=str, default="configs/stable-diffusion/v1-inference.yaml", help="path to config which constructs model",)
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parser.add_argument("--ckpt", type=str, default="models/ldm/stable-diffusion-v1/model.ckpt", help="path to checkpoint of model",)
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parser.add_argument("--config", type=str, default=os.path.join(sd_path, "configs/stable-diffusion/v1-inference.yaml"), help="path to config which constructs model",)
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parser.add_argument("--ckpt", type=str, default=os.path.join(sd_path, "models/ldm/stable-diffusion-v1/model.ckpt"), help="path to checkpoint of model",)
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parser.add_argument("--gfpgan-dir", type=str, help="GFPGAN directory", default=('./src/gfpgan' if os.path.exists('./src/gfpgan') else './GFPGAN'))
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parser.add_argument("--gfpgan-model", type=str, help="GFPGAN model file name", default='GFPGANv1.3.pth')
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parser.add_argument("--no-half", action='store_true', help="do not switch the model to 16-bit floats")
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parser.add_argument("--no-progressbar-hiding", action='store_true', help="do not hide progressbar in gradio UI (we hide it because it slows down ML if you have hardware accleration in browser)")
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parser.add_argument("--max-batch-count", type=int, default=16, help="maximum batch count value for the UI")
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@@ -122,25 +135,34 @@ sd_upscalers = {
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}
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have_gfpgan = False
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if os.path.exists(cmd_opts.gfpgan_dir):
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try:
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sys.path.append(os.path.abspath(cmd_opts.gfpgan_dir))
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from gfpgan import GFPGANer
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def gfpgan_model_path():
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places = [script_path, '.', os.path.join(cmd_opts.gfpgan_dir, 'experiments/pretrained_models')]
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files = [cmd_opts.gfpgan_model] + [os.path.join(dirname, cmd_opts.gfpgan_model) for dirname in places]
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found = [x for x in files if os.path.exists(x)]
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have_gfpgan = True
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except:
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print("Error importing GFPGAN:", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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if len(found) == 0:
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raise Exception("GFPGAN model not found in paths: " + ", ".join(files))
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return found[0]
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def gfpgan():
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model_name = 'GFPGANv1.3'
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model_path = os.path.join(cmd_opts.gfpgan_dir, 'experiments/pretrained_models', model_name + '.pth')
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if not os.path.isfile(model_path):
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raise Exception("GFPGAN model not found at path "+model_path)
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return GFPGANer(model_path=gfpgan_model_path(), upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
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have_gfpgan = False
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try:
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model_path = gfpgan_model_path()
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if os.path.exists(cmd_opts.gfpgan_dir):
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sys.path.append(os.path.abspath(cmd_opts.gfpgan_dir))
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from gfpgan import GFPGANer
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have_gfpgan = True
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except Exception:
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print("Error setting up GFPGAN:", file=sys.stderr)
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print(traceback.format_exc(), file=sys.stderr)
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return GFPGANer(model_path=model_path, upscale=1, arch='clean', channel_multiplier=2, bg_upsampler=None)
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class Options:
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@@ -865,6 +887,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
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seed = int(random.randrange(4294967294) if p.seed == -1 else p.seed)
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sample_path = os.path.join(p.outpath, "samples")
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os.makedirs(sample_path, exist_ok=True)
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base_count = len(os.listdir(sample_path))
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grid_count = len(os.listdir(p.outpath)) - 1
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@@ -1669,5 +1692,12 @@ demo = gr.TabbedInterface(
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analytics_enabled=False,
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)
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# make the program just exit at ctrl+c without waiting for anything
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def sigint_handler(signal, frame):
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print('Interrupted')
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os._exit(0)
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signal.signal(signal.SIGINT, sigint_handler)
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demo.queue(concurrency_count=1)
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demo.launch()
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