disabled SD model download after multiple complaints
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@ -13,9 +13,6 @@ from modules.paths import models_path
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model_dir = "Stable-diffusion"
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model_path = os.path.abspath(os.path.join(models_path, model_dir))
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model_name = "sd-v1-4.ckpt"
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model_url = "https://drive.yerf.org/wl/?id=EBfTrmcCCUAGaQBXVIj5lJmEhjoP1tgl&mode=grid&download=1"
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user_dir = None
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CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
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checkpoints_list = {}
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@ -30,12 +27,10 @@ except Exception:
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pass
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def setup_model(dirname):
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global user_dir
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user_dir = dirname
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def setup_model():
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if not os.path.exists(model_path):
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os.makedirs(model_path)
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checkpoints_list.clear()
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list_models()
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@ -45,7 +40,7 @@ def checkpoint_tiles():
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def list_models():
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checkpoints_list.clear()
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model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=user_dir, ext_filter=[".ckpt"], download_name=model_name)
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model_list = modelloader.load_models(model_path=model_path, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt"])
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def modeltitle(path, shorthash):
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abspath = os.path.abspath(path)
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@ -106,8 +101,11 @@ def select_checkpoint():
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if len(checkpoints_list) == 0:
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print(f"No checkpoints found. When searching for checkpoints, looked at:", file=sys.stderr)
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print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
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print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
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if shared.cmd_opts.ckpt is not None:
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print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
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print(f" - directory {model_path}", file=sys.stderr)
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if shared.cmd_opts.ckpt_dir is not None:
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print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
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print(f"Can't run without a checkpoint. Find and place a .ckpt file into any of those locations. The program will exit.", file=sys.stderr)
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exit(1)
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@ -22,7 +22,7 @@ def train_embedding(*args):
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embedding, filename = ti.train_embedding(*args)
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res = f"""
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Training {'interrupted' if shared.state.interrupted else 'finished'} after {embedding.step} steps.
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Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
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Embedding saved to {html.escape(filename)}
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"""
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return res, ""
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2
webui.py
2
webui.py
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@ -23,7 +23,7 @@ from modules.paths import script_path
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from modules.shared import cmd_opts
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modelloader.cleanup_models()
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modules.sd_models.setup_model(cmd_opts.ckpt_dir)
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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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