Commit a1cde7e6 authored by AUTOMATIC's avatar AUTOMATIC

disabled SD model download after multiple complaints

parent 3ff0de2c
......@@ -13,9 +13,6 @@ from modules.paths import models_path
model_dir = "Stable-diffusion"
model_path = os.path.abspath(os.path.join(models_path, model_dir))
model_name = "sd-v1-4.ckpt"
model_url = "https://drive.yerf.org/wl/?id=EBfTrmcCCUAGaQBXVIj5lJmEhjoP1tgl&mode=grid&download=1"
user_dir = None
CheckpointInfo = namedtuple("CheckpointInfo", ['filename', 'title', 'hash', 'model_name'])
checkpoints_list = {}
......@@ -30,12 +27,10 @@ except Exception:
pass
def setup_model(dirname):
global user_dir
user_dir = dirname
def setup_model():
if not os.path.exists(model_path):
os.makedirs(model_path)
checkpoints_list.clear()
list_models()
......@@ -45,7 +40,7 @@ def checkpoint_tiles():
def list_models():
checkpoints_list.clear()
model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=user_dir, ext_filter=[".ckpt"], download_name=model_name)
model_list = modelloader.load_models(model_path=model_path, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt"])
def modeltitle(path, shorthash):
abspath = os.path.abspath(path)
......@@ -106,8 +101,11 @@ def select_checkpoint():
if len(checkpoints_list) == 0:
print(f"No checkpoints found. When searching for checkpoints, looked at:", file=sys.stderr)
print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
if shared.cmd_opts.ckpt is not None:
print(f" - file {os.path.abspath(shared.cmd_opts.ckpt)}", file=sys.stderr)
print(f" - directory {model_path}", file=sys.stderr)
if shared.cmd_opts.ckpt_dir is not None:
print(f" - directory {os.path.abspath(shared.cmd_opts.ckpt_dir)}", file=sys.stderr)
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)
exit(1)
......
......@@ -22,7 +22,7 @@ def train_embedding(*args):
embedding, filename = ti.train_embedding(*args)
res = f"""
Training {'interrupted' if shared.state.interrupted else 'finished'} after {embedding.step} steps.
Training {'interrupted' if shared.state.interrupted else 'finished'} at {embedding.step} steps.
Embedding saved to {html.escape(filename)}
"""
return res, ""
......
......@@ -23,7 +23,7 @@ from modules.paths import script_path
from modules.shared import cmd_opts
modelloader.cleanup_models()
modules.sd_models.setup_model(cmd_opts.ckpt_dir)
modules.sd_models.setup_model()
codeformer.setup_model(cmd_opts.codeformer_models_path)
gfpgan.setup_model(cmd_opts.gfpgan_models_path)
shared.face_restorers.append(modules.face_restoration.FaceRestoration())
......
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