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correctly list and display model names for #1261

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AUTOMATIC
2022-09-29 00:21:54 +03:00
parent 43e273004b
commit 791808c890
2 changed files with 10 additions and 17 deletions
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23
modules/extras.py
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@@ -6,7 +6,7 @@ from PIL import Image
import torch
import tqdm
from modules import processing, shared, images, devices
from modules import processing, shared, images, devices, sd_models
from modules.shared import opts
import modules.gfpgan_model
from modules.ui import plaintext_to_html
@@ -156,17 +156,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
alpha = 0.5 - math.sin(math.asin(1.0 - 2.0 * alpha) / 3.0)
return theta0 + ((theta1 - theta0) * alpha)
if os.path.exists(primary_model_name):
primary_model_filename = primary_model_name
primary_model_name = os.path.splitext(os.path.basename(primary_model_name))[0]
else:
primary_model_filename = 'models/' + primary_model_name + '.ckpt'
if os.path.exists(secondary_model_name):
secondary_model_filename = secondary_model_name
secondary_model_name = os.path.splitext(os.path.basename(secondary_model_name))[0]
else:
secondary_model_filename = 'models/' + secondary_model_name + '.ckpt'
primary_model_filename = sd_models.checkpoints_list[primary_model_name].filename
secondary_model_filename = sd_models.checkpoints_list[secondary_model_name].filename
print(f"Loading {primary_model_filename}...")
primary_model = torch.load(primary_model_filename, map_location='cpu')
@@ -180,7 +171,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
theta_funcs = {
"Weighted Sum": weighted_sum,
"Sigmoid": sigmoid,
"Inverse Sigmoid": inv_sigmoid
"Inverse Sigmoid": inv_sigmoid,
}
theta_func = theta_funcs[interp_method]
@@ -193,9 +184,11 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int
if 'model' in key and key not in theta_0:
theta_0[key] = theta_1[key]
output_modelname = 'models/' + primary_model_name + '_' + str(round(interp_amount,2)) + '-' + secondary_model_name + '_' + str(round((float(1.0) - interp_amount),2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
filename = primary_model_name + '_' + str(round(interp_amount,2)) + '-' + secondary_model_name + '_' + str(round((float(1.0) - interp_amount),2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt'
output_modelname = os.path.join(shared.cmd_opts.ckpt_dir, filename)
print(f"Saving to {output_modelname}...")
torch.save(primary_model, output_modelname)
print(f"Checkpoint saved.")
return "Checkpoint saved to " + output_modelname
return "Checkpoint saved to " + output_modelname