diff options
Diffstat (limited to 'modules/extras.py')
| -rw-r--r-- | modules/extras.py | 74 |
1 files changed, 52 insertions, 22 deletions
diff --git a/modules/extras.py b/modules/extras.py index 6021a024..6fa7d856 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -62,7 +62,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ # Also keep track of original file names
imageNameArr = []
outputs = []
-
+
if extras_mode == 1:
#convert file to pillow image
for img in image_folder:
@@ -188,13 +188,19 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ for op in extras_ops:
image, info = op(image, info)
- if opts.use_original_name_batch and image_name != None:
+ if opts.use_original_name_batch and image_name is not None:
basename = os.path.splitext(os.path.basename(image_name))[0]
else:
basename = ''
+ # Add upscaler name as a suffix.
+ suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
+ # Add second upscaler if applicable.
+ if suffix and extras_upscaler_2 and extras_upscaler_2_visibility:
+ suffix += f"-{shared.sd_upscalers[extras_upscaler_2].name}"
+
images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
- no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None)
+ no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)
if opts.enable_pnginfo:
image.info = existing_pnginfo
@@ -234,7 +240,7 @@ def run_pnginfo(image): return '', geninfo, info
-def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
+def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format):
def weighted_sum(theta0, theta1, alpha):
return ((1 - alpha) * theta0) + (alpha * theta1)
@@ -246,19 +252,8 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam primary_model_info = sd_models.checkpoints_list[primary_model_name]
secondary_model_info = sd_models.checkpoints_list[secondary_model_name]
- teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None)
-
- print(f"Loading {primary_model_info.filename}...")
- theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
-
- print(f"Loading {secondary_model_info.filename}...")
- theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
-
- if teritary_model_info is not None:
- print(f"Loading {teritary_model_info.filename}...")
- theta_2 = sd_models.read_state_dict(teritary_model_info.filename, map_location='cpu')
- else:
- theta_2 = None
+ tertiary_model_info = sd_models.checkpoints_list.get(tertiary_model_name, None)
+ result_is_inpainting_model = False
theta_funcs = {
"Weighted sum": (None, weighted_sum),
@@ -266,9 +261,16 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam }
theta_func1, theta_func2 = theta_funcs[interp_method]
- print(f"Merging...")
+ if theta_func1 and not tertiary_model_info:
+ return ["Failed: Interpolation method requires a tertiary model."] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
+
+ print(f"Loading {secondary_model_info.filename}...")
+ theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu')
if theta_func1:
+ print(f"Loading {tertiary_model_info.filename}...")
+ theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu')
+
for key in tqdm.tqdm(theta_1.keys()):
if 'model' in key:
if key in theta_2:
@@ -276,12 +278,31 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam theta_1[key] = theta_func1(theta_1[key], t2)
else:
theta_1[key] = torch.zeros_like(theta_1[key])
- del theta_2
+ del theta_2
+
+ print(f"Loading {primary_model_info.filename}...")
+ theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu')
+
+ print("Merging...")
for key in tqdm.tqdm(theta_0.keys()):
if 'model' in key and key in theta_1:
+ a = theta_0[key]
+ b = theta_1[key]
- theta_0[key] = theta_func2(theta_0[key], theta_1[key], multiplier)
+ # this enables merging an inpainting model (A) with another one (B);
+ # where normal model would have 4 channels, for latenst space, inpainting model would
+ # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9
+ if a.shape != b.shape and a.shape[0:1] + a.shape[2:] == b.shape[0:1] + b.shape[2:]:
+ if a.shape[1] == 4 and b.shape[1] == 9:
+ raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.")
+
+ assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"
+
+ theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
+ result_is_inpainting_model = True
+ else:
+ theta_0[key] = theta_func2(a, b, multiplier)
if save_as_half:
theta_0[key] = theta_0[key].half()
@@ -292,11 +313,20 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam theta_0[key] = theta_1[key]
if save_as_half:
theta_0[key] = theta_0[key].half()
+ del theta_1
ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path
- filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.' + checkpoint_format
+ filename = \
+ primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + \
+ secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + \
+ interp_method.replace(" ", "_") + \
+ '-merged.' + \
+ ("inpainting." if result_is_inpainting_model else "") + \
+ checkpoint_format
+
filename = filename if custom_name == '' else (custom_name + '.' + checkpoint_format)
+
output_modelname = os.path.join(ckpt_dir, filename)
print(f"Saving to {output_modelname}...")
@@ -309,5 +339,5 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam sd_models.list_models()
- print(f"Checkpoint saved.")
+ print("Checkpoint saved.")
return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)]
|