diff options
Diffstat (limited to 'scripts')
| -rw-r--r-- | scripts/prompts_from_file.py | 4 | ||||
| -rw-r--r-- | scripts/xy_grid.py | 59 |
2 files changed, 47 insertions, 16 deletions
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 513d9a1c..b24f1a80 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -10,7 +10,6 @@ from modules.processing import Processed, process_images from PIL import Image
from modules.shared import opts, cmd_opts, state
-
class Script(scripts.Script):
def title(self):
return "Prompts from file or textbox"
@@ -29,6 +28,9 @@ class Script(scripts.Script): checkbox_txt.change(fn=lambda x: [gr.File.update(visible = not x), gr.TextArea.update(visible = x)], inputs=[checkbox_txt], outputs=[file, prompt_txt])
return [checkbox_txt, file, prompt_txt]
+ def on_show(self, checkbox_txt, file, prompt_txt):
+ return [ gr.Checkbox.update(visible = True), gr.File.update(visible = not checkbox_txt), gr.TextArea.update(visible = checkbox_txt) ]
+
def run(self, p, checkbox_txt, data: bytes, prompt_txt: str):
if (checkbox_txt):
lines = [x.strip() for x in prompt_txt.splitlines()]
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 6344e612..771eb8e4 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -10,8 +10,8 @@ import numpy as np import modules.scripts as scripts
import gradio as gr
-from modules import images
-from modules.processing import process_images, Processed
+from modules import images, hypernetwork
+from modules.processing import process_images, Processed, get_correct_sampler
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
import modules.sd_samplers
@@ -56,15 +56,17 @@ def apply_order(p, x, xs): p.prompt = prompt_tmp + p.prompt
-samplers_dict = {}
-for i, sampler in enumerate(modules.sd_samplers.samplers):
- samplers_dict[sampler.name.lower()] = i
- for alias in sampler.aliases:
- samplers_dict[alias.lower()] = i
+def build_samplers_dict(p):
+ samplers_dict = {}
+ for i, sampler in enumerate(get_correct_sampler(p)):
+ samplers_dict[sampler.name.lower()] = i
+ for alias in sampler.aliases:
+ samplers_dict[alias.lower()] = i
+ return samplers_dict
def apply_sampler(p, x, xs):
- sampler_index = samplers_dict.get(x.lower(), None)
+ sampler_index = build_samplers_dict(p).get(x.lower(), None)
if sampler_index is None:
raise RuntimeError(f"Unknown sampler: {x}")
@@ -77,6 +79,14 @@ def apply_checkpoint(p, x, xs): modules.sd_models.reload_model_weights(shared.sd_model, info)
+def apply_hypernetwork(p, x, xs):
+ hypernetwork.load_hypernetwork(x)
+
+
+def apply_clip_skip(p, x, xs):
+ opts.data["CLIP_stop_at_last_layers"] = x
+
+
def format_value_add_label(p, opt, x):
if type(x) == float:
x = round(x, 8)
@@ -122,11 +132,13 @@ axis_options = [ AxisOption("Prompt order", str_permutations, apply_order, format_value_join_list),
AxisOption("Sampler", str, apply_sampler, format_value),
AxisOption("Checkpoint name", str, apply_checkpoint, format_value),
+ AxisOption("Hypernetwork", str, apply_hypernetwork, format_value),
AxisOption("Sigma Churn", float, apply_field("s_churn"), format_value_add_label),
AxisOption("Sigma min", float, apply_field("s_tmin"), format_value_add_label),
AxisOption("Sigma max", float, apply_field("s_tmax"), format_value_add_label),
AxisOption("Sigma noise", float, apply_field("s_noise"), format_value_add_label),
AxisOption("Eta", float, apply_field("eta"), format_value_add_label),
+ AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label),
AxisOptionImg2Img("Denoising", float, apply_field("denoising_strength"), format_value_add_label), # as it is now all AxisOptionImg2Img items must go after AxisOption ones
]
@@ -137,7 +149,7 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend): ver_texts = [[images.GridAnnotation(y)] for y in y_labels]
hor_texts = [[images.GridAnnotation(x)] for x in x_labels]
- first_pocessed = None
+ first_processed = None
state.job_count = len(xs) * len(ys) * p.n_iter
@@ -146,8 +158,8 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend): state.job = f"{ix + iy * len(xs) + 1} out of {len(xs) * len(ys)}"
processed = cell(x, y)
- if first_pocessed is None:
- first_pocessed = processed
+ if first_processed is None:
+ first_processed = processed
try:
res.append(processed.images[0])
@@ -158,9 +170,9 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend): if draw_legend:
grid = images.draw_grid_annotations(grid, res[0].width, res[0].height, hor_texts, ver_texts)
- first_pocessed.images = [grid]
+ first_processed.images = [grid]
- return first_pocessed
+ return first_processed
re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
@@ -190,8 +202,11 @@ class Script(scripts.Script): return [x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds]
def run(self, p, x_type, x_values, y_type, y_values, draw_legend, no_fixed_seeds):
- modules.processing.fix_seed(p)
+ if not no_fixed_seeds:
+ modules.processing.fix_seed(p)
+
p.batch_size = 1
+ CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
def process_axis(opt, vals):
if opt.label == 'Nothing':
@@ -206,7 +221,6 @@ class Script(scripts.Script): m = re_range.fullmatch(val)
mc = re_range_count.fullmatch(val)
if m is not None:
-
start = int(m.group(1))
end = int(m.group(2))+1
step = int(m.group(3)) if m.group(3) is not None else 1
@@ -248,6 +262,17 @@ class Script(scripts.Script): valslist = list(permutations(valslist))
valslist = [opt.type(x) for x in valslist]
+
+ # Confirm options are valid before starting
+ if opt.label == "Sampler":
+ samplers_dict = build_samplers_dict(p)
+ for sampler_val in valslist:
+ if sampler_val.lower() not in samplers_dict.keys():
+ raise RuntimeError(f"Unknown sampler: {sampler_val}")
+ elif opt.label == "Checkpoint name":
+ for ckpt_val in valslist:
+ if modules.sd_models.get_closet_checkpoint_match(ckpt_val) is None:
+ raise RuntimeError(f"Checkpoint for {ckpt_val} not found")
return valslist
@@ -300,4 +325,8 @@ class Script(scripts.Script): # restore checkpoint in case it was changed by axes
modules.sd_models.reload_model_weights(shared.sd_model)
+ hypernetwork.load_hypernetwork(opts.sd_hypernetwork)
+
+ opts.data["CLIP_stop_at_last_layers"] = CLIP_stop_at_last_layers
+
return processed
|