diff options
Diffstat (limited to 'scripts')
| -rw-r--r-- | scripts/custom_code.py | 2 | ||||
| -rw-r--r-- | scripts/img2imgalt.py | 7 | ||||
| -rw-r--r-- | scripts/outpainting_mk_2.py | 2 | ||||
| -rw-r--r-- | scripts/poor_mans_outpainting.py | 4 | ||||
| -rw-r--r-- | scripts/prompt_matrix.py | 21 | ||||
| -rw-r--r-- | scripts/prompts_from_file.py | 41 | ||||
| -rw-r--r-- | scripts/sd_upscale.py | 20 | ||||
| -rw-r--r-- | scripts/xy_grid.py | 72 |
8 files changed, 112 insertions, 57 deletions
diff --git a/scripts/custom_code.py b/scripts/custom_code.py index a9b10c09..22e7b77a 100644 --- a/scripts/custom_code.py +++ b/scripts/custom_code.py @@ -14,7 +14,7 @@ class Script(scripts.Script): return cmd_opts.allow_code
def ui(self, is_img2img):
- code = gr.Textbox(label="Python code", visible=False, lines=1)
+ code = gr.Textbox(label="Python code", lines=1)
return [code]
diff --git a/scripts/img2imgalt.py b/scripts/img2imgalt.py index 88abc093..1229f61b 100644 --- a/scripts/img2imgalt.py +++ b/scripts/img2imgalt.py @@ -157,7 +157,7 @@ class Script(scripts.Script): def run(self, p, _, override_sampler, override_prompt, original_prompt, original_negative_prompt, override_steps, st, override_strength, cfg, randomness, sigma_adjustment):
# Override
if override_sampler:
- p.sampler_index = [sampler.name for sampler in sd_samplers.samplers].index("Euler")
+ p.sampler_name = "Euler"
if override_prompt:
p.prompt = original_prompt
p.negative_prompt = original_negative_prompt
@@ -166,8 +166,7 @@ class Script(scripts.Script): if override_strength:
p.denoising_strength = 1.0
-
- def sample_extra(conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength):
+ def sample_extra(conditioning, unconditional_conditioning, seeds, subseeds, subseed_strength, prompts):
lat = (p.init_latent.cpu().numpy() * 10).astype(int)
same_params = self.cache is not None and self.cache.cfg_scale == cfg and self.cache.steps == st \
@@ -192,7 +191,7 @@ class Script(scripts.Script): combined_noise = ((1 - randomness) * rec_noise + randomness * rand_noise) / ((randomness**2 + (1-randomness)**2) ** 0.5)
- sampler = sd_samplers.create_sampler_with_index(sd_samplers.samplers, p.sampler_index, p.sd_model)
+ sampler = sd_samplers.create_sampler(p.sampler_name, p.sd_model)
sigmas = sampler.model_wrap.get_sigmas(p.steps)
diff --git a/scripts/outpainting_mk_2.py b/scripts/outpainting_mk_2.py index 2afd4aa5..cf71cb92 100644 --- a/scripts/outpainting_mk_2.py +++ b/scripts/outpainting_mk_2.py @@ -132,7 +132,7 @@ class Script(scripts.Script): info = gr.HTML("<p style=\"margin-bottom:0.75em\">Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8</p>")
pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128)
- mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=8, visible=False)
+ mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=8)
direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'])
noise_q = gr.Slider(label="Fall-off exponent (lower=higher detail)", minimum=0.0, maximum=4.0, step=0.01, value=1.0)
color_variation = gr.Slider(label="Color variation", minimum=0.0, maximum=1.0, step=0.01, value=0.05)
diff --git a/scripts/poor_mans_outpainting.py b/scripts/poor_mans_outpainting.py index b0469110..ea45beb0 100644 --- a/scripts/poor_mans_outpainting.py +++ b/scripts/poor_mans_outpainting.py @@ -22,8 +22,8 @@ class Script(scripts.Script): return None
pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=256, step=8, value=128)
- mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, visible=False)
- inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False)
+ mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4)
+ inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index")
direction = gr.CheckboxGroup(label="Outpainting direction", choices=['left', 'right', 'up', 'down'], value=['left', 'right', 'up', 'down'])
return [pixels, mask_blur, inpainting_fill, direction]
diff --git a/scripts/prompt_matrix.py b/scripts/prompt_matrix.py index e49c9b20..4c79eaef 100644 --- a/scripts/prompt_matrix.py +++ b/scripts/prompt_matrix.py @@ -18,7 +18,7 @@ def draw_xy_grid(xs, ys, x_label, y_label, cell): ver_texts = [[images.GridAnnotation(y_label(y))] for y in ys]
hor_texts = [[images.GridAnnotation(x_label(x))] for x in xs]
- first_pocessed = None
+ first_processed = None
state.job_count = len(xs) * len(ys)
@@ -27,17 +27,17 @@ def draw_xy_grid(xs, ys, x_label, y_label, cell): 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
res.append(processed.images[0])
grid = images.image_grid(res, rows=len(ys))
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
class Script(scripts.Script):
@@ -46,10 +46,11 @@ class Script(scripts.Script): def ui(self, is_img2img):
put_at_start = gr.Checkbox(label='Put variable parts at start of prompt', value=False)
+ different_seeds = gr.Checkbox(label='Use different seed for each picture', value=False)
- return [put_at_start]
+ return [put_at_start, different_seeds]
- def run(self, p, put_at_start):
+ def run(self, p, put_at_start, different_seeds):
modules.processing.fix_seed(p)
original_prompt = p.prompt[0] if type(p.prompt) == list else p.prompt
@@ -73,15 +74,17 @@ class Script(scripts.Script): print(f"Prompt matrix will create {len(all_prompts)} images using a total of {p.n_iter} batches.")
p.prompt = all_prompts
- p.seed = [p.seed for _ in all_prompts]
+ p.seed = [p.seed + (i if different_seeds else 0) for i in range(len(all_prompts))]
p.prompt_for_display = original_prompt
processed = process_images(p)
grid = images.image_grid(processed.images, p.batch_size, rows=1 << ((len(prompt_matrix_parts) - 1) // 2))
grid = images.draw_prompt_matrix(grid, p.width, p.height, prompt_matrix_parts)
processed.images.insert(0, grid)
+ processed.index_of_first_image = 1
+ processed.infotexts.insert(0, processed.infotexts[0])
if opts.grid_save:
- images.save_image(processed.images[0], p.outpath_grids, "prompt_matrix", prompt=original_prompt, seed=processed.seed, grid=True, p=p)
+ images.save_image(processed.images[0], p.outpath_grids, "prompt_matrix", extension=opts.grid_format, prompt=original_prompt, seed=processed.seed, grid=True, p=p)
return processed
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 1be22960..e8386ed2 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -9,6 +9,7 @@ import shlex import modules.scripts as scripts
import gradio as gr
+from modules import sd_samplers
from modules.processing import Processed, process_images
from PIL import Image
from modules.shared import opts, cmd_opts, state
@@ -44,6 +45,7 @@ prompt_tags = { "seed_resize_from_h": process_int_tag,
"seed_resize_from_w": process_int_tag,
"sampler_index": process_int_tag,
+ "sampler_name": process_string_tag,
"batch_size": process_int_tag,
"n_iter": process_int_tag,
"steps": process_int_tag,
@@ -66,14 +68,28 @@ def cmdargs(line): arg = args[pos]
assert arg.startswith("--"), f'must start with "--": {arg}'
+ assert pos+1 < len(args), f'missing argument for command line option {arg}'
+
tag = arg[2:]
+ if tag == "prompt" or tag == "negative_prompt":
+ pos += 1
+ prompt = args[pos]
+ pos += 1
+ while pos < len(args) and not args[pos].startswith("--"):
+ prompt += " "
+ prompt += args[pos]
+ pos += 1
+ res[tag] = prompt
+ continue
+
+
func = prompt_tags.get(tag, None)
assert func, f'unknown commandline option: {arg}'
- assert pos+1 < len(args), f'missing argument for command line option {arg}'
-
val = args[pos+1]
+ if tag == "sampler_name":
+ val = sd_samplers.samplers_map.get(val.lower(), None)
res[tag] = func(val)
@@ -83,19 +99,21 @@ def cmdargs(line): def load_prompt_file(file):
- if (file is None):
+ if file is None:
lines = []
else:
lines = [x.strip() for x in file.decode('utf8', errors='ignore').split("\n")]
return None, "\n".join(lines), gr.update(lines=7)
+
class Script(scripts.Script):
def title(self):
return "Prompts from file or textbox"
def ui(self, is_img2img):
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False)
+ checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False)
prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1)
file = gr.File(label="Upload prompt inputs", type='bytes')
@@ -106,9 +124,9 @@ class Script(scripts.Script): # We don't shrink back to 1, because that causes the control to ignore [enter], and it may
# be unclear to the user that shift-enter is needed.
prompt_txt.change(lambda tb: gr.update(lines=7) if ("\n" in tb) else gr.update(lines=2), inputs=[prompt_txt], outputs=[prompt_txt])
- return [checkbox_iterate, file, prompt_txt]
+ return [checkbox_iterate, checkbox_iterate_batch, prompt_txt]
- def run(self, p, checkbox_iterate, file, prompt_txt: str):
+ def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str):
lines = [x.strip() for x in prompt_txt.splitlines()]
lines = [x for x in lines if len(x) > 0]
@@ -122,7 +140,7 @@ class Script(scripts.Script): try:
args = cmdargs(line)
except Exception:
- print(f"Error parsing line [line] as commandline:", file=sys.stderr)
+ print(f"Error parsing line {line} as commandline:", file=sys.stderr)
print(traceback.format_exc(), file=sys.stderr)
args = {"prompt": line}
else:
@@ -137,12 +155,14 @@ class Script(scripts.Script): jobs.append(args)
print(f"Will process {len(lines)} lines in {job_count} jobs.")
- if (checkbox_iterate and p.seed == -1):
+ if (checkbox_iterate or checkbox_iterate_batch) and p.seed == -1:
p.seed = int(random.randrange(4294967294))
state.job_count = job_count
images = []
+ all_prompts = []
+ infotexts = []
for n, args in enumerate(jobs):
state.job = f"{state.job_no + 1} out of {state.job_count}"
@@ -153,8 +173,9 @@ class Script(scripts.Script): proc = process_images(copy_p)
images += proc.images
- if (checkbox_iterate):
+ if checkbox_iterate:
p.seed = p.seed + (p.batch_size * p.n_iter)
+ all_prompts += proc.all_prompts
+ infotexts += proc.infotexts
-
- return Processed(p, images, p.seed, "")
\ No newline at end of file + return Processed(p, images, p.seed, "", all_prompts=all_prompts, infotexts=infotexts)
diff --git a/scripts/sd_upscale.py b/scripts/sd_upscale.py index cb37ff7e..9739545c 100644 --- a/scripts/sd_upscale.py +++ b/scripts/sd_upscale.py @@ -17,13 +17,14 @@ class Script(scripts.Script): return is_img2img
def ui(self, is_img2img):
- info = gr.HTML("<p style=\"margin-bottom:0.75em\">Will upscale the image to twice the dimensions; use width and height sliders to set tile size</p>")
- overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64, visible=False)
- upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index", visible=False)
+ info = gr.HTML("<p style=\"margin-bottom:0.75em\">Will upscale the image by the selected scale factor; use width and height sliders to set tile size</p>")
+ overlap = gr.Slider(minimum=0, maximum=256, step=16, label='Tile overlap', value=64)
+ scale_factor = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label='Scale Factor', value=2.0)
+ upscaler_index = gr.Radio(label='Upscaler', choices=[x.name for x in shared.sd_upscalers], value=shared.sd_upscalers[0].name, type="index")
- return [info, overlap, upscaler_index]
+ return [info, overlap, upscaler_index, scale_factor]
- def run(self, p, _, overlap, upscaler_index):
+ def run(self, p, _, overlap, upscaler_index, scale_factor):
processing.fix_seed(p)
upscaler = shared.sd_upscalers[upscaler_index]
@@ -34,9 +35,10 @@ class Script(scripts.Script): seed = p.seed
init_img = p.init_images[0]
-
- if(upscaler.name != "None"):
- img = upscaler.scaler.upscale(init_img, 2, upscaler.data_path)
+ init_img = images.flatten(init_img, opts.img2img_background_color)
+
+ if upscaler.name != "None":
+ img = upscaler.scaler.upscale(init_img, scale_factor, upscaler.data_path)
else:
img = init_img
@@ -69,7 +71,7 @@ class Script(scripts.Script): work_results = []
for i in range(batch_count):
p.batch_size = batch_size
- p.init_images = work[i*batch_size:(i+1)*batch_size]
+ p.init_images = work[i * batch_size:(i + 1) * batch_size]
state.job = f"Batch {i + 1 + n * batch_count} out of {state.job_count}"
processed = processing.process_images(p)
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index f5255786..f92f9776 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -10,13 +10,16 @@ import numpy as np import modules.scripts as scripts
import gradio as gr
-from modules import images
+from modules import images, paths, sd_samplers
from modules.hypernetworks import hypernetwork
-from modules.processing import process_images, Processed, get_correct_sampler, StableDiffusionProcessingTxt2Img
+from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
import modules.sd_samplers
import modules.sd_models
+import modules.sd_vae
+import glob
+import os
import re
@@ -58,29 +61,19 @@ def apply_order(p, x, xs): prompt_tmp += part
prompt_tmp += x[idx]
p.prompt = prompt_tmp + p.prompt
-
-
-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 = build_samplers_dict(p).get(x.lower(), None)
- if sampler_index is None:
+ sampler_name = sd_samplers.samplers_map.get(x.lower(), None)
+ if sampler_name is None:
raise RuntimeError(f"Unknown sampler: {x}")
- p.sampler_index = sampler_index
+ p.sampler_name = sampler_name
def confirm_samplers(p, xs):
- samplers_dict = build_samplers_dict(p)
for x in xs:
- if x.lower() not in samplers_dict.keys():
+ if x.lower() not in sd_samplers.samplers_map:
raise RuntimeError(f"Unknown sampler: {x}")
@@ -124,6 +117,38 @@ def apply_clip_skip(p, x, xs): opts.data["CLIP_stop_at_last_layers"] = x
+def apply_upscale_latent_space(p, x, xs):
+ if x.lower().strip() != '0':
+ opts.data["use_scale_latent_for_hires_fix"] = True
+ else:
+ opts.data["use_scale_latent_for_hires_fix"] = False
+
+
+def find_vae(name: str):
+ if name.lower() in ['auto', 'none']:
+ return name
+ else:
+ vae_path = os.path.abspath(os.path.join(paths.models_path, 'VAE'))
+ found = glob.glob(os.path.join(vae_path, f'**/{name}.*pt'), recursive=True)
+ if found:
+ return found[0]
+ else:
+ return 'auto'
+
+
+def apply_vae(p, x, xs):
+ if x.lower().strip() == 'none':
+ modules.sd_vae.reload_vae_weights(shared.sd_model, vae_file='None')
+ else:
+ found = find_vae(x)
+ if found:
+ v = modules.sd_vae.reload_vae_weights(shared.sd_model, vae_file=found)
+
+
+def apply_styles(p: StableDiffusionProcessingTxt2Img, x: str, _):
+ p.styles = x.split(',')
+
+
def format_value_add_label(p, opt, x):
if type(x) == float:
x = round(x, 8)
@@ -177,7 +202,10 @@ axis_options = [ AxisOption("Eta", float, apply_field("eta"), format_value_add_label, None),
AxisOption("Clip skip", int, apply_clip_skip, format_value_add_label, None),
AxisOption("Denoising", float, apply_field("denoising_strength"), format_value_add_label, None),
+ AxisOption("Hires upscaler", str, apply_field("hr_upscaler"), format_value_add_label, None),
AxisOption("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight"), format_value_add_label, None),
+ AxisOption("VAE", str, apply_vae, format_value_add_label, None),
+ AxisOption("Styles", str, apply_styles, format_value_add_label, None),
]
@@ -239,9 +267,11 @@ class SharedSettingsStackHelper(object): self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
self.hypernetwork = opts.sd_hypernetwork
self.model = shared.sd_model
+ self.vae = opts.sd_vae
def __exit__(self, exc_type, exc_value, tb):
modules.sd_models.reload_model_weights(self.model)
+ modules.sd_vae.reload_vae_weights(self.model, vae_file=find_vae(self.vae))
hypernetwork.load_hypernetwork(self.hypernetwork)
hypernetwork.apply_strength()
@@ -263,12 +293,12 @@ class Script(scripts.Script): current_axis_options = [x for x in axis_options if type(x) == AxisOption or type(x) == AxisOptionImg2Img and is_img2img]
with gr.Row():
- x_type = gr.Dropdown(label="X type", choices=[x.label for x in current_axis_options], value=current_axis_options[1].label, visible=False, type="index", elem_id="x_type")
- x_values = gr.Textbox(label="X values", visible=False, lines=1)
+ x_type = gr.Dropdown(label="X type", choices=[x.label for x in current_axis_options], value=current_axis_options[1].label, type="index", elem_id="x_type")
+ x_values = gr.Textbox(label="X values", lines=1)
with gr.Row():
- y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, visible=False, type="index", elem_id="y_type")
- y_values = gr.Textbox(label="Y values", visible=False, lines=1)
+ y_type = gr.Dropdown(label="Y type", choices=[x.label for x in current_axis_options], value=current_axis_options[0].label, type="index", elem_id="y_type")
+ y_values = gr.Textbox(label="Y values", lines=1)
draw_legend = gr.Checkbox(label='Draw legend', value=True)
include_lone_images = gr.Checkbox(label='Include Separate Images', value=False)
@@ -393,6 +423,6 @@ class Script(scripts.Script): )
if opts.grid_save:
- images.save_image(processed.images[0], p.outpath_grids, "xy_grid", prompt=p.prompt, seed=processed.seed, grid=True, p=p)
+ images.save_image(processed.images[0], p.outpath_grids, "xy_grid", extension=opts.grid_format, prompt=p.prompt, seed=processed.seed, grid=True, p=p)
return processed
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