diff options
Diffstat (limited to 'scripts/xy_grid.py')
| -rw-r--r-- | scripts/xy_grid.py | 79 |
1 files changed, 33 insertions, 46 deletions
diff --git a/scripts/xy_grid.py b/scripts/xy_grid.py index 6629f5d5..1a452355 100644 --- a/scripts/xy_grid.py +++ b/scripts/xy_grid.py @@ -11,7 +11,6 @@ import modules.scripts as scripts import gradio as gr
from modules import images, paths, sd_samplers, processing, sd_models, sd_vae
-from modules.hypernetworks import hypernetwork
from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
from modules.shared import opts, cmd_opts, state
import modules.shared as shared
@@ -94,28 +93,6 @@ def confirm_checkpoints(p, xs): raise RuntimeError(f"Unknown checkpoint: {x}")
-def apply_hypernetwork(p, x, xs):
- if x.lower() in ["", "none"]:
- name = None
- else:
- name = hypernetwork.find_closest_hypernetwork_name(x)
- if not name:
- raise RuntimeError(f"Unknown hypernetwork: {x}")
- hypernetwork.load_hypernetwork(name)
-
-
-def apply_hypernetwork_strength(p, x, xs):
- hypernetwork.apply_strength(x)
-
-
-def confirm_hypernetworks(p, xs):
- for x in xs:
- if x.lower() in ["", "none"]:
- continue
- if not hypernetwork.find_closest_hypernetwork_name(x):
- raise RuntimeError(f"Unknown hypernetwork: {x}")
-
-
def apply_clip_skip(p, x, xs):
opts.data["CLIP_stop_at_last_layers"] = x
@@ -188,12 +165,16 @@ class AxisOption: self.confirm = confirm
self.cost = cost
self.choices = choices
- self.is_img2img = False
class AxisOptionImg2Img(AxisOption):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
+ self.is_img2img = True
+
+class AxisOptionTxt2Img(AxisOption):
+ def __init__(self, *args, **kwargs):
+ super().__init__(*args, **kwargs)
self.is_img2img = False
@@ -203,13 +184,13 @@ axis_options = [ AxisOption("Var. seed", int, apply_field("subseed")),
AxisOption("Var. strength", float, apply_field("subseed_strength")),
AxisOption("Steps", int, apply_field("steps")),
+ AxisOptionTxt2Img("Hires steps", int, apply_field("hr_second_pass_steps")),
AxisOption("CFG Scale", float, apply_field("cfg_scale")),
AxisOption("Prompt S/R", str, apply_prompt, format_value=format_value),
AxisOption("Prompt order", str_permutations, apply_order, format_value=format_value_join_list),
- AxisOption("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
+ AxisOptionTxt2Img("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers]),
+ AxisOptionImg2Img("Sampler", str, apply_sampler, format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img]),
AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_value, confirm=confirm_checkpoints, cost=1.0, choices=lambda: list(sd_models.checkpoints_list)),
- AxisOption("Hypernetwork", str, apply_hypernetwork, format_value=format_value, confirm=confirm_hypernetworks, cost=0.2, choices=lambda: list(shared.hypernetworks)),
- AxisOption("Hypernet str.", float, apply_hypernetwork_strength),
AxisOption("Sigma Churn", float, apply_field("s_churn")),
AxisOption("Sigma min", float, apply_field("s_tmin")),
AxisOption("Sigma max", float, apply_field("s_tmax")),
@@ -217,8 +198,8 @@ axis_options = [ AxisOption("Eta", float, apply_field("eta")),
AxisOption("Clip skip", int, apply_clip_skip),
AxisOption("Denoising", float, apply_field("denoising_strength")),
- AxisOption("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [x.name for x in shared.sd_upscalers]),
- AxisOption("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")),
+ AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
+ AxisOptionImg2Img("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")),
AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: list(sd_vae.vae_dict)),
AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)),
]
@@ -291,7 +272,6 @@ def draw_xy_grid(p, xs, ys, x_labels, y_labels, cell, draw_legend, include_lone_ class SharedSettingsStackHelper(object):
def __enter__(self):
self.CLIP_stop_at_last_layers = opts.CLIP_stop_at_last_layers
- self.hypernetwork = opts.sd_hypernetwork
self.vae = opts.sd_vae
def __exit__(self, exc_type, exc_value, tb):
@@ -299,9 +279,6 @@ class SharedSettingsStackHelper(object): modules.sd_models.reload_model_weights()
modules.sd_vae.reload_vae_weights()
- hypernetwork.load_hypernetwork(self.hypernetwork)
- hypernetwork.apply_strength()
-
opts.data["CLIP_stop_at_last_layers"] = self.CLIP_stop_at_last_layers
@@ -317,42 +294,41 @@ class Script(scripts.Script): return "X/Y plot"
def ui(self, is_img2img):
- current_axis_options = [x for x in axis_options if type(x) == AxisOption or x.is_img2img and is_img2img]
+ self.current_axis_options = [x for x in axis_options if type(x) == AxisOption or x.is_img2img == is_img2img]
with gr.Row():
with gr.Column(scale=19):
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, type="index", elem_id=self.elem_id("x_type"))
+ x_type = gr.Dropdown(label="X type", choices=[x.label for x in self.current_axis_options], value=self.current_axis_options[1].label, type="index", elem_id=self.elem_id("x_type"))
x_values = gr.Textbox(label="X values", lines=1, elem_id=self.elem_id("x_values"))
fill_x_button = ToolButton(value=fill_values_symbol, elem_id="xy_grid_fill_x_tool_button", visible=False)
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, type="index", elem_id=self.elem_id("y_type"))
+ y_type = gr.Dropdown(label="Y type", choices=[x.label for x in self.current_axis_options], value=self.current_axis_options[0].label, type="index", elem_id=self.elem_id("y_type"))
y_values = gr.Textbox(label="Y values", lines=1, elem_id=self.elem_id("y_values"))
fill_y_button = ToolButton(value=fill_values_symbol, elem_id="xy_grid_fill_y_tool_button", visible=False)
- with gr.Row(variant="compact"):
+ with gr.Row(variant="compact", elem_id="axis_options"):
draw_legend = gr.Checkbox(label='Draw legend', value=True, elem_id=self.elem_id("draw_legend"))
include_lone_images = gr.Checkbox(label='Include Separate Images', value=False, elem_id=self.elem_id("include_lone_images"))
no_fixed_seeds = gr.Checkbox(label='Keep -1 for seeds', value=False, elem_id=self.elem_id("no_fixed_seeds"))
swap_axes_button = gr.Button(value="Swap axes", elem_id="xy_grid_swap_axes_button")
def swap_axes(x_type, x_values, y_type, y_values):
- nonlocal current_axis_options
- return current_axis_options[y_type].label, y_values, current_axis_options[x_type].label, x_values
+ return self.current_axis_options[y_type].label, y_values, self.current_axis_options[x_type].label, x_values
swap_args = [x_type, x_values, y_type, y_values]
swap_axes_button.click(swap_axes, inputs=swap_args, outputs=swap_args)
def fill(x_type):
- axis = axis_options[x_type]
+ axis = self.current_axis_options[x_type]
return ", ".join(axis.choices()) if axis.choices else gr.update()
fill_x_button.click(fn=fill, inputs=[x_type], outputs=[x_values])
fill_y_button.click(fn=fill, inputs=[y_type], outputs=[y_values])
def select_axis(x_type):
- return gr.Button.update(visible=axis_options[x_type].choices is not None)
+ return gr.Button.update(visible=self.current_axis_options[x_type].choices is not None)
x_type.change(fn=select_axis, inputs=[x_type], outputs=[fill_x_button])
y_type.change(fn=select_axis, inputs=[y_type], outputs=[fill_y_button])
@@ -427,10 +403,10 @@ class Script(scripts.Script): return valslist
- x_opt = axis_options[x_type]
+ x_opt = self.current_axis_options[x_type]
xs = process_axis(x_opt, x_values)
- y_opt = axis_options[y_type]
+ y_opt = self.current_axis_options[y_type]
ys = process_axis(y_opt, y_values)
def fix_axis_seeds(axis_opt, axis_list):
@@ -451,10 +427,21 @@ class Script(scripts.Script): total_steps = p.steps * len(xs) * len(ys)
if isinstance(p, StableDiffusionProcessingTxt2Img) and p.enable_hr:
- total_steps *= 2
+ if x_opt.label == "Hires steps":
+ total_steps += sum(xs) * len(ys)
+ elif y_opt.label == "Hires steps":
+ total_steps += sum(ys) * len(xs)
+ elif p.hr_second_pass_steps:
+ total_steps += p.hr_second_pass_steps * len(xs) * len(ys)
+ else:
+ total_steps *= 2
+
+ total_steps *= p.n_iter
- print(f"X/Y plot will create {len(xs) * len(ys) * p.n_iter} images on a {len(xs)}x{len(ys)} grid. (Total steps to process: {total_steps * p.n_iter})")
- shared.total_tqdm.updateTotal(total_steps * p.n_iter)
+ image_cell_count = p.n_iter * p.batch_size
+ cell_console_text = f"; {image_cell_count} images per cell" if image_cell_count > 1 else ""
+ print(f"X/Y plot will create {len(xs) * len(ys) * image_cell_count} images on a {len(xs)}x{len(ys)} grid{cell_console_text}. (Total steps to process: {total_steps})")
+ shared.total_tqdm.updateTotal(total_steps)
grid_infotext = [None]
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