diff options
Diffstat (limited to 'scripts')
| -rw-r--r-- | scripts/postprocessing_caption.py | 30 | ||||
| -rw-r--r-- | scripts/postprocessing_codeformer.py | 16 | ||||
| -rw-r--r-- | scripts/postprocessing_create_flipped_copies.py | 32 | ||||
| -rw-r--r-- | scripts/postprocessing_focal_crop.py | 54 | ||||
| -rw-r--r-- | scripts/postprocessing_gfpgan.py | 13 | ||||
| -rw-r--r-- | scripts/postprocessing_split_oversized.py | 71 | ||||
| -rw-r--r-- | scripts/postprocessing_upscale.py | 14 | ||||
| -rw-r--r-- | scripts/processing_autosized_crop.py | 64 | ||||
| -rw-r--r-- | scripts/prompts_from_file.py | 32 | ||||
| -rw-r--r-- | scripts/xyz_grid.py | 189 |
10 files changed, 430 insertions, 85 deletions
diff --git a/scripts/postprocessing_caption.py b/scripts/postprocessing_caption.py new file mode 100644 index 00000000..5592a898 --- /dev/null +++ b/scripts/postprocessing_caption.py @@ -0,0 +1,30 @@ +from modules import scripts_postprocessing, ui_components, deepbooru, shared
+import gradio as gr
+
+
+class ScriptPostprocessingCeption(scripts_postprocessing.ScriptPostprocessing):
+ name = "Caption"
+ order = 4040
+
+ def ui(self):
+ with ui_components.InputAccordion(False, label="Caption") as enable:
+ option = gr.CheckboxGroup(value=["Deepbooru"], choices=["Deepbooru", "BLIP"], show_label=False)
+
+ return {
+ "enable": enable,
+ "option": option,
+ }
+
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, option):
+ if not enable:
+ return
+
+ captions = [pp.caption]
+
+ if "Deepbooru" in option:
+ captions.append(deepbooru.model.tag(pp.image))
+
+ if "BLIP" in option:
+ captions.append(shared.interrogator.interrogate(pp.image.convert("RGB")))
+
+ pp.caption = ", ".join([x for x in captions if x])
diff --git a/scripts/postprocessing_codeformer.py b/scripts/postprocessing_codeformer.py index a7d80d40..e1e156dd 100644 --- a/scripts/postprocessing_codeformer.py +++ b/scripts/postprocessing_codeformer.py @@ -1,28 +1,28 @@ from PIL import Image
import numpy as np
-from modules import scripts_postprocessing, codeformer_model
+from modules import scripts_postprocessing, codeformer_model, ui_components
import gradio as gr
-from modules.ui_components import FormRow
-
class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing):
name = "CodeFormer"
order = 3000
def ui(self):
- with FormRow():
- codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer visibility", value=0, elem_id="extras_codeformer_visibility")
- codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="CodeFormer weight (0 = maximum effect, 1 = minimum effect)", value=0, elem_id="extras_codeformer_weight")
+ with ui_components.InputAccordion(False, label="CodeFormer") as enable:
+ with gr.Row():
+ codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id="extras_codeformer_visibility")
+ codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Weight (0 = maximum effect, 1 = minimum effect)", value=0, elem_id="extras_codeformer_weight")
return {
+ "enable": enable,
"codeformer_visibility": codeformer_visibility,
"codeformer_weight": codeformer_weight,
}
- def process(self, pp: scripts_postprocessing.PostprocessedImage, codeformer_visibility, codeformer_weight):
- if codeformer_visibility == 0:
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, codeformer_visibility, codeformer_weight):
+ if codeformer_visibility == 0 or not enable:
return
restored_img = codeformer_model.codeformer.restore(np.array(pp.image, dtype=np.uint8), w=codeformer_weight)
diff --git a/scripts/postprocessing_create_flipped_copies.py b/scripts/postprocessing_create_flipped_copies.py new file mode 100644 index 00000000..b673003b --- /dev/null +++ b/scripts/postprocessing_create_flipped_copies.py @@ -0,0 +1,32 @@ +from PIL import ImageOps, Image
+
+from modules import scripts_postprocessing, ui_components
+import gradio as gr
+
+
+class ScriptPostprocessingCreateFlippedCopies(scripts_postprocessing.ScriptPostprocessing):
+ name = "Create flipped copies"
+ order = 4030
+
+ def ui(self):
+ with ui_components.InputAccordion(False, label="Create flipped copies") as enable:
+ with gr.Row():
+ option = gr.CheckboxGroup(value=["Horizontal"], choices=["Horizontal", "Vertical", "Both"], show_label=False)
+
+ return {
+ "enable": enable,
+ "option": option,
+ }
+
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, option):
+ if not enable:
+ return
+
+ if "Horizontal" in option:
+ pp.extra_images.append(ImageOps.mirror(pp.image))
+
+ if "Vertical" in option:
+ pp.extra_images.append(pp.image.transpose(Image.Transpose.FLIP_TOP_BOTTOM))
+
+ if "Both" in option:
+ pp.extra_images.append(pp.image.transpose(Image.Transpose.FLIP_TOP_BOTTOM).transpose(Image.Transpose.FLIP_LEFT_RIGHT))
diff --git a/scripts/postprocessing_focal_crop.py b/scripts/postprocessing_focal_crop.py new file mode 100644 index 00000000..cff1dbc5 --- /dev/null +++ b/scripts/postprocessing_focal_crop.py @@ -0,0 +1,54 @@ +
+from modules import scripts_postprocessing, ui_components, errors
+import gradio as gr
+
+from modules.textual_inversion import autocrop
+
+
+class ScriptPostprocessingFocalCrop(scripts_postprocessing.ScriptPostprocessing):
+ name = "Auto focal point crop"
+ order = 4010
+
+ def ui(self):
+ with ui_components.InputAccordion(False, label="Auto focal point crop") as enable:
+ face_weight = gr.Slider(label='Focal point face weight', value=0.9, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_focal_crop_face_weight")
+ entropy_weight = gr.Slider(label='Focal point entropy weight', value=0.15, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_focal_crop_entropy_weight")
+ edges_weight = gr.Slider(label='Focal point edges weight', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_focal_crop_edges_weight")
+ debug = gr.Checkbox(label='Create debug image', elem_id="train_process_focal_crop_debug")
+
+ return {
+ "enable": enable,
+ "face_weight": face_weight,
+ "entropy_weight": entropy_weight,
+ "edges_weight": edges_weight,
+ "debug": debug,
+ }
+
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, face_weight, entropy_weight, edges_weight, debug):
+ if not enable:
+ return
+
+ if not pp.shared.target_width or not pp.shared.target_height:
+ return
+
+ dnn_model_path = None
+ try:
+ dnn_model_path = autocrop.download_and_cache_models()
+ except Exception:
+ errors.report("Unable to load face detection model for auto crop selection. Falling back to lower quality haar method.", exc_info=True)
+
+ autocrop_settings = autocrop.Settings(
+ crop_width=pp.shared.target_width,
+ crop_height=pp.shared.target_height,
+ face_points_weight=face_weight,
+ entropy_points_weight=entropy_weight,
+ corner_points_weight=edges_weight,
+ annotate_image=debug,
+ dnn_model_path=dnn_model_path,
+ )
+
+ result, *others = autocrop.crop_image(pp.image, autocrop_settings)
+
+ pp.image = result
+ pp.extra_images = [pp.create_copy(x, nametags=["focal-crop-debug"], disable_processing=True) for x in others]
+
diff --git a/scripts/postprocessing_gfpgan.py b/scripts/postprocessing_gfpgan.py index d854f3f7..6e756605 100644 --- a/scripts/postprocessing_gfpgan.py +++ b/scripts/postprocessing_gfpgan.py @@ -1,26 +1,25 @@ from PIL import Image
import numpy as np
-from modules import scripts_postprocessing, gfpgan_model
+from modules import scripts_postprocessing, gfpgan_model, ui_components
import gradio as gr
-from modules.ui_components import FormRow
-
class ScriptPostprocessingGfpGan(scripts_postprocessing.ScriptPostprocessing):
name = "GFPGAN"
order = 2000
def ui(self):
- with FormRow():
- gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="GFPGAN visibility", value=0, elem_id="extras_gfpgan_visibility")
+ with ui_components.InputAccordion(False, label="GFPGAN") as enable:
+ gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Visibility", value=1.0, elem_id="extras_gfpgan_visibility")
return {
+ "enable": enable,
"gfpgan_visibility": gfpgan_visibility,
}
- def process(self, pp: scripts_postprocessing.PostprocessedImage, gfpgan_visibility):
- if gfpgan_visibility == 0:
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, gfpgan_visibility):
+ if gfpgan_visibility == 0 or not enable:
return
restored_img = gfpgan_model.gfpgan_fix_faces(np.array(pp.image, dtype=np.uint8))
diff --git a/scripts/postprocessing_split_oversized.py b/scripts/postprocessing_split_oversized.py new file mode 100644 index 00000000..c4a03160 --- /dev/null +++ b/scripts/postprocessing_split_oversized.py @@ -0,0 +1,71 @@ +import math
+
+from modules import scripts_postprocessing, ui_components
+import gradio as gr
+
+
+def split_pic(image, inverse_xy, width, height, overlap_ratio):
+ if inverse_xy:
+ from_w, from_h = image.height, image.width
+ to_w, to_h = height, width
+ else:
+ from_w, from_h = image.width, image.height
+ to_w, to_h = width, height
+ h = from_h * to_w // from_w
+ if inverse_xy:
+ image = image.resize((h, to_w))
+ else:
+ image = image.resize((to_w, h))
+
+ split_count = math.ceil((h - to_h * overlap_ratio) / (to_h * (1.0 - overlap_ratio)))
+ y_step = (h - to_h) / (split_count - 1)
+ for i in range(split_count):
+ y = int(y_step * i)
+ if inverse_xy:
+ splitted = image.crop((y, 0, y + to_h, to_w))
+ else:
+ splitted = image.crop((0, y, to_w, y + to_h))
+ yield splitted
+
+
+class ScriptPostprocessingSplitOversized(scripts_postprocessing.ScriptPostprocessing):
+ name = "Split oversized images"
+ order = 4000
+
+ def ui(self):
+ with ui_components.InputAccordion(False, label="Split oversized images") as enable:
+ with gr.Row():
+ split_threshold = gr.Slider(label='Threshold', value=0.5, minimum=0.0, maximum=1.0, step=0.05, elem_id="postprocess_split_threshold")
+ overlap_ratio = gr.Slider(label='Overlap ratio', value=0.2, minimum=0.0, maximum=0.9, step=0.05, elem_id="postprocess_overlap_ratio")
+
+ return {
+ "enable": enable,
+ "split_threshold": split_threshold,
+ "overlap_ratio": overlap_ratio,
+ }
+
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, split_threshold, overlap_ratio):
+ if not enable:
+ return
+
+ width = pp.shared.target_width
+ height = pp.shared.target_height
+
+ if not width or not height:
+ return
+
+ if pp.image.height > pp.image.width:
+ ratio = (pp.image.width * height) / (pp.image.height * width)
+ inverse_xy = False
+ else:
+ ratio = (pp.image.height * width) / (pp.image.width * height)
+ inverse_xy = True
+
+ if ratio >= 1.0 and ratio > split_threshold:
+ return
+
+ result, *others = split_pic(pp.image, inverse_xy, width, height, overlap_ratio)
+
+ pp.image = result
+ pp.extra_images = [pp.create_copy(x) for x in others]
+
diff --git a/scripts/postprocessing_upscale.py b/scripts/postprocessing_upscale.py index edb70ac0..ed709688 100644 --- a/scripts/postprocessing_upscale.py +++ b/scripts/postprocessing_upscale.py @@ -29,7 +29,7 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): upscaling_resize_w = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="extras_upscaling_resize_w")
upscaling_resize_h = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="extras_upscaling_resize_h")
with gr.Column(elem_id="upscaling_dimensions_row", scale=1, elem_classes="dimensions-tools"):
- upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn")
+ upscaling_res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="upscaling_res_switch_btn", tooltip="Switch width/height")
upscaling_crop = gr.Checkbox(label='Crop to fit', value=True, elem_id="extras_upscaling_crop")
with FormRow():
@@ -81,6 +81,14 @@ class ScriptPostprocessingUpscale(scripts_postprocessing.ScriptPostprocessing): return image
+ def process_firstpass(self, pp: scripts_postprocessing.PostprocessedImage, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
+ if upscale_mode == 1:
+ pp.shared.target_width = upscale_to_width
+ pp.shared.target_height = upscale_to_height
+ else:
+ pp.shared.target_width = int(pp.image.width * upscale_by)
+ pp.shared.target_height = int(pp.image.height * upscale_by)
+
def process(self, pp: scripts_postprocessing.PostprocessedImage, upscale_mode=1, upscale_by=2.0, upscale_to_width=None, upscale_to_height=None, upscale_crop=False, upscaler_1_name=None, upscaler_2_name=None, upscaler_2_visibility=0.0):
if upscaler_1_name == "None":
upscaler_1_name = None
@@ -126,6 +134,10 @@ class ScriptPostprocessingUpscaleSimple(ScriptPostprocessingUpscale): "upscaler_name": upscaler_name,
}
+ def process_firstpass(self, pp: scripts_postprocessing.PostprocessedImage, upscale_by=2.0, upscaler_name=None):
+ pp.shared.target_width = int(pp.image.width * upscale_by)
+ pp.shared.target_height = int(pp.image.height * upscale_by)
+
def process(self, pp: scripts_postprocessing.PostprocessedImage, upscale_by=2.0, upscaler_name=None):
if upscaler_name is None or upscaler_name == "None":
return
diff --git a/scripts/processing_autosized_crop.py b/scripts/processing_autosized_crop.py new file mode 100644 index 00000000..7e674989 --- /dev/null +++ b/scripts/processing_autosized_crop.py @@ -0,0 +1,64 @@ +from PIL import Image
+
+from modules import scripts_postprocessing, ui_components
+import gradio as gr
+
+
+def center_crop(image: Image, w: int, h: int):
+ iw, ih = image.size
+ if ih / h < iw / w:
+ sw = w * ih / h
+ box = (iw - sw) / 2, 0, iw - (iw - sw) / 2, ih
+ else:
+ sh = h * iw / w
+ box = 0, (ih - sh) / 2, iw, ih - (ih - sh) / 2
+ return image.resize((w, h), Image.Resampling.LANCZOS, box)
+
+
+def multicrop_pic(image: Image, mindim, maxdim, minarea, maxarea, objective, threshold):
+ iw, ih = image.size
+ err = lambda w, h: 1 - (lambda x: x if x < 1 else 1 / x)(iw / ih / (w / h))
+ wh = max(((w, h) for w in range(mindim, maxdim + 1, 64) for h in range(mindim, maxdim + 1, 64)
+ if minarea <= w * h <= maxarea and err(w, h) <= threshold),
+ key=lambda wh: (wh[0] * wh[1], -err(*wh))[::1 if objective == 'Maximize area' else -1],
+ default=None
+ )
+ return wh and center_crop(image, *wh)
+
+
+class ScriptPostprocessingAutosizedCrop(scripts_postprocessing.ScriptPostprocessing):
+ name = "Auto-sized crop"
+ order = 4020
+
+ def ui(self):
+ with ui_components.InputAccordion(False, label="Auto-sized crop") as enable:
+ gr.Markdown('Each image is center-cropped with an automatically chosen width and height.')
+ with gr.Row():
+ mindim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension lower bound", value=384, elem_id="postprocess_multicrop_mindim")
+ maxdim = gr.Slider(minimum=64, maximum=2048, step=8, label="Dimension upper bound", value=768, elem_id="postprocess_multicrop_maxdim")
+ with gr.Row():
+ minarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area lower bound", value=64 * 64, elem_id="postprocess_multicrop_minarea")
+ maxarea = gr.Slider(minimum=64 * 64, maximum=2048 * 2048, step=1, label="Area upper bound", value=640 * 640, elem_id="postprocess_multicrop_maxarea")
+ with gr.Row():
+ objective = gr.Radio(["Maximize area", "Minimize error"], value="Maximize area", label="Resizing objective", elem_id="postprocess_multicrop_objective")
+ threshold = gr.Slider(minimum=0, maximum=1, step=0.01, label="Error threshold", value=0.1, elem_id="postprocess_multicrop_threshold")
+
+ return {
+ "enable": enable,
+ "mindim": mindim,
+ "maxdim": maxdim,
+ "minarea": minarea,
+ "maxarea": maxarea,
+ "objective": objective,
+ "threshold": threshold,
+ }
+
+ def process(self, pp: scripts_postprocessing.PostprocessedImage, enable, mindim, maxdim, minarea, maxarea, objective, threshold):
+ if not enable:
+ return
+
+ cropped = multicrop_pic(pp.image, mindim, maxdim, minarea, maxarea, objective, threshold)
+ if cropped is not None:
+ pp.image = cropped
+ else:
+ print(f"skipped {pp.image.width}x{pp.image.height} image (can't find suitable size within error threshold)")
diff --git a/scripts/prompts_from_file.py b/scripts/prompts_from_file.py index 50320d55..a4a2f24d 100644 --- a/scripts/prompts_from_file.py +++ b/scripts/prompts_from_file.py @@ -5,11 +5,17 @@ import shlex import modules.scripts as scripts
import gradio as gr
-from modules import sd_samplers, errors
+from modules import sd_samplers, errors, sd_models
from modules.processing import Processed, process_images
from modules.shared import state
+def process_model_tag(tag):
+ info = sd_models.get_closet_checkpoint_match(tag)
+ assert info is not None, f'Unknown checkpoint: {tag}'
+ return info.name
+
+
def process_string_tag(tag):
return tag
@@ -27,7 +33,7 @@ def process_boolean_tag(tag): prompt_tags = {
- "sd_model": None,
+ "sd_model": process_model_tag,
"outpath_samples": process_string_tag,
"outpath_grids": process_string_tag,
"prompt_for_display": process_string_tag,
@@ -108,6 +114,7 @@ class Script(scripts.Script): def ui(self, is_img2img):
checkbox_iterate = gr.Checkbox(label="Iterate seed every line", value=False, elem_id=self.elem_id("checkbox_iterate"))
checkbox_iterate_batch = gr.Checkbox(label="Use same random seed for all lines", value=False, elem_id=self.elem_id("checkbox_iterate_batch"))
+ prompt_position = gr.Radio(["start", "end"], label="Insert prompts at the", elem_id=self.elem_id("prompt_position"), value="start")
prompt_txt = gr.Textbox(label="List of prompt inputs", lines=1, elem_id=self.elem_id("prompt_txt"))
file = gr.File(label="Upload prompt inputs", type='binary', elem_id=self.elem_id("file"))
@@ -118,9 +125,9 @@ 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], show_progress=False)
- return [checkbox_iterate, checkbox_iterate_batch, prompt_txt]
+ return [checkbox_iterate, checkbox_iterate_batch, prompt_position, prompt_txt]
- def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_txt: str):
+ def run(self, p, checkbox_iterate, checkbox_iterate_batch, prompt_position, prompt_txt: str):
lines = [x for x in (x.strip() for x in prompt_txt.splitlines()) if x]
p.do_not_save_grid = True
@@ -156,7 +163,22 @@ class Script(scripts.Script): copy_p = copy.copy(p)
for k, v in args.items():
- setattr(copy_p, k, v)
+ if k == "sd_model":
+ copy_p.override_settings['sd_model_checkpoint'] = v
+ else:
+ setattr(copy_p, k, v)
+
+ if args.get("prompt") and p.prompt:
+ if prompt_position == "start":
+ copy_p.prompt = args.get("prompt") + " " + p.prompt
+ else:
+ copy_p.prompt = p.prompt + " " + args.get("prompt")
+
+ if args.get("negative_prompt") and p.negative_prompt:
+ if prompt_position == "start":
+ copy_p.negative_prompt = args.get("negative_prompt") + " " + p.negative_prompt
+ else:
+ copy_p.negative_prompt = p.negative_prompt + " " + args.get("negative_prompt")
proc = process_images(copy_p)
images += proc.images
diff --git a/scripts/xyz_grid.py b/scripts/xyz_grid.py index 4eb1b197..34267c2c 100644 --- a/scripts/xyz_grid.py +++ b/scripts/xyz_grid.py @@ -3,6 +3,7 @@ from copy import copy from itertools import permutations, chain
import random
import csv
+import os.path
from io import StringIO
from PIL import Image
import numpy as np
@@ -10,7 +11,7 @@ import numpy as np import modules.scripts as scripts
import gradio as gr
-from modules import images, sd_samplers, processing, sd_models, sd_vae, sd_samplers_kdiffusion
+from modules import images, sd_samplers, processing, sd_models, sd_vae, sd_samplers_kdiffusion, errors
from modules.processing import process_images, Processed, StableDiffusionProcessingTxt2Img
from modules.shared import opts, state
import modules.shared as shared
@@ -66,14 +67,6 @@ def apply_order(p, x, xs): p.prompt = prompt_tmp + p.prompt
-def apply_sampler(p, x, xs):
- sampler_name = sd_samplers.samplers_map.get(x.lower(), None)
- if sampler_name is None:
- raise RuntimeError(f"Unknown sampler: {x}")
-
- p.sampler_name = sampler_name
-
-
def confirm_samplers(p, xs):
for x in xs:
if x.lower() not in sd_samplers.samplers_map:
@@ -93,6 +86,15 @@ def confirm_checkpoints(p, xs): raise RuntimeError(f"Unknown checkpoint: {x}")
+def confirm_checkpoints_or_none(p, xs):
+ for x in xs:
+ if x in (None, "", "None", "none"):
+ continue
+
+ if modules.sd_models.get_closet_checkpoint_match(x) is None:
+ raise RuntimeError(f"Unknown checkpoint: {x}")
+
+
def apply_clip_skip(p, x, xs):
opts.data["CLIP_stop_at_last_layers"] = x
@@ -183,19 +185,34 @@ def format_nothing(p, opt, x): return ""
+def format_remove_path(p, opt, x):
+ return os.path.basename(x)
+
+
def str_permutations(x):
"""dummy function for specifying it in AxisOption's type when you want to get a list of permutations"""
return x
+def list_to_csv_string(data_list):
+ with StringIO() as o:
+ csv.writer(o).writerow(data_list)
+ return o.getvalue().strip()
+
+
+def csv_string_to_list_strip(data_str):
+ return list(map(str.strip, chain.from_iterable(csv.reader(StringIO(data_str)))))
+
+
class AxisOption:
- def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None):
+ def __init__(self, label, type, apply, format_value=format_value_add_label, confirm=None, cost=0.0, choices=None, prepare=None):
self.label = label
self.type = type
self.apply = apply
self.format_value = format_value
self.confirm = confirm
self.cost = cost
+ self.prepare = prepare
self.choices = choices
@@ -204,6 +221,7 @@ class AxisOptionImg2Img(AxisOption): super().__init__(*args, **kwargs)
self.is_img2img = True
+
class AxisOptionTxt2Img(AxisOption):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@@ -221,9 +239,10 @@ axis_options = [ AxisOptionImg2Img("Image CFG Scale", float, apply_field("image_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),
- 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: sorted(sd_models.checkpoints_list, key=str.casefold)),
+ AxisOptionTxt2Img("Sampler", str, apply_field("sampler_name"), format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers if x.name not in opts.hide_samplers]),
+ AxisOptionTxt2Img("Hires sampler", str, apply_field("hr_sampler_name"), confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img if x.name not in opts.hide_samplers]),
+ AxisOptionImg2Img("Sampler", str, apply_field("sampler_name"), format_value=format_value, confirm=confirm_samplers, choices=lambda: [x.name for x in sd_samplers.samplers_for_img2img if x.name not in opts.hide_samplers]),
+ AxisOption("Checkpoint name", str, apply_checkpoint, format_value=format_remove_path, confirm=confirm_checkpoints, cost=1.0, choices=lambda: sorted(sd_models.checkpoints_list, key=str.casefold)),
AxisOption("Negative Guidance minimum sigma", float, apply_field("s_min_uncond")),
AxisOption("Sigma Churn", float, apply_field("s_churn")),
AxisOption("Sigma min", float, apply_field("s_tmin")),
@@ -236,6 +255,8 @@ axis_options = [ AxisOption("Eta", float, apply_field("eta")),
AxisOption("Clip skip", int, apply_clip_skip),
AxisOption("Denoising", float, apply_field("denoising_strength")),
+ AxisOption("Initial noise multiplier", float, apply_field("initial_noise_multiplier")),
+ AxisOption("Extra noise", float, apply_override("img2img_extra_noise")),
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: ['None'] + list(sd_vae.vae_dict)),
@@ -245,6 +266,11 @@ axis_options = [ AxisOption("Token merging ratio", float, apply_override('token_merging_ratio')),
AxisOption("Token merging ratio high-res", float, apply_override('token_merging_ratio_hr')),
AxisOption("Always discard next-to-last sigma", str, apply_override('always_discard_next_to_last_sigma', boolean=True), choices=boolean_choice(reverse=True)),
+ AxisOption("SGM noise multiplier", str, apply_override('sgm_noise_multiplier', boolean=True), choices=boolean_choice(reverse=True)),
+ AxisOption("Refiner checkpoint", str, apply_field('refiner_checkpoint'), format_value=format_remove_path, confirm=confirm_checkpoints_or_none, cost=1.0, choices=lambda: ['None'] + sorted(sd_models.checkpoints_list, key=str.casefold)),
+ AxisOption("Refiner switch at", float, apply_field('refiner_switch_at')),
+ AxisOption("RNG source", str, apply_override("randn_source"), choices=lambda: ["GPU", "CPU", "NV"]),
+ AxisOption("FP8 mode", str, apply_override("fp8_storage"), cost=0.9, choices=lambda: ["Disable", "Enable for SDXL", "Enable"]),
]
@@ -290,11 +316,10 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend cell_size = (processed_result.width, processed_result.height)
if processed_result.images[0] is not None:
cell_mode = processed_result.images[0].mode
- #This corrects size in case of batches:
+ # This corrects size in case of batches:
cell_size = processed_result.images[0].size
processed_result.images[idx] = Image.new(cell_mode, cell_size)
-
if first_axes_processed == 'x':
for ix, x in enumerate(xs):
if second_axes_processed == 'y':
@@ -352,9 +377,9 @@ def draw_xyz_grid(p, xs, ys, zs, x_labels, y_labels, z_labels, cell, draw_legend if draw_legend:
z_grid = images.draw_grid_annotations(z_grid, sub_grid_size[0], sub_grid_size[1], title_texts, [[images.GridAnnotation()]])
processed_result.images.insert(0, z_grid)
- #TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
- #processed_result.all_prompts.insert(0, processed_result.all_prompts[0])
- #processed_result.all_seeds.insert(0, processed_result.all_seeds[0])
+ # TODO: Deeper aspects of the program rely on grid info being misaligned between metadata arrays, which is not ideal.
+ # processed_result.all_prompts.insert(0, processed_result.all_prompts[0])
+ # processed_result.all_seeds.insert(0, processed_result.all_seeds[0])
processed_result.infotexts.insert(0, processed_result.infotexts[0])
return processed_result
@@ -378,8 +403,8 @@ class SharedSettingsStackHelper(object): re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
re_range_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\(([+-]\d+(?:.\d*)?)\s*\))?\s*")
-re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*\])?\s*")
-re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*\])?\s*")
+re_range_count = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\[(\d+)\s*])?\s*")
+re_range_count_float = re.compile(r"\s*([+-]?\s*\d+(?:.\d*)?)\s*-\s*([+-]?\s*\d+(?:.\d*)?)(?:\s*\[(\d+(?:.\d*)?)\s*])?\s*")
class Script(scripts.Script):
@@ -394,19 +419,19 @@ class Script(scripts.Script): with gr.Row():
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"))
- x_values_dropdown = gr.Dropdown(label="X values",visible=False,multiselect=True,interactive=True)
+ x_values_dropdown = gr.Dropdown(label="X values", visible=False, multiselect=True, interactive=True)
fill_x_button = ToolButton(value=fill_values_symbol, elem_id="xyz_grid_fill_x_tool_button", visible=False)
with gr.Row():
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"))
- y_values_dropdown = gr.Dropdown(label="Y values",visible=False,multiselect=True,interactive=True)
+ y_values_dropdown = gr.Dropdown(label="Y values", visible=False, multiselect=True, interactive=True)
fill_y_button = ToolButton(value=fill_values_symbol, elem_id="xyz_grid_fill_y_tool_button", visible=False)
with gr.Row():
z_type = gr.Dropdown(label="Z 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("z_type"))
z_values = gr.Textbox(label="Z values", lines=1, elem_id=self.elem_id("z_values"))
- z_values_dropdown = gr.Dropdown(label="Z values",visible=False,multiselect=True,interactive=True)
+ z_values_dropdown = gr.Dropdown(label="Z values", visible=False, multiselect=True, interactive=True)
fill_z_button = ToolButton(value=fill_values_symbol, elem_id="xyz_grid_fill_z_tool_button", visible=False)
with gr.Row(variant="compact", elem_id="axis_options"):
@@ -422,6 +447,8 @@ class Script(scripts.Script): vary_seeds_z = gr.Checkbox(label='Vary seed on Z axis', value=False, elem_id=self.elem_id("vary_seeds_z"))
with gr.Column():
margin_size = gr.Slider(label="Grid margins (px)", minimum=0, maximum=500, value=0, step=2, elem_id=self.elem_id("margin_size"))
+ with gr.Column():
+ csv_mode = gr.Checkbox(label='Use text inputs instead of dropdowns', value=False, elem_id=self.elem_id("csv_mode"))
with gr.Row(variant="compact", elem_id="swap_axes"):
swap_xy_axes_button = gr.Button(value="Swap X/Y axes", elem_id="xy_grid_swap_axes_button")
@@ -438,50 +465,75 @@ class Script(scripts.Script): xz_swap_args = [x_type, x_values, x_values_dropdown, z_type, z_values, z_values_dropdown]
swap_xz_axes_button.click(swap_axes, inputs=xz_swap_args, outputs=xz_swap_args)
- def fill(x_type):
- axis = self.current_axis_options[x_type]
- return axis.choices() if axis.choices else gr.update()
+ def fill(axis_type, csv_mode):
+ axis = self.current_axis_options[axis_type]
+ if axis.choices:
+ if csv_mode:
+ return list_to_csv_string(axis.choices()), gr.update()
+ else:
+ return gr.update(), axis.choices()
+ else:
+ return gr.update(), gr.update()
+
+ fill_x_button.click(fn=fill, inputs=[x_type, csv_mode], outputs=[x_values, x_values_dropdown])
+ fill_y_button.click(fn=fill, inputs=[y_type, csv_mode], outputs=[y_values, y_values_dropdown])
+ fill_z_button.click(fn=fill, inputs=[z_type, csv_mode], outputs=[z_values, z_values_dropdown])
- fill_x_button.click(fn=fill, inputs=[x_type], outputs=[x_values_dropdown])
- fill_y_button.click(fn=fill, inputs=[y_type], outputs=[y_values_dropdown])
- fill_z_button.click(fn=fill, inputs=[z_type], outputs=[z_values_dropdown])
+ def select_axis(axis_type, axis_values, axis_values_dropdown, csv_mode):
+ axis_type = axis_type or 0 # if axle type is None set to 0
- def select_axis(axis_type,axis_values_dropdown):
choices = self.current_axis_options[axis_type].choices
has_choices = choices is not None
- current_values = axis_values_dropdown
+
if has_choices:
choices = choices()
- if isinstance(current_values,str):
- current_values = current_values.split(",")
- current_values = list(filter(lambda x: x in choices, current_values))
- return gr.Button.update(visible=has_choices),gr.Textbox.update(visible=not has_choices),gr.update(choices=choices if has_choices else None,visible=has_choices,value=current_values)
-
- x_type.change(fn=select_axis, inputs=[x_type,x_values_dropdown], outputs=[fill_x_button,x_values,x_values_dropdown])
- y_type.change(fn=select_axis, inputs=[y_type,y_values_dropdown], outputs=[fill_y_button,y_values,y_values_dropdown])
- z_type.change(fn=select_axis, inputs=[z_type,z_values_dropdown], outputs=[fill_z_button,z_values,z_values_dropdown])
-
- def get_dropdown_update_from_params(axis,params):
+ if csv_mode:
+ if axis_values_dropdown:
+ axis_values = list_to_csv_string(list(filter(lambda x: x in choices, axis_values_dropdown)))
+ axis_values_dropdown = []
+ else:
+ if axis_values:
+ axis_values_dropdown = list(filter(lambda x: x in choices, csv_string_to_list_strip(axis_values)))
+ axis_values = ""
+
+ return (gr.Button.update(visible=has_choices), gr.Textbox.update(visible=not has_choices or csv_mode, value=axis_values),
+ gr.update(choices=choices if has_choices else None, visible=has_choices and not csv_mode, value=axis_values_dropdown))
+
+ x_type.change(fn=select_axis, inputs=[x_type, x_values, x_values_dropdown, csv_mode], outputs=[fill_x_button, x_values, x_values_dropdown])
+ y_type.change(fn=select_axis, inputs=[y_type, y_values, y_values_dropdown, csv_mode], outputs=[fill_y_button, y_values, y_values_dropdown])
+ z_type.change(fn=select_axis, inputs=[z_type, z_values, z_values_dropdown, csv_mode], outputs=[fill_z_button, z_values, z_values_dropdown])
+
+ def change_choice_mode(csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown):
+ _fill_x_button, _x_values, _x_values_dropdown = select_axis(x_type, x_values, x_values_dropdown, csv_mode)
+ _fill_y_button, _y_values, _y_values_dropdown = select_axis(y_type, y_values, y_values_dropdown, csv_mode)
+ _fill_z_button, _z_values, _z_values_dropdown = select_axis(z_type, z_values, z_values_dropdown, csv_mode)
+ return _fill_x_button, _x_values, _x_values_dropdown, _fill_y_button, _y_values, _y_values_dropdown, _fill_z_button, _z_values, _z_values_dropdown
+
+ csv_mode.change(fn=change_choice_mode, inputs=[csv_mode, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown], outputs=[fill_x_button, x_values, x_values_dropdown, fill_y_button, y_values, y_values_dropdown, fill_z_button, z_values, z_values_dropdown])
+
+ def get_dropdown_update_from_params(axis, params):
val_key = f"{axis} Values"
- vals = params.get(val_key,"")
- valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x]
- return gr.update(value = valslist)
+ vals = params.get(val_key, "")
+ valslist = csv_string_to_list_strip(vals)
+ return gr.update(value=valslist)
self.infotext_fields = (
(x_type, "X Type"),
(x_values, "X Values"),
- (x_values_dropdown, lambda params:get_dropdown_update_from_params("X",params)),
+ (x_values_dropdown, lambda params: get_dropdown_update_from_params("X", params)),
(y_type, "Y Type"),
(y_values, "Y Values"),
- (y_values_dropdown, lambda params:get_dropdown_update_from_params("Y",params)),
+ (y_values_dropdown, lambda params: get_dropdown_update_from_params("Y", params)),
(z_type, "Z Type"),
(z_values, "Z Values"),
- (z_values_dropdown, lambda params:get_dropdown_update_from_params("Z",params)),
+ (z_values_dropdown, lambda params: get_dropdown_update_from_params("Z", params)),
)
- return [x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size]
+ return [x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size, csv_mode]
+
+ def run(self, p, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, margin_size, csv_mode):
+ x_type, y_type, z_type = x_type or 0, y_type or 0, z_type or 0 # if axle type is None set to 0
- def run(self, p, x_type, x_values, x_values_dropdown, y_type, y_values, y_values_dropdown, z_type, z_values, z_values_dropdown, draw_legend, include_lone_images, include_sub_grids, no_fixed_seeds, vary_seeds_x, vary_seeds_y, vary_seeds_z, margin_size):
if not no_fixed_seeds:
modules.processing.fix_seed(p)
@@ -492,10 +544,12 @@ class Script(scripts.Script): if opt.label == 'Nothing':
return [0]
- if opt.choices is not None:
+ if opt.choices is not None and not csv_mode:
valslist = vals_dropdown
+ elif opt.prepare is not None:
+ valslist = opt.prepare(vals)
else:
- valslist = [x.strip() for x in chain.from_iterable(csv.reader(StringIO(vals))) if x]
+ valslist = csv_string_to_list_strip(vals)
if opt.type == int:
valslist_ext = []
@@ -511,8 +565,8 @@ class Script(scripts.Script): valslist_ext += list(range(start, end, step))
elif mc is not None:
start = int(mc.group(1))
- end = int(mc.group(2))
- num = int(mc.group(3)) if mc.group(3) is not None else 1
+ end = int(mc.group(2))
+ num = int(mc.group(3)) if mc.group(3) is not None else 1
valslist_ext += [int(x) for x in np.linspace(start=start, stop=end, num=num).tolist()]
else:
@@ -533,8 +587,8 @@ class Script(scripts.Script): valslist_ext += np.arange(start, end + step, step).tolist()
elif mc is not None:
start = float(mc.group(1))
- end = float(mc.group(2))
- num = int(mc.group(3)) if mc.group(3) is not None else 1
+ end = float(mc.group(2))
+ num = int(mc.group(3)) if mc.group(3) is not None else 1
valslist_ext += np.linspace(start=start, stop=end, num=num).tolist()
else:
@@ -553,22 +607,22 @@ class Script(scripts.Script): return valslist
x_opt = self.current_axis_options[x_type]
- if x_opt.choices is not None:
- x_values = ",".join(x_values_dropdown)
+ if x_opt.choices is not None and not csv_mode:
+ x_values = list_to_csv_string(x_values_dropdown)
xs = process_axis(x_opt, x_values, x_values_dropdown)
y_opt = self.current_axis_options[y_type]
- if y_opt.choices is not None:
- y_values = ",".join(y_values_dropdown)
+ if y_opt.choices is not None and not csv_mode:
+ y_values = list_to_csv_string(y_values_dropdown)
ys = process_axis(y_opt, y_values, y_values_dropdown)
z_opt = self.current_axis_options[z_type]
- if z_opt.choices is not None:
- z_values = ",".join(z_values_dropdown)
+ if z_opt.choices is not None and not csv_mode:
+ z_values = list_to_csv_string(z_values_dropdown)
zs = process_axis(z_opt, z_values, z_values_dropdown)
# this could be moved to common code, but unlikely to be ever triggered anywhere else
- Image.MAX_IMAGE_PIXELS = None # disable check in Pillow and rely on check below to allow large custom image sizes
+ Image.MAX_IMAGE_PIXELS = None # disable check in Pillow and rely on check below to allow large custom image sizes
grid_mp = round(len(xs) * len(ys) * len(zs) * p.width * p.height / 1000000)
assert grid_mp < opts.img_max_size_mp, f'Error: Resulting grid would be too large ({grid_mp} MPixels) (max configured size is {opts.img_max_size_mp} MPixels)'
@@ -662,7 +716,12 @@ class Script(scripts.Script): if vary_seeds_z:
pc.seed += iz * xdim * ydim
- res = process_images(pc)
+ try:
+ res = process_images(pc)
+ except Exception as e:
+ errors.display(e, "generating image for xyz plot")
+
+ res = Processed(p, [], p.seed, "")
# Sets subgrid infotexts
subgrid_index = 1 + iz
@@ -733,9 +792,11 @@ class Script(scripts.Script): # Auto-save main and sub-grids:
grid_count = z_count + 1 if z_count > 1 else 1
for g in range(grid_count):
- #TODO: See previous comment about intentional data misalignment.
+ # TODO: See previous comment about intentional data misalignment.
adj_g = g-1 if g > 0 else g
images.save_image(processed.images[g], p.outpath_grids, "xyz_grid", info=processed.infotexts[g], extension=opts.grid_format, prompt=processed.all_prompts[adj_g], seed=processed.all_seeds[adj_g], grid=True, p=processed)
+ if not include_sub_grids: # if not include_sub_grids then skip saving after the first grid
+ break
if not include_sub_grids:
# Done with sub-grids, drop all related information:
|