diff options
| -rw-r--r-- | modules/img2img.py | 8 | ||||
| -rwxr-xr-x | modules/processing.py | 340 | ||||
| -rw-r--r-- | modules/processing_scripts/refiner.py | 16 | ||||
| -rw-r--r-- | modules/processing_scripts/seed.py | 100 | ||||
| -rw-r--r-- | modules/scripts.py | 83 | ||||
| -rw-r--r-- | modules/sd_samplers_common.py | 7 | ||||
| -rw-r--r-- | modules/shared_items.py | 1 | ||||
| -rw-r--r-- | modules/txt2img.py | 8 | ||||
| -rw-r--r-- | modules/ui.py | 119 | ||||
| -rw-r--r-- | modules/ui_common.py | 14 | ||||
| -rw-r--r-- | style.css | 26 |
11 files changed, 417 insertions, 305 deletions
diff --git a/modules/img2img.py b/modules/img2img.py index c7bbbac8..ac9fd3f8 100644 --- a/modules/img2img.py +++ b/modules/img2img.py @@ -116,7 +116,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal process_images(p)
-def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_name: str, mask_blur: int, mask_alpha: float, inpainting_fill: int, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, seed_enable_extras: bool, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args):
+def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_styles, init_img, sketch, init_img_with_mask, inpaint_color_sketch, inpaint_color_sketch_orig, init_img_inpaint, init_mask_inpaint, steps: int, sampler_name: str, mask_blur: int, mask_alpha: float, inpainting_fill: int, n_iter: int, batch_size: int, cfg_scale: float, image_cfg_scale: float, denoising_strength: float, selected_scale_tab: int, height: int, width: int, scale_by: float, resize_mode: int, inpaint_full_res: bool, inpaint_full_res_padding: int, inpainting_mask_invert: int, img2img_batch_input_dir: str, img2img_batch_output_dir: str, img2img_batch_inpaint_mask_dir: str, override_settings_texts, img2img_batch_use_png_info: bool, img2img_batch_png_info_props: list, img2img_batch_png_info_dir: str, request: gr.Request, *args):
override_settings = create_override_settings_dict(override_settings_texts)
is_batch = mode == 5
@@ -166,12 +166,6 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s prompt=prompt,
negative_prompt=negative_prompt,
styles=prompt_styles,
- seed=seed,
- subseed=subseed,
- subseed_strength=subseed_strength,
- seed_resize_from_h=seed_resize_from_h,
- seed_resize_from_w=seed_resize_from_w,
- seed_enable_extras=seed_enable_extras,
sampler_name=sampler_name,
batch_size=batch_size,
n_iter=n_iter,
diff --git a/modules/processing.py b/modules/processing.py index 6ad105d7..007a4e05 100755 --- a/modules/processing.py +++ b/modules/processing.py @@ -1,9 +1,11 @@ +from __future__ import annotations
import json
import logging
import math
import os
import sys
import hashlib
+from dataclasses import dataclass, field
import torch
import numpy as np
@@ -11,7 +13,7 @@ from PIL import Image, ImageOps import random
import cv2
from skimage import exposure
-from typing import Any, Dict, List
+from typing import Any
import modules.sd_hijack
from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common, sd_unet, errors, rng
@@ -104,97 +106,126 @@ def txt2img_image_conditioning(sd_model, x, width, height): return x.new_zeros(x.shape[0], 5, 1, 1, dtype=x.dtype, device=x.device)
+@dataclass(repr=False)
class StableDiffusionProcessing:
- """
- The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
- """
+ sd_model: object = None
+ outpath_samples: str = None
+ outpath_grids: str = None
+ prompt: str = ""
+ prompt_for_display: str = None
+ negative_prompt: str = ""
+ styles: list[str] = field(default_factory=list)
+ seed: int = -1
+ subseed: int = -1
+ subseed_strength: float = 0
+ seed_resize_from_h: int = -1
+ seed_resize_from_w: int = -1
+ seed_enable_extras: bool = True
+ sampler_name: str = None
+ batch_size: int = 1
+ n_iter: int = 1
+ steps: int = 50
+ cfg_scale: float = 7.0
+ width: int = 512
+ height: int = 512
+ restore_faces: bool = None
+ tiling: bool = None
+ do_not_save_samples: bool = False
+ do_not_save_grid: bool = False
+ extra_generation_params: dict[str, Any] = None
+ overlay_images: list = None
+ eta: float = None
+ do_not_reload_embeddings: bool = False
+ denoising_strength: float = 0
+ ddim_discretize: str = None
+ s_min_uncond: float = None
+ s_churn: float = None
+ s_tmax: float = None
+ s_tmin: float = None
+ s_noise: float = None
+ override_settings: dict[str, Any] = None
+ override_settings_restore_afterwards: bool = True
+ sampler_index: int = None
+ refiner_checkpoint: str = None
+ refiner_switch_at: float = None
+ token_merging_ratio = 0
+ token_merging_ratio_hr = 0
+ disable_extra_networks: bool = False
+
+ script_args: list = None
+
cached_uc = [None, None]
cached_c = [None, None]
- def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = None, tiling: bool = None, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = None, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None):
- if sampler_index is not None:
+ sampler: sd_samplers_common.Sampler | None = field(default=None, init=False)
+ is_using_inpainting_conditioning: bool = field(default=False, init=False)
+ paste_to: tuple | None = field(default=None, init=False)
+
+ is_hr_pass: bool = field(default=False, init=False)
+
+ c: tuple = field(default=None, init=False)
+ uc: tuple = field(default=None, init=False)
+
+ rng: rng.ImageRNG | None = field(default=None, init=False)
+ step_multiplier: int = field(default=1, init=False)
+ color_corrections: list = field(default=None, init=False)
+
+ scripts: list = field(default=None, init=False)
+ all_prompts: list = field(default=None, init=False)
+ all_negative_prompts: list = field(default=None, init=False)
+ all_seeds: list = field(default=None, init=False)
+ all_subseeds: list = field(default=None, init=False)
+ iteration: int = field(default=0, init=False)
+ main_prompt: str = field(default=None, init=False)
+ main_negative_prompt: str = field(default=None, init=False)
+
+ prompts: list = field(default=None, init=False)
+ negative_prompts: list = field(default=None, init=False)
+ seeds: list = field(default=None, init=False)
+ subseeds: list = field(default=None, init=False)
+ extra_network_data: dict = field(default=None, init=False)
+
+ user: str = field(default=None, init=False)
+
+ sd_model_name: str = field(default=None, init=False)
+ sd_model_hash: str = field(default=None, init=False)
+ sd_vae_name: str = field(default=None, init=False)
+ sd_vae_hash: str = field(default=None, init=False)
+
+ def __post_init__(self):
+ if self.sampler_index is not None:
print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
- self.outpath_samples: str = outpath_samples
- self.outpath_grids: str = outpath_grids
- self.prompt: str = prompt
- self.prompt_for_display: str = None
- self.negative_prompt: str = (negative_prompt or "")
- self.styles: list = styles or []
- self.seed: int = seed
- self.subseed: int = subseed
- self.subseed_strength: float = subseed_strength
- self.seed_resize_from_h: int = seed_resize_from_h
- self.seed_resize_from_w: int = seed_resize_from_w
- self.sampler_name: str = sampler_name
- self.batch_size: int = batch_size
- self.n_iter: int = n_iter
- self.steps: int = steps
- self.cfg_scale: float = cfg_scale
- self.width: int = width
- self.height: int = height
- self.restore_faces: bool = restore_faces
- self.tiling: bool = tiling
- self.do_not_save_samples: bool = do_not_save_samples
- self.do_not_save_grid: bool = do_not_save_grid
- self.extra_generation_params: dict = extra_generation_params or {}
- self.overlay_images = overlay_images
- self.eta = eta
- self.do_not_reload_embeddings = do_not_reload_embeddings
- self.paste_to = None
- self.color_corrections = None
- self.denoising_strength: float = denoising_strength
self.sampler_noise_scheduler_override = None
- self.ddim_discretize = ddim_discretize or opts.ddim_discretize
- self.s_min_uncond = s_min_uncond or opts.s_min_uncond
- self.s_churn = s_churn or opts.s_churn
- self.s_tmin = s_tmin or opts.s_tmin
- self.s_tmax = (s_tmax if s_tmax is not None else opts.s_tmax) or float('inf')
- self.s_noise = s_noise if s_noise is not None else opts.s_noise
- self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
- self.override_settings_restore_afterwards = override_settings_restore_afterwards
- self.is_using_inpainting_conditioning = False
- self.disable_extra_networks = False
- self.token_merging_ratio = 0
- self.token_merging_ratio_hr = 0
-
- if not seed_enable_extras:
+ self.s_min_uncond = self.s_min_uncond if self.s_min_uncond is not None else opts.s_min_uncond
+ self.s_churn = self.s_churn if self.s_churn is not None else opts.s_churn
+ self.s_tmin = self.s_tmin if self.s_tmin is not None else opts.s_tmin
+ self.s_tmax = (self.s_tmax if self.s_tmax is not None else opts.s_tmax) or float('inf')
+ self.s_noise = self.s_noise if self.s_noise is not None else opts.s_noise
+
+ self.extra_generation_params = self.extra_generation_params or {}
+ self.override_settings = self.override_settings or {}
+ self.script_args = self.script_args or {}
+
+ self.refiner_checkpoint_info = None
+
+ if not self.seed_enable_extras:
self.subseed = -1
self.subseed_strength = 0
self.seed_resize_from_h = 0
self.seed_resize_from_w = 0
- self.scripts = None
- self.script_args = script_args
- self.all_prompts = None
- self.all_negative_prompts = None
- self.all_seeds = None
- self.all_subseeds = None
- self.iteration = 0
- self.is_hr_pass = False
- self.sampler = None
- self.main_prompt = None
- self.main_negative_prompt = None
-
- self.prompts = None
- self.negative_prompts = None
- self.extra_network_data = None
- self.seeds = None
- self.subseeds = None
-
- self.step_multiplier = 1
self.cached_uc = StableDiffusionProcessing.cached_uc
self.cached_c = StableDiffusionProcessing.cached_c
- self.uc = None
- self.c = None
- self.rng: rng.ImageRNG = None
-
- self.user = None
@property
def sd_model(self):
return shared.sd_model
+ @sd_model.setter
+ def sd_model(self, value):
+ pass
+
def txt2img_image_conditioning(self, x, width=None, height=None):
self.is_using_inpainting_conditioning = self.sd_model.model.conditioning_key in {'hybrid', 'concat'}
@@ -408,7 +439,10 @@ class Processed: self.batch_size = p.batch_size
self.restore_faces = p.restore_faces
self.face_restoration_model = opts.face_restoration_model if p.restore_faces else None
- self.sd_model_hash = shared.sd_model.sd_model_hash
+ self.sd_model_name = p.sd_model_name
+ self.sd_model_hash = p.sd_model_hash
+ self.sd_vae_name = p.sd_vae_name
+ self.sd_vae_hash = p.sd_vae_hash
self.seed_resize_from_w = p.seed_resize_from_w
self.seed_resize_from_h = p.seed_resize_from_h
self.denoising_strength = getattr(p, 'denoising_strength', None)
@@ -459,7 +493,10 @@ class Processed: "batch_size": self.batch_size,
"restore_faces": self.restore_faces,
"face_restoration_model": self.face_restoration_model,
+ "sd_model_name": self.sd_model_name,
"sd_model_hash": self.sd_model_hash,
+ "sd_vae_name": self.sd_vae_name,
+ "sd_vae_hash": self.sd_vae_hash,
"seed_resize_from_w": self.seed_resize_from_w,
"seed_resize_from_h": self.seed_resize_from_h,
"denoising_strength": self.denoising_strength,
@@ -578,10 +615,10 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter "Seed": p.all_seeds[0] if use_main_prompt else all_seeds[index],
"Face restoration": opts.face_restoration_model if p.restore_faces else None,
"Size": f"{p.width}x{p.height}",
- "Model hash": getattr(p, 'sd_model_hash', None if not opts.add_model_hash_to_info or not shared.sd_model.sd_model_hash else shared.sd_model.sd_model_hash),
- "Model": (None if not opts.add_model_name_to_info else shared.sd_model.sd_checkpoint_info.name_for_extra),
- "VAE hash": p.loaded_vae_hash if opts.add_model_hash_to_info else None,
- "VAE": p.loaded_vae_name if opts.add_model_name_to_info else None,
+ "Model hash": p.sd_model_hash if opts.add_model_hash_to_info else None,
+ "Model": p.sd_model_name if opts.add_model_name_to_info else None,
+ "VAE hash": p.sd_vae_hash if opts.add_model_hash_to_info else None,
+ "VAE": p.sd_vae_name if opts.add_model_name_to_info else None,
"Variation seed": (None if p.subseed_strength == 0 else (p.all_subseeds[0] if use_main_prompt else all_subseeds[index])),
"Variation seed strength": (None if p.subseed_strength == 0 else p.subseed_strength),
"Seed resize from": (None if p.seed_resize_from_w <= 0 or p.seed_resize_from_h <= 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
@@ -670,8 +707,15 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed: if p.tiling is None:
p.tiling = opts.tiling
- p.loaded_vae_name = sd_vae.get_loaded_vae_name()
- p.loaded_vae_hash = sd_vae.get_loaded_vae_hash()
+ if p.refiner_checkpoint not in (None, "", "None"):
+ p.refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(p.refiner_checkpoint)
+ if p.refiner_checkpoint_info is None:
+ raise Exception(f'Could not find checkpoint with name {p.refiner_checkpoint}')
+
+ p.sd_model_name = shared.sd_model.sd_checkpoint_info.name_for_extra
+ p.sd_model_hash = shared.sd_model.sd_model_hash
+ p.sd_vae_name = sd_vae.get_loaded_vae_name()
+ p.sd_vae_hash = sd_vae.get_loaded_vae_hash()
modules.sd_hijack.model_hijack.apply_circular(p.tiling)
modules.sd_hijack.model_hijack.clear_comments()
@@ -910,49 +954,51 @@ def old_hires_fix_first_pass_dimensions(width, height): return width, height
+@dataclass(repr=False)
class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
- sampler = None
+ enable_hr: bool = False
+ denoising_strength: float = 0.75
+ firstphase_width: int = 0
+ firstphase_height: int = 0
+ hr_scale: float = 2.0
+ hr_upscaler: str = None
+ hr_second_pass_steps: int = 0
+ hr_resize_x: int = 0
+ hr_resize_y: int = 0
+ hr_checkpoint_name: str = None
+ hr_sampler_name: str = None
+ hr_prompt: str = ''
+ hr_negative_prompt: str = ''
+
cached_hr_uc = [None, None]
cached_hr_c = [None, None]
- def __init__(self, enable_hr: bool = False, denoising_strength: float = 0.75, firstphase_width: int = 0, firstphase_height: int = 0, hr_scale: float = 2.0, hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, hr_checkpoint_name: str = None, hr_sampler_name: str = None, hr_prompt: str = '', hr_negative_prompt: str = '', **kwargs):
- super().__init__(**kwargs)
- self.enable_hr = enable_hr
- self.denoising_strength = denoising_strength
- self.hr_scale = hr_scale
- self.hr_upscaler = hr_upscaler
- self.hr_second_pass_steps = hr_second_pass_steps
- self.hr_resize_x = hr_resize_x
- self.hr_resize_y = hr_resize_y
- self.hr_upscale_to_x = hr_resize_x
- self.hr_upscale_to_y = hr_resize_y
- self.hr_checkpoint_name = hr_checkpoint_name
- self.hr_checkpoint_info = None
- self.hr_sampler_name = hr_sampler_name
- self.hr_prompt = hr_prompt
- self.hr_negative_prompt = hr_negative_prompt
- self.all_hr_prompts = None
- self.all_hr_negative_prompts = None
- self.latent_scale_mode = None
-
- if firstphase_width != 0 or firstphase_height != 0:
+ hr_checkpoint_info: dict = field(default=None, init=False)
+ hr_upscale_to_x: int = field(default=0, init=False)
+ hr_upscale_to_y: int = field(default=0, init=False)
+ truncate_x: int = field(default=0, init=False)
+ truncate_y: int = field(default=0, init=False)
+ applied_old_hires_behavior_to: tuple = field(default=None, init=False)
+ latent_scale_mode: dict = field(default=None, init=False)
+ hr_c: tuple | None = field(default=None, init=False)
+ hr_uc: tuple | None = field(default=None, init=False)
+ all_hr_prompts: list = field(default=None, init=False)
+ all_hr_negative_prompts: list = field(default=None, init=False)
+ hr_prompts: list = field(default=None, init=False)
+ hr_negative_prompts: list = field(default=None, init=False)
+ hr_extra_network_data: list = field(default=None, init=False)
+
+ def __post_init__(self):
+ super().__post_init__()
+
+ if self.firstphase_width != 0 or self.firstphase_height != 0:
self.hr_upscale_to_x = self.width
self.hr_upscale_to_y = self.height
- self.width = firstphase_width
- self.height = firstphase_height
-
- self.truncate_x = 0
- self.truncate_y = 0
- self.applied_old_hires_behavior_to = None
-
- self.hr_prompts = None
- self.hr_negative_prompts = None
- self.hr_extra_network_data = None
+ self.width = self.firstphase_width
+ self.height = self.firstphase_height
self.cached_hr_uc = StableDiffusionProcessingTxt2Img.cached_hr_uc
self.cached_hr_c = StableDiffusionProcessingTxt2Img.cached_hr_c
- self.hr_c = None
- self.hr_uc = None
def calculate_target_resolution(self):
if opts.use_old_hires_fix_width_height and self.applied_old_hires_behavior_to != (self.width, self.height):
@@ -1230,7 +1276,6 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): return super().get_conds()
-
def parse_extra_network_prompts(self):
res = super().parse_extra_network_prompts()
@@ -1243,32 +1288,37 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): return res
+@dataclass(repr=False)
class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
- sampler = None
-
- def __init__(self, init_images: list = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: float = None, mask: Any = None, mask_blur: int = None, mask_blur_x: int = 4, mask_blur_y: int = 4, inpainting_fill: int = 0, inpaint_full_res: bool = True, inpaint_full_res_padding: int = 0, inpainting_mask_invert: int = 0, initial_noise_multiplier: float = None, **kwargs):
- super().__init__(**kwargs)
-
- self.init_images = init_images
- self.resize_mode: int = resize_mode
- self.denoising_strength: float = denoising_strength
- self.image_cfg_scale: float = image_cfg_scale if shared.sd_model.cond_stage_key == "edit" else None
- self.init_latent = None
- self.image_mask = mask
- self.latent_mask = None
- self.mask_for_overlay = None
- self.mask_blur_x = mask_blur_x
- self.mask_blur_y = mask_blur_y
- if mask_blur is not None:
- self.mask_blur = mask_blur
- self.inpainting_fill = inpainting_fill
- self.inpaint_full_res = inpaint_full_res
- self.inpaint_full_res_padding = inpaint_full_res_padding
- self.inpainting_mask_invert = inpainting_mask_invert
- self.initial_noise_multiplier = opts.initial_noise_multiplier if initial_noise_multiplier is None else initial_noise_multiplier
+ init_images: list = None
+ resize_mode: int = 0
+ denoising_strength: float = 0.75
+ image_cfg_scale: float = None
+ mask: Any = None
+ mask_blur_x: int = 4
+ mask_blur_y: int = 4
+ mask_blur: int = None
+ inpainting_fill: int = 0
+ inpaint_full_res: bool = True
+ inpaint_full_res_padding: int = 0
+ inpainting_mask_invert: int = 0
+ initial_noise_multiplier: float = None
+ latent_mask: Image = None
+
+ image_mask: Any = field(default=None, init=False)
+
+ nmask: torch.Tensor = field(default=None, init=False)
+ image_conditioning: torch.Tensor = field(default=None, init=False)
+ init_img_hash: str = field(default=None, init=False)
+ mask_for_overlay: Image = field(default=None, init=False)
+ init_latent: torch.Tensor = field(default=None, init=False)
+
+ def __post_init__(self):
+ super().__post_init__()
+
+ self.image_mask = self.mask
self.mask = None
- self.nmask = None
- self.image_conditioning = None
+ self.initial_noise_multiplier = opts.initial_noise_multiplier if self.initial_noise_multiplier is None else self.initial_noise_multiplier
@property
def mask_blur(self):
@@ -1278,15 +1328,13 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): @mask_blur.setter
def mask_blur(self, value):
- self.mask_blur_x = value
- self.mask_blur_y = value
-
- @mask_blur.deleter
- def mask_blur(self):
- del self.mask_blur_x
- del self.mask_blur_y
+ if isinstance(value, int):
+ self.mask_blur_x = value
+ self.mask_blur_y = value
def init(self, all_prompts, all_seeds, all_subseeds):
+ self.image_cfg_scale: float = self.image_cfg_scale if shared.sd_model.cond_stage_key == "edit" else None
+
self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
crop_region = None
diff --git a/modules/processing_scripts/refiner.py b/modules/processing_scripts/refiner.py index 773ec5d0..7b946d05 100644 --- a/modules/processing_scripts/refiner.py +++ b/modules/processing_scripts/refiner.py @@ -41,15 +41,9 @@ class ScriptRefiner(scripts.Script): def before_process(self, p, enable_refiner, refiner_checkpoint, refiner_switch_at):
# the actual implementation is in sd_samplers_common.py, apply_refiner
- p.refiner_checkpoint_info = None
- p.refiner_switch_at = None
-
if not enable_refiner or refiner_checkpoint in (None, "", "None"):
- return
-
- refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(refiner_checkpoint)
- if refiner_checkpoint_info is None:
- raise Exception(f'Could not find checkpoint with name {refiner_checkpoint}')
-
- p.refiner_checkpoint_info = refiner_checkpoint_info
- p.refiner_switch_at = refiner_switch_at
+ p.refiner_checkpoint_info = None
+ p.refiner_switch_at = None
+ else:
+ p.refiner_checkpoint = refiner_checkpoint
+ p.refiner_switch_at = refiner_switch_at
diff --git a/modules/processing_scripts/seed.py b/modules/processing_scripts/seed.py new file mode 100644 index 00000000..cc90775a --- /dev/null +++ b/modules/processing_scripts/seed.py @@ -0,0 +1,100 @@ +import json
+
+import gradio as gr
+
+from modules import scripts, ui, errors
+from modules.shared import cmd_opts
+from modules.ui_components import ToolButton
+
+
+class ScriptSeed(scripts.ScriptBuiltin):
+ section = "seed"
+ create_group = False
+
+ def __init__(self):
+ self.seed = None
+ self.reuse_seed = None
+ self.reuse_subseed = None
+
+ def title(self):
+ return "Seed"
+
+ def show(self, is_img2img):
+ return scripts.AlwaysVisible
+
+ def ui(self, is_img2img):
+ with gr.Row(elem_id=self.elem_id("seed_row")):
+ with gr.Column(scale=1, min_width=205):
+ with gr.Row():
+ if cmd_opts.use_textbox_seed:
+ self.seed = gr.Textbox(label='Seed', value="", elem_id=self.elem_id("seed"), min_width=100)
+ else:
+ self.seed = gr.Number(label='Seed', value=-1, elem_id=self.elem_id("seed"), min_width=100, precision=0)
+
+ random_seed = ToolButton(ui.random_symbol, elem_id=self.elem_id("random_seed"), label='Random seed')
+ reuse_seed = ToolButton(ui.reuse_symbol, elem_id=self.elem_id("reuse_seed"), label='Reuse seed')
+
+ with gr.Column(scale=1, min_width=205):
+ with gr.Row():
+ subseed = gr.Number(label='Variation seed', value=-1, elem_id=self.elem_id("subseed"), min_width=100, precision=0)
+
+ random_subseed = ToolButton(ui.random_symbol, elem_id=self.elem_id("random_subseed"))
+ reuse_subseed = ToolButton(ui.reuse_symbol, elem_id=self.elem_id("reuse_subseed"))
+
+ with gr.Column(scale=2, min_width=100):
+ subseed_strength = gr.Slider(label='Variation strength', value=0.0, minimum=0, maximum=1, step=0.01, elem_id=self.elem_id("subseed_strength"))
+
+ random_seed.click(fn=None, _js="function(){setRandomSeed('" + self.elem_id("seed") + "')}", show_progress=False, inputs=[], outputs=[])
+ random_subseed.click(fn=None, _js="function(){setRandomSeed('" + self.elem_id("subseed") + "')}", show_progress=False, inputs=[], outputs=[])
+
+ self.infotext_fields = [
+ (self.seed, "Seed"),
+ (subseed, "Variation seed"),
+ (subseed_strength, "Variation seed strength"),
+ ]
+
+ self.on_after_component(lambda x: connect_reuse_seed(self.seed, reuse_seed, x.component, False), elem_id=f'generation_info_{self.tabname}')
+ self.on_after_component(lambda x: connect_reuse_seed(subseed, reuse_subseed, x.component, True), elem_id=f'generation_info_{self.tabname}')
+
+ return self.seed, subseed, subseed_strength
+
+ def before_process(self, p, seed, subseed, subseed_strength):
+ p.seed = seed
+
+ if subseed_strength > 0:
+ p.subseed = subseed
+ p.subseed_strength = subseed_strength
+
+
+def connect_reuse_seed(seed: gr.Number, reuse_seed: gr.Button, generation_info: gr.Textbox, is_subseed):
+ """ Connects a 'reuse (sub)seed' button's click event so that it copies last used
+ (sub)seed value from generation info the to the seed field. If copying subseed and subseed strength
+ was 0, i.e. no variation seed was used, it copies the normal seed value instead."""
+
+ def copy_seed(gen_info_string: str, index):
+ res = -1
+
+ try:
+ gen_info = json.loads(gen_info_string)
+ index -= gen_info.get('index_of_first_image', 0)
+
+ if is_subseed and gen_info.get('subseed_strength', 0) > 0:
+ all_subseeds = gen_info.get('all_subseeds', [-1])
+ res = all_subseeds[index if 0 <= index < len(all_subseeds) else 0]
+ else:
+ all_seeds = gen_info.get('all_seeds', [-1])
+ res = all_seeds[index if 0 <= index < len(all_seeds) else 0]
+
+ except json.decoder.JSONDecodeError:
+ if gen_info_string:
+ errors.report(f"Error parsing JSON generation info: {gen_info_string}")
+
+ return [res, gr.update()]
+
+ reuse_seed.click(
+ fn=copy_seed,
+ _js="(x, y) => [x, selected_gallery_index()]",
+ show_progress=False,
+ inputs=[generation_info, seed],
+ outputs=[seed, seed]
+ )
diff --git a/modules/scripts.py b/modules/scripts.py index 51da732a..c6459b45 100644 --- a/modules/scripts.py +++ b/modules/scripts.py @@ -3,6 +3,7 @@ import re import sys
import inspect
from collections import namedtuple
+from dataclasses import dataclass
import gradio as gr
@@ -21,6 +22,11 @@ class PostprocessBatchListArgs: self.images = images
+@dataclass
+class OnComponent:
+ component: gr.blocks.Block
+
+
class Script:
name = None
"""script's internal name derived from title"""
@@ -35,6 +41,7 @@ class Script: is_txt2img = False
is_img2img = False
+ tabname = None
group = None
"""A gr.Group component that has all script's UI inside it."""
@@ -55,6 +62,12 @@ class Script: api_info = None
"""Generated value of type modules.api.models.ScriptInfo with information about the script for API"""
+ on_before_component_elem_id = None
+ """list of callbacks to be called before a component with an elem_id is created"""
+
+ on_after_component_elem_id = None
+ """list of callbacks to be called after a component with an elem_id is created"""
+
def title(self):
"""this function should return the title of the script. This is what will be displayed in the dropdown menu."""
@@ -215,6 +228,28 @@ class Script: pass
+ def on_before_component(self, callback, *, elem_id):
+ """
+ Calls callback before a component is created. The callback function is called with a single argument of type OnComponent.
+
+ This function is an alternative to before_component in that it also cllows to run before a component is created, but
+ it doesn't require to be called for every created component - just for the one you need.
+ """
+ if self.on_before_component_elem_id is None:
+ self.on_before_component_elem_id = []
+
+ self.on_before_component_elem_id.append((elem_id, callback))
+
+ def on_after_component(self, callback, *, elem_id):
+ """
+ Calls callback after a component is created. The callback function is called with a single argument of type OnComponent.
+ """
+ if self.on_after_component_elem_id is None:
+ self.on_after_component_elem_id = []
+
+ self.on_after_component_elem_id.append((elem_id, callback))
+
+
def describe(self):
"""unused"""
return ""
@@ -236,6 +271,17 @@ class Script: pass
+class ScriptBuiltin(Script):
+
+ def elem_id(self, item_id):
+ """helper function to generate id for a HTML element, constructs final id out of tab and user-supplied item_id"""
+
+ need_tabname = self.show(True) == self.show(False)
+ tabname = ('img2img' if self.is_img2img else 'txt2txt') + "_" if need_tabname else ""
+
+ return f'{tabname}{item_id}'
+
+
current_basedir = paths.script_path
@@ -354,10 +400,17 @@ class ScriptRunner: self.selectable_scripts = []
self.alwayson_scripts = []
self.titles = []
+ self.title_map = {}
self.infotext_fields = []
self.paste_field_names = []
self.inputs = [None]
+ self.on_before_component_elem_id = {}
+ """dict of callbacks to be called before an element is created; key=elem_id, value=list of callbacks"""
+
+ self.on_after_component_elem_id = {}
+ """dict of callbacks to be called after an element is created; key=elem_id, value=list of callbacks"""
+
def initialize_scripts(self, is_img2img):
from modules import scripts_auto_postprocessing
@@ -372,6 +425,7 @@ class ScriptRunner: script.filename = script_data.path
script.is_txt2img = not is_img2img
script.is_img2img = is_img2img
+ script.tabname = "img2img" if is_img2img else "txt2img"
visibility = script.show(script.is_img2img)
@@ -446,6 +500,8 @@ class ScriptRunner: self.inputs = [None]
def setup_ui(self):
+ all_titles = [wrap_call(script.title, script.filename, "title") or script.filename for script in self.scripts]
+ self.title_map = {title.lower(): script for title, script in zip(all_titles, self.scripts)}
self.titles = [wrap_call(script.title, script.filename, "title") or f"{script.filename} [error]" for script in self.selectable_scripts]
self.setup_ui_for_section(None)
@@ -492,6 +548,17 @@ class ScriptRunner: self.infotext_fields.append((dropdown, lambda x: gr.update(value=x.get('Script', 'None'))))
self.infotext_fields.extend([(script.group, onload_script_visibility) for script in self.selectable_scripts])
+ for script in self.scripts:
+ for elem_id, callback in script.on_before_component_elem_id or []:
+ items = self.on_before_component_elem_id.get(elem_id, [])
+ items.append((callback, script))
+ self.on_before_component_elem_id[elem_id] = items
+
+ for elem_id, callback in script.on_after_component_elem_id or []:
+ items = self.on_after_component_elem_id.get(elem_id, [])
+ items.append((callback, script))
+ self.on_after_component_elem_id[elem_id] = items
+
return self.inputs
def run(self, p, *args):
@@ -585,6 +652,12 @@ class ScriptRunner: errors.report(f"Error running postprocess_image: {script.filename}", exc_info=True)
def before_component(self, component, **kwargs):
+ for callback, script in self.on_before_component_elem_id.get(kwargs.get("elem_id"), []):
+ try:
+ callback(OnComponent(component=component))
+ except Exception:
+ errors.report(f"Error running on_before_component: {script.filename}", exc_info=True)
+
for script in self.scripts:
try:
script.before_component(component, **kwargs)
@@ -592,12 +665,21 @@ class ScriptRunner: errors.report(f"Error running before_component: {script.filename}", exc_info=True)
def after_component(self, component, **kwargs):
+ for callback, script in self.on_after_component_elem_id.get(component.elem_id, []):
+ try:
+ callback(OnComponent(component=component))
+ except Exception:
+ errors.report(f"Error running on_after_component: {script.filename}", exc_info=True)
+
for script in self.scripts:
try:
script.after_component(component, **kwargs)
except Exception:
errors.report(f"Error running after_component: {script.filename}", exc_info=True)
+ def script(self, title):
+ return self.title_map.get(title.lower())
+
def reload_sources(self, cache):
for si, script in list(enumerate(self.scripts)):
args_from = script.args_from
@@ -616,7 +698,6 @@ class ScriptRunner: self.scripts[si].args_from = args_from
self.scripts[si].args_to = args_to
-
def before_hr(self, p):
for script in self.alwayson_scripts:
try:
|