Revert "Merge pull request #7931 from space-nuko/img2img-enhance"

This reverts commit 4268759370, reversing
changes made to 1b63afbedc.
This commit is contained in:
AUTOMATIC 2023-03-28 20:36:57 +03:00
parent 4268759370
commit 433b3ab701
7 changed files with 13 additions and 131 deletions

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@ -132,14 +132,7 @@ function create_tab_index_args(tabId, args){
function get_img2img_tab_index() { function get_img2img_tab_index() {
let res = args_to_array(arguments) let res = args_to_array(arguments)
res.splice(-2) // gradio also sends outputs to the arguments, pop them off res.splice(-2)
res[0] = get_tab_index('mode_img2img')
return res
}
function get_img2img_tab_index_for_res_preview() {
let res = args_to_array(arguments)
res.splice(-1) // gradio also sends outputs to the arguments, pop them off
res[0] = get_tab_index('mode_img2img') res[0] = get_tab_index('mode_img2img')
return res return res
} }
@ -368,16 +361,3 @@ function selectCheckpoint(name){
desiredCheckpointName = name; desiredCheckpointName = name;
gradioApp().getElementById('change_checkpoint').click() gradioApp().getElementById('change_checkpoint').click()
} }
function onCalcResolutionImg2Img(mode, scale, width, height, resize_mode, init_img, sketch, init_img_with_mask, inpaint_color_sketch, init_img_inpaint){
i2iScale = gradioApp().getElementById('img2img_scale')
i2iWidth = gradioApp().getElementById('img2img_width')
i2iHeight = gradioApp().getElementById('img2img_height')
setInactive(i2iScale, scale == 1)
setInactive(i2iWidth, scale > 1)
setInactive(i2iHeight, scale > 1)
return [];
}

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@ -282,9 +282,6 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
res["Hires resize-1"] = 0 res["Hires resize-1"] = 0
res["Hires resize-2"] = 0 res["Hires resize-2"] = 0
if "Img2Img upscale" not in res:
res["Img2Img upscale"] = 1
restore_old_hires_fix_params(res) restore_old_hires_fix_params(res)
return res return res

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@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
processed_image.save(os.path.join(output_dir, filename)) processed_image.save(os.path.join(output_dir, filename))
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_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, 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, height: int, width: int, scale: float, upscaler: str, 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, *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_index: int, mask_blur: int, mask_alpha: float, inpainting_fill: int, restore_faces: bool, tiling: bool, 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, height: int, width: int, 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, *args):
override_settings = create_override_settings_dict(override_settings_texts) override_settings = create_override_settings_dict(override_settings_texts)
is_batch = mode == 5 is_batch = mode == 5
@ -149,8 +149,6 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
inpaint_full_res_padding=inpaint_full_res_padding, inpaint_full_res_padding=inpaint_full_res_padding,
inpainting_mask_invert=inpainting_mask_invert, inpainting_mask_invert=inpainting_mask_invert,
override_settings=override_settings, override_settings=override_settings,
scale=scale,
upscaler=upscaler,
) )
p.scripts = modules.scripts.scripts_txt2img p.scripts = modules.scripts.scripts_txt2img

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@ -946,7 +946,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
class StableDiffusionProcessingImg2Img(StableDiffusionProcessing): class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
sampler = None sampler = None
def __init__(self, init_images: Optional[list] = None, resize_mode: int = 0, denoising_strength: float = 0.75, image_cfg_scale: Optional[float] = None, mask: Any = None, mask_blur: 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: Optional[float] = None, scale: float = 0, upscaler: Optional[str] = None, **kwargs): 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 = 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) super().__init__(**kwargs)
self.init_images = init_images self.init_images = init_images
@ -966,37 +966,11 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.mask = None self.mask = None
self.nmask = None self.nmask = None
self.image_conditioning = None self.image_conditioning = None
self.scale = scale
self.upscaler = upscaler
def get_final_size(self):
if self.scale > 1:
img = self.init_images[0]
width = int(img.width * self.scale)
height = int(img.height * self.scale)
return width, height
else:
return self.width, self.height
def init(self, all_prompts, all_seeds, all_subseeds): def init(self, all_prompts, all_seeds, all_subseeds):
self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model) self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
crop_region = None crop_region = None
if self.scale > 1:
self.extra_generation_params["Img2Img upscale"] = self.scale
# Non-latent upscalers are run before sampling
# Latent upscalers are run during sampling
init_upscaler = None
if self.upscaler is not None:
self.extra_generation_params["Img2Img upscaler"] = self.upscaler
if self.upscaler not in shared.latent_upscale_modes:
assert len([x for x in shared.sd_upscalers if x.name == self.upscaler]) > 0, f"could not find upscaler named {self.upscaler}"
init_upscaler = self.upscaler
self.width, self.height = self.get_final_size()
image_mask = self.image_mask image_mask = self.image_mask
if image_mask is not None: if image_mask is not None:
@ -1019,7 +993,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
image_mask = images.resize_image(2, mask, self.width, self.height) image_mask = images.resize_image(2, mask, self.width, self.height)
self.paste_to = (x1, y1, x2-x1, y2-y1) self.paste_to = (x1, y1, x2-x1, y2-y1)
else: else:
image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height, init_upscaler) image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height)
np_mask = np.array(image_mask) np_mask = np.array(image_mask)
np_mask = np.clip((np_mask.astype(np.float32)) * 2, 0, 255).astype(np.uint8) np_mask = np.clip((np_mask.astype(np.float32)) * 2, 0, 255).astype(np.uint8)
self.mask_for_overlay = Image.fromarray(np_mask) self.mask_for_overlay = Image.fromarray(np_mask)
@ -1036,7 +1010,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
image = images.flatten(img, opts.img2img_background_color) image = images.flatten(img, opts.img2img_background_color)
if crop_region is None and self.resize_mode != 3: if crop_region is None and self.resize_mode != 3:
image = images.resize_image(self.resize_mode, image, self.width, self.height, init_upscaler) image = images.resize_image(self.resize_mode, image, self.width, self.height)
if image_mask is not None: if image_mask is not None:
image_masked = Image.new('RGBa', (image.width, image.height)) image_masked = Image.new('RGBa', (image.width, image.height))
@ -1081,9 +1055,8 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image)) self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image))
latent_scale_mode = shared.latent_upscale_modes.get(self.upscaler, None) if self.upscaler is not None else shared.latent_upscale_modes.get(shared.latent_upscale_default_mode, "nearest") if self.resize_mode == 3:
if latent_scale_mode is not None: self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode=latent_scale_mode["mode"], antialias=latent_scale_mode["antialias"])
if image_mask is not None: if image_mask is not None:
init_mask = latent_mask init_mask = latent_mask

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@ -15,7 +15,6 @@ import warnings
import gradio as gr import gradio as gr
import gradio.routes import gradio.routes
import gradio.utils import gradio.utils
from gradio.events import Releaseable
import numpy as np import numpy as np
from PIL import Image, PngImagePlugin from PIL import Image, PngImagePlugin
from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
@ -128,26 +127,6 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>" return f"resize: from <span class='resolution'>{p.width}x{p.height}</span> to <span class='resolution'>{p.hr_resize_x or p.hr_upscale_to_x}x{p.hr_resize_y or p.hr_upscale_to_y}</span>"
def calc_resolution_img2img(mode, scale, resize_x, resize_y, resize_mode, *i2i_images):
init_img = None
if mode in {0, 1, 3, 4}:
init_img = i2i_images[mode]
elif mode == 2:
init_img = i2i_images[mode]["image"]
if not init_img:
return ""
if scale > 1:
width = int(init_img.width * scale)
height = int(init_img.height * scale)
else:
width = resize_x
height = resize_y
return f"resize: from <span class='resolution'>{init_img.width}x{init_img.height}</span> to <span class='resolution'>{width}x{height}</span>"
def apply_styles(prompt, prompt_neg, styles): def apply_styles(prompt, prompt_neg, styles):
prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles) prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles)
prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles) prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles)
@ -756,7 +735,7 @@ def create_ui():
) )
with FormRow(): with FormRow():
resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill"], type="index", value="Just resize") resize_mode = gr.Radio(label="Resize mode", elem_id="resize_mode", choices=["Just resize", "Crop and resize", "Resize and fill", "Just resize (latent upscale)"], type="index", value="Just resize")
for category in ordered_ui_categories(): for category in ordered_ui_categories():
if category == "sampler": if category == "sampler":
@ -765,11 +744,6 @@ def create_ui():
elif category == "dimensions": elif category == "dimensions":
with FormRow(): with FormRow():
with gr.Column(elem_id="img2img_column_size", scale=4): with gr.Column(elem_id="img2img_column_size", scale=4):
with FormRow(variant="compact"):
final_resolution = FormHTML(value="", elem_id="img2img_finalres", label="Upscaled resolution", interactive=False)
with FormRow(variant="compact"):
scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=1.0, elem_id="img2img_scale")
with FormRow(variant="compact"):
width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width") width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height") height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
@ -786,8 +760,6 @@ def create_ui():
with FormRow(): with FormRow():
cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale") cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=shared.sd_model and shared.sd_model.cond_stage_key == "edit") image_cfg_scale = gr.Slider(minimum=0, maximum=3.0, step=0.05, label='Image CFG Scale', value=1.5, elem_id="img2img_image_cfg_scale", visible=shared.sd_model and shared.sd_model.cond_stage_key == "edit")
with FormRow():
upscaler = gr.Dropdown(label="Upscaler", elem_id="img2img_upscaler", choices=[*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]], value=shared.latent_upscale_default_mode)
denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength") denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
elif category == "seed": elif category == "seed":
@ -841,39 +813,6 @@ def create_ui():
outputs=[inpaint_controls, mask_alpha], outputs=[inpaint_controls, mask_alpha],
) )
img2img_resolution_preview_inputs = [dummy_component, # filled in by selected img2img tab index in _js
scale, width, height, resize_mode,
init_img, sketch, init_img_with_mask, inpaint_color_sketch, init_img_inpaint]
for input in img2img_resolution_preview_inputs[1:]:
if isinstance(input, Releaseable):
input.release(
fn=calc_resolution_img2img,
_js="get_img2img_tab_index_for_res_preview",
inputs=img2img_resolution_preview_inputs,
outputs=[final_resolution],
show_progress=False,
).success(
None,
_js="onCalcResolutionImg2Img",
inputs=img2img_resolution_preview_inputs,
outputs=[],
show_progress=False,
)
else:
input.change(
fn=calc_resolution_img2img,
_js="get_img2img_tab_index_for_res_preview",
inputs=img2img_resolution_preview_inputs,
outputs=[final_resolution],
show_progress=False,
).success(
None,
_js="onCalcResolutionImg2Img",
inputs=img2img_resolution_preview_inputs,
outputs=[],
show_progress=False,
)
img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples) img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False) connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
@ -922,8 +861,6 @@ def create_ui():
subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox, subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
height, height,
width, width,
scale,
upscaler,
resize_mode, resize_mode,
inpaint_full_res, inpaint_full_res,
inpaint_full_res_padding, inpaint_full_res_padding,
@ -1009,8 +946,6 @@ def create_ui():
(seed, "Seed"), (seed, "Seed"),
(width, "Size-1"), (width, "Size-1"),
(height, "Size-2"), (height, "Size-2"),
(scale, "Img2Img upscale"),
(upscaler, "Img2Img upscaler"),
(batch_size, "Batch size"), (batch_size, "Batch size"),
(subseed, "Variation seed"), (subseed, "Variation seed"),
(subseed_strength, "Variation seed strength"), (subseed_strength, "Variation seed strength"),

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@ -220,7 +220,6 @@ axis_options = [
AxisOption("Clip skip", int, apply_clip_skip), AxisOption("Clip skip", int, apply_clip_skip),
AxisOption("Denoising", float, apply_field("denoising_strength")), AxisOption("Denoising", float, apply_field("denoising_strength")),
AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]), AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
AxisOptionImg2Img("Upscaler", str, apply_field("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")), 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("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)), AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)),

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@ -287,13 +287,13 @@ button.custom-button{
border-radius: 0 0.5rem 0.5rem 0; border-radius: 0 0.5rem 0.5rem 0;
} }
#txtimg_hr_finalres, #img2img_finalres { #txtimg_hr_finalres{
min-height: 0 !important; min-height: 0 !important;
padding: .625rem .75rem; padding: .625rem .75rem;
margin-left: -0.75em margin-left: -0.75em
} }
#txtimg_hr_finalres .resolution, #img2img_finalres .resolution{ #txtimg_hr_finalres .resolution{
font-weight: bold; font-weight: bold;
} }