mirror of
https://github.com/openvinotoolkit/stable-diffusion-webui.git
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Merge pull request #7931 from space-nuko/img2img-enhance
Add `Upscale by` and `Upscaler` options to img2img
This commit is contained in:
AUTOMATIC1111
GitHub
commit
4268759370
@ -132,7 +132,14 @@ function create_tab_index_args(tabId, args){
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function get_img2img_tab_index() {
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let res = args_to_array(arguments)
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res.splice(-2)
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res.splice(-2) // gradio also sends outputs to the arguments, pop them off
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res[0] = get_tab_index('mode_img2img')
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return res
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}
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function get_img2img_tab_index_for_res_preview() {
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let res = args_to_array(arguments)
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res.splice(-1) // gradio also sends outputs to the arguments, pop them off
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res[0] = get_tab_index('mode_img2img')
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return res
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}
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@ -361,3 +368,16 @@ function selectCheckpoint(name){
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desiredCheckpointName = name;
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gradioApp().getElementById('change_checkpoint').click()
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}
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function onCalcResolutionImg2Img(mode, scale, width, height, resize_mode, init_img, sketch, init_img_with_mask, inpaint_color_sketch, init_img_inpaint){
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i2iScale = gradioApp().getElementById('img2img_scale')
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i2iWidth = gradioApp().getElementById('img2img_width')
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i2iHeight = gradioApp().getElementById('img2img_height')
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setInactive(i2iScale, scale == 1)
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setInactive(i2iWidth, scale > 1)
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setInactive(i2iHeight, scale > 1)
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return [];
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}
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@ -282,6 +282,9 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
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res["Hires resize-1"] = 0
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res["Hires resize-2"] = 0
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if "Img2Img upscale" not in res:
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res["Img2Img upscale"] = 1
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restore_old_hires_fix_params(res)
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return res
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@ -78,7 +78,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args):
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processed_image.save(os.path.join(output_dir, filename))
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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):
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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):
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override_settings = create_override_settings_dict(override_settings_texts)
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is_batch = mode == 5
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@ -149,6 +149,8 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
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inpaint_full_res_padding=inpaint_full_res_padding,
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inpainting_mask_invert=inpainting_mask_invert,
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override_settings=override_settings,
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scale=scale,
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upscaler=upscaler,
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)
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p.scripts = modules.scripts.scripts_txt2img
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@ -946,7 +946,7 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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sampler = None
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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):
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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):
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super().__init__(**kwargs)
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self.init_images = init_images
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@ -966,11 +966,37 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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self.mask = None
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self.nmask = None
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self.image_conditioning = None
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self.scale = scale
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self.upscaler = upscaler
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def get_final_size(self):
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if self.scale > 1:
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img = self.init_images[0]
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width = int(img.width * self.scale)
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height = int(img.height * self.scale)
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return width, height
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else:
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return self.width, self.height
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def init(self, all_prompts, all_seeds, all_subseeds):
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self.sampler = sd_samplers.create_sampler(self.sampler_name, self.sd_model)
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crop_region = None
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if self.scale > 1:
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self.extra_generation_params["Img2Img upscale"] = self.scale
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# Non-latent upscalers are run before sampling
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# Latent upscalers are run during sampling
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init_upscaler = None
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if self.upscaler is not None:
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self.extra_generation_params["Img2Img upscaler"] = self.upscaler
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if self.upscaler not in shared.latent_upscale_modes:
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assert len([x for x in shared.sd_upscalers if x.name == self.upscaler]) > 0, f"could not find upscaler named {self.upscaler}"
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init_upscaler = self.upscaler
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self.width, self.height = self.get_final_size()
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image_mask = self.image_mask
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if image_mask is not None:
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@ -993,7 +1019,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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image_mask = images.resize_image(2, mask, self.width, self.height)
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self.paste_to = (x1, y1, x2-x1, y2-y1)
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else:
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image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height)
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image_mask = images.resize_image(self.resize_mode, image_mask, self.width, self.height, init_upscaler)
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np_mask = np.array(image_mask)
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np_mask = np.clip((np_mask.astype(np.float32)) * 2, 0, 255).astype(np.uint8)
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self.mask_for_overlay = Image.fromarray(np_mask)
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@ -1010,7 +1036,7 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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image = images.flatten(img, opts.img2img_background_color)
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if crop_region is None and self.resize_mode != 3:
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image = images.resize_image(self.resize_mode, image, self.width, self.height)
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image = images.resize_image(self.resize_mode, image, self.width, self.height, init_upscaler)
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if image_mask is not None:
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image_masked = Image.new('RGBa', (image.width, image.height))
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@ -1055,8 +1081,9 @@ class StableDiffusionProcessingImg2Img(StableDiffusionProcessing):
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self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image))
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if self.resize_mode == 3:
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self.init_latent = torch.nn.functional.interpolate(self.init_latent, size=(self.height // opt_f, self.width // opt_f), mode="bilinear")
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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")
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if latent_scale_mode is not None:
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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"])
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if image_mask is not None:
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init_mask = latent_mask
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@ -15,6 +15,7 @@ import warnings
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import gradio as gr
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import gradio.routes
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import gradio.utils
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from gradio.events import Releaseable
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import numpy as np
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from PIL import Image, PngImagePlugin
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from modules.call_queue import wrap_gradio_gpu_call, wrap_queued_call, wrap_gradio_call
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@ -127,6 +128,26 @@ def calc_resolution_hires(enable, width, height, hr_scale, hr_resize_x, hr_resiz
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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>"
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def calc_resolution_img2img(mode, scale, resize_x, resize_y, resize_mode, *i2i_images):
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init_img = None
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if mode in {0, 1, 3, 4}:
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init_img = i2i_images[mode]
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elif mode == 2:
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init_img = i2i_images[mode]["image"]
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if not init_img:
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return ""
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if scale > 1:
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width = int(init_img.width * scale)
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height = int(init_img.height * scale)
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else:
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width = resize_x
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height = resize_y
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return f"resize: from <span class='resolution'>{init_img.width}x{init_img.height}</span> to <span class='resolution'>{width}x{height}</span>"
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def apply_styles(prompt, prompt_neg, styles):
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prompt = shared.prompt_styles.apply_styles_to_prompt(prompt, styles)
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prompt_neg = shared.prompt_styles.apply_negative_styles_to_prompt(prompt_neg, styles)
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@ -735,7 +756,7 @@ def create_ui():
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)
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with FormRow():
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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")
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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")
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for category in ordered_ui_categories():
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if category == "sampler":
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@ -744,8 +765,13 @@ def create_ui():
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elif category == "dimensions":
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with FormRow():
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with gr.Column(elem_id="img2img_column_size", scale=4):
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width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
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height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
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with FormRow(variant="compact"):
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final_resolution = FormHTML(value="", elem_id="img2img_finalres", label="Upscaled resolution", interactive=False)
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with FormRow(variant="compact"):
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scale = gr.Slider(minimum=1.0, maximum=4.0, step=0.05, label="Upscale by", value=1.0, elem_id="img2img_scale")
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with FormRow(variant="compact"):
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width = gr.Slider(minimum=64, maximum=2048, step=8, label="Width", value=512, elem_id="img2img_width")
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height = gr.Slider(minimum=64, maximum=2048, step=8, label="Height", value=512, elem_id="img2img_height")
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with gr.Column(elem_id="img2img_dimensions_row", scale=1, elem_classes="dimensions-tools"):
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res_switch_btn = ToolButton(value=switch_values_symbol, elem_id="img2img_res_switch_btn")
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@ -760,7 +786,9 @@ def create_ui():
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with FormRow():
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cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0, elem_id="img2img_cfg_scale")
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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")
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denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
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with FormRow():
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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)
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denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75, elem_id="img2img_denoising_strength")
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elif category == "seed":
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seed, reuse_seed, subseed, reuse_subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox = create_seed_inputs('img2img')
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@ -813,6 +841,39 @@ def create_ui():
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outputs=[inpaint_controls, mask_alpha],
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)
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img2img_resolution_preview_inputs = [dummy_component, # filled in by selected img2img tab index in _js
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scale, width, height, resize_mode,
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init_img, sketch, init_img_with_mask, inpaint_color_sketch, init_img_inpaint]
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for input in img2img_resolution_preview_inputs[1:]:
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if isinstance(input, Releaseable):
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input.release(
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fn=calc_resolution_img2img,
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_js="get_img2img_tab_index_for_res_preview",
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inputs=img2img_resolution_preview_inputs,
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outputs=[final_resolution],
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show_progress=False,
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).success(
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None,
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_js="onCalcResolutionImg2Img",
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inputs=img2img_resolution_preview_inputs,
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outputs=[],
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show_progress=False,
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)
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else:
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input.change(
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fn=calc_resolution_img2img,
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_js="get_img2img_tab_index_for_res_preview",
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inputs=img2img_resolution_preview_inputs,
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outputs=[final_resolution],
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show_progress=False,
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).success(
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None,
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_js="onCalcResolutionImg2Img",
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inputs=img2img_resolution_preview_inputs,
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outputs=[],
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show_progress=False,
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)
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img2img_gallery, generation_info, html_info, html_log = create_output_panel("img2img", opts.outdir_img2img_samples)
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connect_reuse_seed(seed, reuse_seed, generation_info, dummy_component, is_subseed=False)
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@ -861,6 +922,8 @@ def create_ui():
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subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w, seed_checkbox,
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height,
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width,
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scale,
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upscaler,
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resize_mode,
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inpaint_full_res,
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inpaint_full_res_padding,
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@ -946,6 +1009,8 @@ def create_ui():
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(seed, "Seed"),
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(width, "Size-1"),
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(height, "Size-2"),
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(scale, "Img2Img upscale"),
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(upscaler, "Img2Img upscaler"),
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(batch_size, "Batch size"),
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(subseed, "Variation seed"),
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(subseed_strength, "Variation seed strength"),
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@ -220,6 +220,7 @@ axis_options = [
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AxisOption("Clip skip", int, apply_clip_skip),
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AxisOption("Denoising", float, apply_field("denoising_strength")),
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AxisOptionTxt2Img("Hires upscaler", str, apply_field("hr_upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
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AxisOptionImg2Img("Upscaler", str, apply_field("upscaler"), choices=lambda: [*shared.latent_upscale_modes, *[x.name for x in shared.sd_upscalers]]),
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AxisOptionImg2Img("Cond. Image Mask Weight", float, apply_field("inpainting_mask_weight")),
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AxisOption("VAE", str, apply_vae, cost=0.7, choices=lambda: list(sd_vae.vae_dict)),
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AxisOption("Styles", str, apply_styles, choices=lambda: list(shared.prompt_styles.styles)),
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@ -287,13 +287,13 @@ button.custom-button{
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border-radius: 0 0.5rem 0.5rem 0;
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}
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#txtimg_hr_finalres{
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#txtimg_hr_finalres, #img2img_finalres {
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min-height: 0 !important;
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padding: .625rem .75rem;
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margin-left: -0.75em
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}
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#txtimg_hr_finalres .resolution{
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#txtimg_hr_finalres .resolution, #img2img_finalres .resolution{
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font-weight: bold;
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}
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