face restoration and tiling moved to settings - use "Options in main UI" setting if you want them back

modules/generation_parameters_copypaste.py

@@ -343,6 +343,8 @@ infotext_to_setting_name_mapping = [
     ('Pad conds', 'pad_cond_uncond'),
     ('VAE Encoder', 'sd_vae_encode_method'),
     ('VAE Decoder', 'sd_vae_decode_method'),
+    ('Tiling', 'tiling'),
+    ('Face restoration', 'face_restoration'),
 ]
 
 

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, 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, 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, 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):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     is_batch = mode == 5
@@ -179,8 +179,6 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
         cfg_scale=cfg_scale,
         width=width,
         height=height,
-        restore_faces=restore_faces,
-        tiling=tiling,
         init_images=[image],
         mask=mask,
         mask_blur=mask_blur,

modules/processing.py

@@ -111,7 +111,7 @@ class StableDiffusionProcessing:
     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 = False, tiling: bool = False, 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):
+    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:
             print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
 
@@ -564,7 +564,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "CFG scale": p.cfg_scale,
         "Image CFG scale": getattr(p, 'image_cfg_scale', None),
         "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),
+        "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),
@@ -580,6 +580,7 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" and opts.randn_source != "NV" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
+        "Tiling": "True" if p.tiling else None,
         **p.extra_generation_params,
         "Version": program_version() if opts.add_version_to_infotext else None,
         "User": p.user if opts.add_user_name_to_info else None,
@@ -645,6 +646,12 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
     seed = get_fixed_seed(p.seed)
     subseed = get_fixed_seed(p.subseed)
 
+    if p.restore_faces is None:
+        p.restore_faces = opts.face_restoration
+
+    if p.tiling is None:
+        p.tiling = opts.tiling
+
     modules.sd_hijack.model_hijack.apply_circular(p.tiling)
     modules.sd_hijack.model_hijack.clear_comments()
 

modules/shared_options.py

@@ -92,6 +92,7 @@ options_templates.update(options_section(('upscaling', "Upscaling"), {
 }))
 
 options_templates.update(options_section(('face-restoration', "Face restoration"), {
+    "face_restoration": OptionInfo(False, "Restore faces").info("will use a third-party model on generation result to reconstruct faces"),
     "face_restoration_model": OptionInfo("CodeFormer", "Face restoration model", gr.Radio, lambda: {"choices": [x.name() for x in shared.face_restorers]}),
     "code_former_weight": OptionInfo(0.5, "CodeFormer weight", gr.Slider, {"minimum": 0, "maximum": 1, "step": 0.01}).info("0 = maximum effect; 1 = minimum effect"),
     "face_restoration_unload": OptionInfo(False, "Move face restoration model from VRAM into RAM after processing"),
@@ -138,6 +139,7 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
     "CLIP_stop_at_last_layers": OptionInfo(1, "Clip skip", gr.Slider, {"minimum": 1, "maximum": 12, "step": 1}).link("wiki", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features#clip-skip").info("ignore last layers of CLIP network; 1 ignores none, 2 ignores one layer"),
     "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
     "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"),
+    "tiling": OptionInfo(False, "Tiling").info("produce a tileable picture"),
 }))
 
 options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), {

modules/txt2img.py

@@ -9,7 +9,7 @@ from modules.ui import plaintext_to_html
 import gradio as gr
 
 
-def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_name: str, restore_faces: bool, tiling: bool, n_iter: int, batch_size: int, cfg_scale: 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, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_checkpoint_name: str, hr_sampler_name: str, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args):
+def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, steps: int, sampler_name: str, n_iter: int, batch_size: int, cfg_scale: 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, enable_hr: bool, denoising_strength: float, hr_scale: float, hr_upscaler: str, hr_second_pass_steps: int, hr_resize_x: int, hr_resize_y: int, hr_checkpoint_name: str, hr_sampler_name: str, hr_prompt: str, hr_negative_prompt, override_settings_texts, request: gr.Request, *args):
     override_settings = create_override_settings_dict(override_settings_texts)
 
     p = processing.StableDiffusionProcessingTxt2Img(
@@ -32,8 +32,6 @@ def txt2img(id_task: str, prompt: str, negative_prompt: str, prompt_styles, step
         cfg_scale=cfg_scale,
         width=width,
         height=height,
-        restore_faces=restore_faces,
-        tiling=tiling,
         enable_hr=enable_hr,
         denoising_strength=denoising_strength if enable_hr else None,
         hr_scale=hr_scale,

modules/ui.py

@@ -432,8 +432,7 @@ def create_ui():
 
                     elif category == "checkboxes":
                         with FormRow(elem_classes="checkboxes-row", variant="compact"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="txt2img_restore_faces")
+                            pass
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="txt2img_tiling")
 
                     elif category == "hires_fix":
                         with InputAccordion(False, label="Hires. fix") as enable_hr:
@@ -516,8 +515,6 @@ def create_ui():
                     toprow.ui_styles.dropdown,
                     steps,
                     sampler_name,
-                    restore_faces,
-                    tiling,
                     batch_count,
                     batch_size,
                     cfg_scale,
@@ -572,7 +569,6 @@ def create_ui():
                 (toprow.negative_prompt, "Negative prompt"),
                 (steps, "Steps"),
                 (sampler_name, "Sampler"),
-                (restore_faces, "Face restoration"),
                 (cfg_scale, "CFG scale"),
                 (seed, "Seed"),
                 (width, "Size-1"),
@@ -792,8 +788,7 @@ def create_ui():
 
                     elif category == "checkboxes":
                         with FormRow(elem_classes="checkboxes-row", variant="compact"):
-                            restore_faces = gr.Checkbox(label='Restore faces', value=False, visible=len(shared.face_restorers) > 1, elem_id="img2img_restore_faces")
+                            pass
-                            tiling = gr.Checkbox(label='Tiling', value=False, elem_id="img2img_tiling")
 
                     elif category == "batch":
                         if not opts.dimensions_and_batch_together:
@@ -866,8 +861,6 @@ def create_ui():
                     mask_blur,
                     mask_alpha,
                     inpainting_fill,
-                    restore_faces,
-                    tiling,
                     batch_count,
                     batch_size,
                     cfg_scale,
@@ -959,7 +952,6 @@ def create_ui():
                 (toprow.negative_prompt, "Negative prompt"),
                 (steps, "Steps"),
                 (sampler_name, "Sampler"),
-                (restore_faces, "Face restoration"),
                 (cfg_scale, "CFG scale"),
                 (image_cfg_scale, "Image CFG scale"),
                 (seed, "Seed"),