fix adetailer

Signed-off-by: Vladimir Mandic <mandic00@live.com>

modules/processing.py

@@ -354,30 +354,37 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 else:
                     sample = validate_sample(sample)
                     image = Image.fromarray(sample)
-                sample = face_restoration.restore_faces(sample, p)
+                if p.restore_faces:
+                    p.ops.append('restore')
+                    if not p.do_not_save_samples and shared.opts.save_images_before_detailer:
+                        info = create_infotext(p, p.prompts, p.seeds, p.subseeds, index=i)
+                        images.save_image(Image.fromarray(sample), path=p.outpath_samples, basename="", seed=p.seeds[i], prompt=p.prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix="-before-restore")
+                    sample = face_restoration.restore_faces(sample, p)
+                    if sample is not None:
+                        image = Image.fromarray(sample)
                 if p.detailer:
+                    p.ops.append('detailer')
                     if not p.do_not_save_samples and shared.opts.save_images_before_detailer:
                         info = create_infotext(p, p.prompts, p.seeds, p.subseeds, index=i)
                         images.save_image(Image.fromarray(sample), path=p.outpath_samples, basename="", seed=p.seeds[i], prompt=p.prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix="-before-detailer")
-                    p.ops.append('detailer')
                     sample = detailer.detail(sample, p)
                     if sample is not None:
                         image = Image.fromarray(sample)
-                if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
-                    pp = scripts.PostprocessImageArgs(image)
-                    p.scripts.postprocess_image(p, pp)
-                    if pp.image is not None:
-                        image = pp.image
                 if p.color_corrections is not None and i < len(p.color_corrections):
+                    p.ops.append('color')
                     if not p.do_not_save_samples and shared.opts.save_images_before_color_correction:
                         orig = p.color_corrections
                         p.color_corrections = None
                         p.color_corrections = orig
                         image_without_cc = apply_overlay(image, p.paste_to, i, p.overlay_images)
                         info = create_infotext(p, p.prompts, p.seeds, p.subseeds, index=i)
                         images.save_image(image_without_cc, path=p.outpath_samples, basename="", seed=p.seeds[i], prompt=p.prompts[i], extension=shared.opts.samples_format, info=info, p=p, suffix="-before-color-correct")
-                    p.ops.append('color')
                     image = apply_color_correction(p.color_corrections[i], image)
+                if p.scripts is not None and isinstance(p.scripts, scripts.ScriptRunner):
+                    pp = scripts.PostprocessImageArgs(image)
+                    p.scripts.postprocess_image(p, pp)
+                    if pp.image is not None:
+                        image = pp.image
                 if shared.opts.mask_apply_overlay:
                     image = apply_overlay(image, p.paste_to, i, p.overlay_images)
 

modules/processing_class.py

@@ -20,7 +20,68 @@ class StableDiffusionProcessing:
     """
     The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
     """
-    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, hr_sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, image_cfg_scale: float = None, clip_skip: int = 1, width: int = 512, height: int = 512, full_quality: bool = True, detailer: bool = False, tiling: bool = False, hidiffusion: 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, diffusers_guidance_rescale: float = 0.7, pag_scale: float = 0.0, pag_adaptive: float = 0.5, cfg_end: float = 1, resize_mode: int = 0, resize_name: str = 'None', resize_context: str = 'None', scale_by: float = 0, selected_scale_tab: int = 0, hdr_mode: int = 0, hdr_brightness: float = 0, hdr_color: float = 0, hdr_sharpen: float = 0, hdr_clamp: bool = False, hdr_boundary: float = 4.0, hdr_threshold: float = 0.95, hdr_maximize: bool = False, hdr_max_center: float = 0.6, hdr_max_boundry: float = 1.0, hdr_color_picker: str = None, hdr_tint_ratio: float = 0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None): # pylint: disable=unused-argument
+    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,
+                 hr_sampler_name: str = None,
+                 batch_size: int = 1,
+                 n_iter: int = 1,
+                 steps: int = 50,
+                 cfg_scale: float = 7.0,
+                 image_cfg_scale: float = None,
+                 clip_skip: int = 1,
+                 width: int = 512,
+                 height: int = 512,
+                 full_quality: bool = True,
+                 detailer: bool = False,
+                 restore_faces: bool = False,
+                 tiling: bool = False,
+                 hidiffusion: 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,
+                 diffusers_guidance_rescale: float = 0.7,
+                 pag_scale: float = 0.0,
+                 pag_adaptive: float = 0.5,
+                 cfg_end: float = 1,
+                 resize_mode: int = 0,
+                 resize_name: str = 'None',
+                 resize_context: str = 'None',
+                 scale_by: float = 0,
+                 selected_scale_tab: int = 0,
+                 hdr_mode: int = 0,
+                 hdr_brightness: float = 0,
+                 hdr_color: float = 0,
+                 hdr_sharpen: float = 0,
+                 hdr_clamp: bool = False,
+                 hdr_boundary: float = 4.0,
+                 hdr_threshold: float = 0.95,
+                 hdr_maximize: bool = False,
+                 hdr_max_center: float = 0.6,
+                 hdr_max_boundry: float = 1.0,
+                 hdr_color_picker: str = None,
+                 hdr_tint_ratio: float = 0,
+                 override_settings: Dict[str, Any] = None,
+                 override_settings_restore_afterwards: bool = True,
+                 sampler_index: int = None,
+                 script_args: list = None
+                ): # pylint: disable=unused-argument
+
         self.state: str = ''
         self.skip = []
         self.outpath_samples: str = outpath_samples
@@ -51,6 +112,7 @@ def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prom
         self.height: int = height
         self.full_quality: bool = full_quality
         self.detailer: bool = detailer
+        self.restore_faces: bool = restore_faces
         self.tiling: bool = tiling
         self.hidiffusion: bool = hidiffusion
         self.do_not_save_samples: bool = do_not_save_samples
@@ -191,7 +253,25 @@ def close(self):
 
 class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
 
-    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_force: bool = False, hr_resize_mode: int = 0, hr_resize_context: str = 'None', hr_upscaler: str = None, hr_second_pass_steps: int = 0, hr_resize_x: int = 0, hr_resize_y: int = 0, refiner_steps: int = 5, refiner_start: float = 0, refiner_prompt: str = '', refiner_negative: str = '', **kwargs):
+    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_force: bool = False,
+                 hr_resize_mode: int = 0,
+                 hr_resize_context: str = 'None',
+                 hr_upscaler: str = None,
+                 hr_second_pass_steps: int = 0,
+                 hr_resize_x: int = 0,
+                 hr_resize_y: int = 0,
+                 refiner_steps: int = 5,
+                 refiner_start: float = 0,
+                 refiner_prompt: str = '',
+                 refiner_negative: str = '',
+                 **kwargs
+                ):
 
         super().__init__(**kwargs)
         self.reprocess = {}

modules/shared.py

@@ -474,9 +474,9 @@ def get_default_modes():
     "cuda_compile_errors": OptionInfo(True, "Model compile suppress errors"),
     "deep_cache_interval": OptionInfo(3, "DeepCache cache interval", gr.Slider, {"minimum": 1, "maximum": 10, "step": 1}),
 
-    "quant_sep": OptionInfo("<h2>Model Quantization</h2>", "", gr.HTML),
-    "quant_shuffle_weights": OptionInfo(False, "Shuffle the weights between GPU and CPU when quantizing"),
-    "diffusers_quantization": OptionInfo(False, "Dynamic quantization with TorchAO"),
+    "quant_sep": OptionInfo("<h2>Model Quantization</h2>", "", gr.HTML, {"visible": native}),
+    "quant_shuffle_weights": OptionInfo(False, "Shuffle the weights between GPU and CPU when quantizing", gr.Checkbox, {"visible": native}),
+    "diffusers_quantization": OptionInfo(False, "Dynamic quantization with TorchAO", gr.Checkbox, {"visible": native}),
     "nncf_compress_weights": OptionInfo([], "Compress Model weights with NNCF INT8", gr.CheckboxGroup, {"choices": ["Model", "VAE", "Text Encoder", "ControlNet"], "visible": native}),
     "optimum_quanto_weights": OptionInfo([], "Quantize Model weights with Optimum Quanto", gr.CheckboxGroup, {"choices": ["Model", "VAE", "Text Encoder", "ControlNet"], "visible": native}),
     "optimum_quanto_weights_type": OptionInfo("qint8", "Weights type for Optimum Quanto", gr.Radio, {"choices": ['qint8', 'qfloat8_e4m3fn', 'qfloat8_e5m2', 'qint4', 'qint2'], "visible": native}),
@@ -543,7 +543,7 @@ def get_default_modes():
     "batch_frame_mode": OptionInfo(False, "Parallel process images in batch"),
     "inference_other_sep": OptionInfo("<h2>Other</h2>", "", gr.HTML),
     "inference_mode": OptionInfo("no-grad", "Torch inference mode", gr.Radio, {"choices": ["no-grad", "inference-mode", "none"]}),
-    "sd_vae_sliced_encode": OptionInfo(False, "VAE sliced encode"),
+    "sd_vae_sliced_encode": OptionInfo(False, "VAE sliced encode", gr.Checkbox, {"visible": not native}),
 }))
 
 options_templates.update(options_section(('diffusers', "Diffusers Settings"), {