facehires set steps, sampler

CHANGELOG.md

@@ -69,7 +69,7 @@
   - new *face restore* option, works similar to well-known *adetailer* by running an inpaint on detected faces but with just a checkbox to enable/disable  
   - set as default face restorer in settings -> postprocessing  
   - disabled by default, to enable simply check *face restore* in your generate advanced settings  
-  - strength is controlled by refine strength setting  
+  - strength, steps and sampler are set using by hires section in refine menu  
   - will use secondary prompt and secondary negative prompt if present in refine  
 - **Watermarking**
   - SD.Next disables all known watermarks in models, but does allow user to set custom watermark  

modules/processing_class.py

@@ -521,6 +521,9 @@ def switch_class(p: StableDiffusionProcessing, new_class: type, dct: dict = None
     shared.log.debug(f"Switching class: {p.__class__} -> {new_class}")
     p.__class__ = new_class
     p.__init__(**kwargs)
+    for k, v in p.__dict__.items():
+        if hasattr(p, k):
+            setattr(p, k, v)
     if dct is not None: # post init set additional values
         for k, v in dct.items():
             if hasattr(p, k):

scripts/face-details.py

@@ -90,7 +90,9 @@ class FaceRestorerYolo(FaceRestoration):
 
     def restore(self, np_image, p: processing.StableDiffusionProcessing = None):
         from modules import devices, processing_class
-        if np_image is None or hasattr(p, 'facehires'):
+        if not hasattr(p, 'facehires'):
+            p.facehires = 0
+        if np_image is None or getattr(p, 'facehires', 0) >= p.batch_size:
             return np_image
         self.load()
         if self.model is None:
@@ -107,7 +109,7 @@ class FaceRestorerYolo(FaceRestoration):
         orig_cls = p.__class__
 
         pp = None
-        p.facehires = True # set flag to avoid recursion
+        p.facehires += 1 # set flag to avoid recursion
         shared.opts.data['mask_apply_overlay'] = True
         p = processing_class.switch_class(p, processing.StableDiffusionProcessingImg2Img)
 
@@ -122,6 +124,8 @@ class FaceRestorerYolo(FaceRestoration):
             p.inpaint_full_res = True
             p.inpainting_mask_invert = 0
             p.inpainting_fill = 1 # no fill
+            p.sampler_name = orig_p.get('hr_sampler_name', 'default')
+            p.steps = orig_p.get('hr_second_pass_steps', p.steps)
             p.denoising_strength = orig_p.get('denoising_strength', 0.3)
             p.styles = []
             p.prompt = orig_p.get('refiner_prompt', '')