i (#114)

modules/async_worker.py

@@ -14,6 +14,7 @@ def worker():
     import random
     import modules.default_pipeline as pipeline
     import modules.path
+    import modules.patch
 
     from PIL import Image
     from modules.sdxl_styles import apply_style, aspect_ratios
@@ -30,11 +31,13 @@ def worker():
 
     def handler(task):
         prompt, negative_prompt, style_selction, performance_selction, \
-        aspect_ratios_selction, image_number, image_seed, base_model_name, refiner_model_name, \
+        aspect_ratios_selction, image_number, image_seed, sharpness, base_model_name, refiner_model_name, \
         l1, w1, l2, w2, l3, w3, l4, w4, l5, w5 = task
 
         loras = [(l1, w1), (l2, w2), (l3, w3), (l4, w4), (l5, w5)]
 
+        modules.patch.sharpness = sharpness
+
         pipeline.refresh_base_model(base_model_name)
         pipeline.refresh_refiner_model(refiner_model_name)
         pipeline.refresh_loras(loras)

modules/html.py

@@ -76,6 +76,12 @@ progress::after {
   resize: none !important;
 }
 
+.refresh_button{
+  border: none !important;
+  background: none !important;
+  font-size: none !important;
+}
+
 '''
 progress_html = '''
 <div class="loader-container">

modules/patch.py

@@ -7,6 +7,8 @@ from comfy.samplers import model_management, lcm, math
 from comfy.ldm.modules.diffusionmodules.openaimodel import timestep_embedding, forward_timestep_embed
 from modules.filters import gaussian_filter_2d
 
+sharpness = 2.0
+
 
 def sampling_function_patched(model_function, x, timestep, uncond, cond, cond_scale, cond_concat=None, model_options={},
                       seed=None):
@@ -346,7 +348,7 @@ def unet_forward_patched(self, x, timesteps=None, context=None, y=None, control=
     x0 = self.out(h)
 
     alpha = 1.0 - (timesteps / 999.0)[:, None, None, None].clone()
-    alpha *= 0.002
+    alpha *= 0.001 * sharpness
     degraded_x0 = gaussian_filter_2d(x0) * alpha + x0 * (1.0 - alpha)
 
     x0 = x0 * uc_mask + degraded_x0 * (1.0 - uc_mask)