fix gradio (#444)

modules/async_worker.py

@@ -5,10 +5,11 @@ import torch
 
 buffer = []
 outputs = []
+default_image = None
 
 
 def worker():
-    global buffer, outputs
+    global buffer, outputs, default_image
 
     import time
     import shared
@@ -45,6 +46,8 @@ def worker():
     @torch.no_grad()
     @torch.inference_mode()
     def handler(task):
+        global default_image
+
         prompt, negative_prompt, style_selections, performance_selction, \
             aspect_ratios_selction, image_number, image_seed, sharpness, \
             base_model_name, refiner_model_name, \
@@ -90,6 +93,7 @@ def worker():
             progressbar(0, 'Image processing ...')
             if current_tab == 'uov' and uov_method != flags.disabled and uov_input_image is not None:
                 uov_input_image = HWC3(uov_input_image)
+                default_image = uov_input_image
                 if 'vary' in uov_method:
                     if not image_is_generated_in_current_ui(uov_input_image, ui_width=width, ui_height=height):
                         uov_input_image = resize_image(uov_input_image, width=width, height=height)
@@ -167,6 +171,7 @@ def worker():
             if current_tab == 'inpaint' and isinstance(inpaint_input_image, dict):
                 inpaint_image = inpaint_input_image['image']
                 inpaint_mask = inpaint_input_image['mask'][:, :, 0]
+                default_image = inpaint_image
                 if isinstance(inpaint_image, np.ndarray) and isinstance(inpaint_mask, np.ndarray) \
                         and (np.any(inpaint_mask > 127) or len(outpaint_selections) > 0):
                     if len(outpaint_selections) > 0: