Update app.py

app.py

@@ -86,7 +86,20 @@ def king(type = "Image Generation",
         use_resolution_binning: bool = True,
         progress=gr.Progress(track_tqdm=True),
     ):
-    if type=="Image Generation" :
+    if type=="Image Editing" :
+        seed = int(randomize_seed_fn(seed, randomize_seed))
+        text_cfg_scale = text_cfg_scale
+        image_cfg_scale = image_cfg_scale
+        input_image = input_image
+
+        steps=steps*3
+        generator = torch.manual_seed(seed)
+        output_image = pipe_edit(
+            instruction, image=input_image,
+            guidance_scale=text_cfg_scale, image_guidance_scale=image_cfg_scale,
+            num_inference_steps=steps, generator=generator).images[0]
+        return seed, output_image
+    else :
         pipe.to(device)
         seed = int(randomize_seed_fn(seed, randomize_seed))
         generator = torch.Generator().manual_seed(seed)   
@@ -104,19 +117,8 @@ def king(type = "Image Generation",
         
         output_image = pipe(**options).images[0]
         return seed, output_image
-    else:
-        seed = int(randomize_seed_fn(seed, randomize_seed))
-        text_cfg_scale = text_cfg_scale
-        image_cfg_scale = image_cfg_scale
-        input_image = input_image
 
-        steps=steps*3
-        generator = torch.manual_seed(seed)
-        output_image = pipe_edit(
-            instruction, image=input_image,
-            guidance_scale=text_cfg_scale, image_guidance_scale=image_cfg_scale,
-            num_inference_steps=steps, generator=generator).images[0]
-        return seed, output_image
+
         
 def response(instruction, input_image=None):
     if input_image is None: