Update app.py

app.py

@@ -24,14 +24,16 @@ pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev",
 pipe.to(DEVICE)
 
 def get_examples():
-    examples = [[Image.open("metal.png"), "a dragon, in 3d melting gold metal",0.9, 0.5, 0, 5, 28, 28,  0, False,False, 2,  False,Image.open("dragon.png") ],        
-               [Image.open("doll.png"), "anime illustration",0.9, 0.5, 0, 6, 28, 28,  0, False, False, 2,  False ,Image.open("anime.png")],
-               [Image.open("doll.png"), "raccoon, made of yarn",0.9, 0.5, 0, 4, 28, 28,  0, False, False, 2,  False , Image.open("raccoon.png")],
-               [Image.open("cat.jpg"), "a parrot", 0.9 ,0.5,2, 8,28, 28,0, False ,  False, 1,  False,Image.open("parrot.png")],
-               [Image.open("cat.jpg"), "a tiger", 0.9 ,0.5,0, 4,8, 8,789385745, False ,  False, 1,  True,Image.open("tiger.png")],
-               [Image.open("metal.png"),"a dragon, in 3d melting gold metal",0.9, 0.5, 0, 4, 8, 8,  789385745, False,True, 2,  True , Image.open("dragon.png")],
-               ]
-    return examples
+    case = [
+           [Image.open("metal.png"), "a dragon, in 3d melting gold metal",0.9, 0.5, 0, 5, 28, 28,  0, False,False, 2,  False,Image.open("dragon.png") ],        
+           [Image.open("doll.png"), "anime illustration",0.9, 0.5, 0, 6, 28, 28,  0, False, False, 2,  False ,Image.open("anime.png")],
+           [Image.open("doll.png"), "raccoon, made of yarn",0.9, 0.5, 0, 4, 28, 28,  0, False, False, 2,  False , Image.open("raccoon.png")],
+           [Image.open("cat.jpg"), "a parrot", 0.9 ,0.5,2, 8,28, 28,0, False ,  False, 1,  False,Image.open("parrot.png")],
+           [Image.open("cat.jpg"), "a tiger", 0.9 ,0.5,0, 4,8, 8,789385745, False ,  False, 1,  True,Image.open("tiger.png")],
+           [Image.open("metal.png"),"a dragon, in 3d melting gold metal",0.9, 0.5, 0, 4, 8, 8,  789385745, False,True, 2,  True , Image.open("dragon.png")],
+        ]
+    return case
+    
 def reset_do_inversion():
         return True
     
@@ -265,7 +267,7 @@ based on the implementations of [@raven38](https://github.com/raven38) & [@DarkM
     )
 
     gr.Examples(
-                examples=get_examples,
+                examples=get_examples(),
                 inputs=[input_image, prompt,eta,gamma,start_timestep, stop_timestep, num_inversion_steps, num_inference_steps,  seed, randomize_seed, eta_decay, decay_power, enable_hyper_flux ],
                 outputs=[result],