Update app.py

app.py

@@ -1625,14 +1625,14 @@ if __name__ == "__main__":
     # GRADIO MODE
 
     @spaces.GPU()
-    def infer(prompt, resolution, num_inference_steps, guidance_scale, progress=gr.Progress(track_tqdm=True)):
-        set_seed(args.seed)
+    def infer(prompt, resolution, num_inference_steps, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
+        set_seed(seed)
         width,height = list(map(int, resolution.split(',')))
         cross_attention_kwargs = {"edit_type": "visualize",
                                   "n_self_replace": 0.4,
                                   "n_cross_replace": {"default_": 1.0, "confetti": 0.8},
                                   }
-        seed = args.seed
+        seed = seed
         generator = torch.Generator(device='cuda')
         generator = generator.manual_seed(seed)
         
@@ -1672,6 +1672,9 @@ if __name__ == "__main__":
         margin: 0 auto;
     }
     """
+
+    MAX_SEED = np.iinfo(np.int32).max
+    
     with gr.Blocks(css=css) as demo:
         with gr.Column(elem_id="col-container"):
             gr.Markdown("# AccDiffusion: An Accurate Method for Higher-Resolution Image Generation")
@@ -1704,6 +1707,7 @@ if __name__ == "__main__":
                         with gr.Column():
                             num_inference_steps = gr.Slider(label="Inference Steps", minimum=2, maximum=50, step=1, value=50)
                             guidance_scale = gr.Slider(label="Guidance Scale", minimum=1, maximum=510, step=0.1, value=7.5)
+                            seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=42)
             
             output_images = gr.Image(label="Output Image", format="png")
             gr.Examples(
@@ -1716,7 +1720,7 @@ if __name__ == "__main__":
             )
         submit_btn.click(
             fn = infer,
-            inputs = [prompt, resolution, num_inference_steps, guidance_scale],
+            inputs = [prompt, resolution, num_inference_steps, guidance_scale, seed],
             outputs = [output_images],
             show_api=False
         )