update

app.py

@@ -1609,7 +1609,7 @@ if __name__ == "__main__":
     parser.add_argument('--resolution', default='1024,1024', help="target resolution")
     parser.add_argument('--use_multidiffusion', default=False, action='store_true', help="use multidiffusion or not")
     parser.add_argument('--use_guassian', default=False, action='store_true', help="use guassian or not")
-    parser.add_argument('--use_dilated_sampling', default=False, action='store_true', help="use dilated sampling or not")
+    parser.add_argument('--use_dilated_sampling', default=True, action='store_true', help="use dilated sampling or not")
     parser.add_argument('--use_progressive_upscaling', default=False, action='store_true', help="use progressive upscaling or not")
     parser.add_argument('--shuffle', default=False, action='store_true', help="shuffle or not")
     parser.add_argument('--use_skip_residual', default=False, action='store_true', help="use skip_residual or not")
@@ -1634,7 +1634,8 @@ if __name__ == "__main__":
     # GRADIO MODE
 
 #    @spaces.GPU()
-    def infer(prompt, resolution, num_inference_steps, guidance_scale, seed, progress=gr.Progress(track_tqdm=True)):
+    def infer(prompt, resolution, num_inference_steps, guidance_scale, seed, use_multidiffusion, use_skip_residual, use_dilated_sampling, use_progressive_upscaling, shuffle, use_md_prompt, progress=gr.Progress(track_tqdm=True)):
+    #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",
@@ -1667,17 +1668,24 @@ if __name__ == "__main__":
                       sigma=args.sigma, use_guassian=args.use_guassian,
                       multi_decoder=args.multi_decoder, 
                       upscale_mode=args.upscale_mode, 
-                      use_multidiffusion=args.use_multidiffusion, 
-                      use_skip_residual=args.use_skip_residual, 
-                      use_progressive_upscaling=args.use_progressive_upscaling,
-                      use_dilated_sampling=args.use_dilated_sampling,
-                      shuffle=args.shuffle, 
+                      use_multidiffusion=use_multidiffusion,
+                      use_skip_residual=use_skip_residual,
+                      use_progressive_upscaling=use_progressive_upscaling,
+                      use_dilated_sampling=use_dilated_sampling,
+                      shuffle=shuffle,
+                      #use_multidiffusion=args.use_multidiffusion, 
+                      #use_skip_residual=args.use_skip_residual, 
+                      #use_progressive_upscaling=args.use_progressive_upscaling,
+                      #use_dilated_sampling=args.use_dilated_sampling,
+                      #shuffle=args.shuffle, 
                       result_path=result_path, 
-                      debug=args.debug, save_attention_map=args.save_attention_map, use_md_prompt=args.use_md_prompt, c=args.c
+                      #debug=args.debug, save_attention_map=args.save_attention_map, use_md_prompt=args.use_md_prompt, c=args.c
+                      debug=args.debug, save_attention_map=args.save_attention_map, use_md_prompt=use_md_prompt, c=args.c
                     )
         print(images)
 
-        return images[0]
+        #return images[0]
+        return images
     
     css = """
     #col-container{
@@ -1728,14 +1736,23 @@ if __name__ == "__main__":
                             choices = [
                                 "1024,1024", "2048,2048", "2048,1024", "1536,3072", "3072,3072", "4096,4096", "4096,2048"
                             ],
-                            value = "1024,1024"
+                            #value = "1024,1024"
+                            value = "2048,2048",
+                            interactive=False
                         )
                         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)
+                    use_multidiffusion = gr.Checkbox(label="use_multidiffusion", value=True)
+                    use_skip_residual = gr.Checkbox(label="use_skip_residual", value=True)
+                    use_dilated_sampling = gr.Checkbox(label="use_dilated_sampling", value=True)
+                    use_progressive_upscaling = gr.Checkbox(label="use_progressive_upscaling", value=False)
+                    shuffle = gr.Checkbox(label="shuffle", value=False)
+                    use_md_prompt = gr.Checkbox(label="use_md_prompt", value=False)
             
-            output_images = gr.Image(label="Output Image", format="png")
+#            output_images = gr.Image(label="Output Image", format="png")
+            output_images = gr.Gallery(label="Output Image", format="png")
             gr.Examples(
                 examples = [
                     ["Astronaut on Mars during sunset."],
@@ -1746,7 +1763,8 @@ if __name__ == "__main__":
             )
         submit_btn.click(
             fn = infer,
-            inputs = [prompt, resolution, num_inference_steps, guidance_scale, seed],
+            #inputs = [prompt, resolution, num_inference_steps, guidance_scale, seed],
+            inputs = [prompt, resolution, num_inference_steps, guidance_scale, seed, use_multidiffusion, use_skip_residual, use_dilated_sampling, use_progressive_upscaling, shuffle, use_md_prompt],
             outputs = [output_images],
             show_api=False
         )