Update app.py

app.py

@@ -107,7 +107,7 @@ def slider_release(index, image,  mask_np_list_updated, mask_label_list):
         new_image = transparent_paste_with_mask(image, segmentation, mask_np, transparency = TRANSPARENCY)
     return new_image, mask_label
 def image_change():
-    return gr.Slider(value = 0, minimum=0, maximum=1, step=1, visible=False)
+    return gr.Slider(value = 0, minimum=0, maximum=1, step=1, visible=False),gr.Button("Run Editing (Check log for progress.)",interactive = False)
 
 def save_as_orig_mask(mask_np_list_updated, mask_label_list, input_folder="example_tmp"):
     print(mask_np_list_updated)
@@ -194,7 +194,7 @@ with gr.Blocks() as demo:
                         outputs= [canvas, label]
                     )
 
-            canvas.upload(image_change, inputs=[], outputs=[slider])
+            
                 
     with gr.Tab(label="2 Optimization"):
         with gr.Row():
@@ -244,30 +244,15 @@ with gr.Blocks() as demo:
                         )
                         run_optimization()
                         print('finish')
-                        return "Optimization finished! Move to the next step."
+                        return "Optimization finished! Move to the next step.",gr.Button("Run Editing (Check log for progress.)",interactive = True)
                     except:
-                        return "CUDA out of memory, use a smaller batch size or try another picture."
+                        return "CUDA out of memory, use a smaller batch size or try another picture.",gr.Button("Run Editing (Check log for progress.)",interactive = False)
 
                 
                 def immediate_update():
                     return gr.Button("Run Optimization (Check log for progress.).", interactive=True)
-                
-                add_button.click(run_optimization_wrapper, 
-                        inputs = [
-                            mask_np_list,
-                            mask_label_list,
-                            image_loaded,
-                            opt_flag,
-                            num_tokens,
-                            embedding_learning_rate , 
-                            max_emb_train_steps , 
-                            diffusion_model_learning_rate , 
-                            max_diffusion_train_steps,
-                            train_batch_size,
-                            gradient_accumulation_steps
-                        ], 
-                        outputs = [result_info], api_name=False, concurrency_limit=45)
-                add_button.click(fn=immediate_update, inputs=[], outputs=[add_button])
+
+                #add_button.click(fn=immediate_update, inputs=[], outputs=[add_button])
                 #add_button.update()
                 def change_text():
                     return gr.Textbox("Optimization Finished! Move to the next step.", interactive = False)
@@ -292,7 +277,7 @@ with gr.Blocks() as demo:
                     edge_thickness = gr.Number(value="10", label="Editing: Edge thickness", interactive= True )
                     strength = gr.Textbox(value="0.5", label="Editing: Mask strength", interactive= True )
                     
-                    add_button  = gr.Button("Run Editing (Check log for progress.)")
+                    add_button2  = gr.Button("Run Editing (Check log for progress.)",interactive = False)
                     def run_edit_text_wrapper(
                             mask_np_list,
                             mask_label_list,
@@ -324,8 +309,26 @@ with gr.Blocks() as demo:
                         )
                         run_edit_text()
                         return load_pil_img()
-                        
-                    add_button.click(run_edit_text_wrapper, 
+
+
+        canvas.upload(image_change, inputs=[], outputs=[slider,add_button2])            
+        add_button.click(run_optimization_wrapper, 
+                        inputs = [
+                            mask_np_list,
+                            mask_label_list,
+                            image_loaded,
+                            opt_flag,
+                            num_tokens,
+                            embedding_learning_rate , 
+                            max_emb_train_steps , 
+                            diffusion_model_learning_rate , 
+                            max_diffusion_train_steps,
+                            train_batch_size,
+                            gradient_accumulation_steps
+                        ], 
+                        outputs = [result_info,add_button2], api_name=False, concurrency_limit=45)
+                
+        add_button2.click(run_edit_text_wrapper, 
                         inputs = [  mask_np_list,
                                     mask_label_list,
                                     image_loaded,num_tokens_global,
@@ -336,8 +339,7 @@ with gr.Blocks() as demo:
                                     tgt_prompt ,
                                     slider2
                                 ],        
-                        outputs = [canvas_text_edit],queue=True,
-                    )
+                        outputs = [canvas_text_edit],queue=True)
                     
         slider.change(
             lambda x: x,