Update app.py

step2 and step3 together

app.py

@@ -119,7 +119,7 @@ def slider_release(index, image,  mask_np_list_updated, mask_label_list):
     gr.Info('Edit '+ mask_label)
     return new_image, mask_label, mask_prompt
 def image_change():
-    return gr.Slider(value = 0, minimum=0, maximum=1, step=1, visible=False),gr.Button("Step 3. Run Editing (Check log for progress.)",interactive = False)
+    return gr.Slider(value = 0, minimum=0, maximum=1, step=1, visible=False)
 
 def save_as_orig_mask(mask_np_list_updated, mask_label_list, input_folder="example_tmp"):
     print(mask_np_list_updated)
@@ -188,7 +188,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         gr.Markdown("""# D-Edit""")
 
-    with gr.Tab(label="D-edit"): 
+    if 1:
         with gr.Row():
             with gr.Column():
                 canvas = gr.Image(value = None, type="numpy",  label="Show Mask", show_label=True, height=LENGTH, width=LENGTH, interactive=True)
@@ -211,7 +211,6 @@ with gr.Blocks() as demo:
 
             
                 
-    #with gr.Tab(label="2 Optimization"):
 
                 result_info = gr.Text(label="Response")
                 
@@ -229,7 +228,6 @@ with gr.Blocks() as demo:
                     train_batch_size = gr.Number(value="20", label="Batch size", interactive= True )
                     gradient_accumulation_steps=gr.Number(value="2", label="Gradient accumulation", interactive= True )
                 
-                add_button  = gr.Button("Step 2. Run optimization")
                 def run_optimization_wrapper (
                         mask_np_list,
                         mask_label_list,
@@ -259,11 +257,11 @@ with gr.Blocks() as demo:
                         )
                         run_optimization()
                         gr.Info("Optimization Finished! Move to the next step.")
-                        return "Optimization finished! Move to the next step.",gr.Button("Step 3. Run Editing",interactive = True)
+                        return "Optimization finished! Move to the next step."#,gr.Button("Step 3. Run Editing",interactive = True)
                     except Exception as e:
                         print(e)
                         gr.Error("e")
-                        return "Error: use a smaller batch size or try latter.",gr.Button("Step 3. Run Editing",interactive = False)
+                        return "Error: use a smaller batch size or try latter."#,gr.Button("Step 3. Run Editing",interactive = False)
 
 
 
@@ -283,7 +281,7 @@ 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_button2  = gr.Button("Step 3. Run Editing",interactive = False)
+                    add_button  = gr.Button("Step 2. Run Editing",interactive = False)
                     def run_edit_text_wrapper(
                             mask_np_list,
                             mask_label_list,
@@ -319,36 +317,41 @@ with gr.Blocks() as demo:
 
 
 
+            def run_total_wrapper(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, num_tokens_global, guidance_scale, num_sampling_steps, strength, edge_thickness, tgt_prompt, slider2):
+                result_info = run_optimization_wrapper(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)
+                canvas_text_edit = run_edit_text_wrapper(mask_np_list, mask_label_list, image_loaded, num_tokens_global, guidance_scale, num_sampling_steps, strength, edge_thickness, tgt_prompt, slider2)
+                return result_info, canvas_text_edit
 
-        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,
-                                    guidance_scale,
-                                    num_sampling_steps,
-                                    strength ,
-                                    edge_thickness,
-                                    tgt_prompt ,
-                                    slider2
-                                ],        
-                        outputs = [canvas_text_edit],queue=True)
+
+            add_button.click(
+                run_total_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,
+                    num_tokens_global,
+                    guidance_scale,
+                    num_sampling_steps,
+                    strength,
+                    edge_thickness,
+                    tgt_prompt,
+                    slider2
+                ],
+                outputs=[result_info, canvas_text_edit],
+            )
+
+
+
+
+        canvas.upload(image_change, inputs=[], outputs=[slider])       
 
         slider.release(slider_release, 
                         inputs = [slider, image_loaded,   mask_np_list_updated, mask_label_list],