enables multiple editing without initializing the image each time

app.py

@@ -28,19 +28,23 @@ pipe_inversion.scheduler_inference = scheduler_class.from_config(pipe_inference.
 #     pipe = pipe.to(device)
 
 
-def infer(input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps=4,
-          num_inversion_steps=4,
-          inversion_max_step=0.6):
+def set_pipe(input_image, description_prompt, edit_guidance_scale, num_inference_steps=4,
+          num_inversion_steps=4, inversion_max_step=0.6):
     config = RunConfig(num_inference_steps=num_inference_steps,
                        num_inversion_steps=num_inversion_steps,
                        edit_guidance_scale=edit_guidance_scale,
                        inversion_max_step=inversion_max_step)
 
-    editor = ImageEditorDemo(pipe_inversion, pipe_inference, input_image, description_prompt, config, device)
+    return ImageEditorDemo(pipe_inversion, pipe_inference, input_image, description_prompt, config, device)
 
-    image = editor.edit(target_prompt)
-    return image
+    # return editor
+    # image = editor.edit(target_prompt)
+    # return image
 
+def edit(editor, target_prompt):
+    if editor is None:
+        return "Please set image & description before editing."
+    return editor.edit(target_prompt)
 
 examples = [
     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
@@ -85,6 +89,10 @@ with gr.Blocks() as demo:
                     container=False,
                 )
 
+            with gr.Row():
+                set_button = gr.Button("Set input image & description", scale=1)
+
+            editor_state = gr.State()
             with gr.Row():
                 target_prompt = gr.Text(
                     label="Edit prompt",
@@ -131,13 +139,20 @@ with gr.Blocks() as demo:
             #     inputs = [prompt]
             # )
 
+    set_button.click(
+        fn=set_pipe,
+        inputs=[input_image, description_prompt, edit_guidance_scale, num_inference_steps,
+                num_inference_steps, inversion_max_step],
+        outputs=editor_state
+    )
+
     run_button.click(
-        fn=infer,
-        inputs=[input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps,
-                num_inference_steps],
+        fn=edit,
+        inputs=[editor_state, target_prompt],
         outputs=[result]
     )
 
+
 demo.queue().launch()
 
 # im = infer(input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps=4, num_inversion_steps=4,