added example

app.py

@@ -18,16 +18,6 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 #     pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
 #     pipe = pipe.to(device)
 
-    # return editor
-    # image = editor.edit(target_prompt)
-    # return image
-
-# examples = [
-#     "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-#     "An astronaut riding a green horse",
-#     "A delicious ceviche cheesecake slice",
-# ]
-
 # css = """
 # #col-container-1 {
 #     margin: 0 auto;
@@ -56,40 +46,39 @@ with gr.Blocks(css="style.css") as demo:
     @spaces.GPU
     def set_pipe(input_image, description_prompt, edit_guidance_scale, num_inference_steps=4,
                  num_inversion_steps=4, inversion_max_step=0.6, rnri_iterations=2, rnri_alpha=0.1, rnri_lr=0.2):
-                    
         scheduler_class = MyEulerAncestralDiscreteScheduler
-        
+
         print('\n################## 1')
-        pipe_inversion = SDXLDDIMPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)#.to('cpu')
+        pipe_inversion = SDXLDDIMPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)  # .to('cpu')
         print('\n################## 2')
-        pipe_inference = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)#.to('cpu')
+        pipe_inference = AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo",
+                                                                    use_safetensors=True)  # .to('cpu')
         print('\n################## 3')
         pipe_inference.scheduler = scheduler_class.from_config(pipe_inference.scheduler.config)
         pipe_inversion.scheduler = scheduler_class.from_config(pipe_inversion.scheduler.config)
         pipe_inversion.scheduler_inference = scheduler_class.from_config(pipe_inference.scheduler.config)
         print('\n################## 4')
 
-
         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)
         image_editor = ImageEditorDemo(pipe_inversion, pipe_inference, input_image,
-                               description_prompt, config, device,
-                               [rnri_iterations, rnri_alpha, rnri_lr])
+                                       description_prompt, config, device,
+                                       [rnri_iterations, rnri_alpha, rnri_lr])
         print('\n################## 5')
         return image_editor, "Input has set!"
-    
     @spaces.GPU
     def edit(editor, target_prompt):
         if editor is None:
             raise gr.Error("Set inputs before editing.")
-       # if device == "cuda":
-     #       image = editor.to(device).edit(target_prompt)
-      #  else:
+        # if device == "cuda":
+        #       image = editor.to(device).edit(target_prompt)
+        #  else:
         image = editor.edit(target_prompt)
         return image
 
+
     gr.Markdown(f"""running on {power_device}""")
     with gr.Row():
         with gr.Column(elem_id="col-container-1"):
@@ -99,14 +88,13 @@ with gr.Blocks(css="style.css") as demo:
             with gr.Row():
                 description_prompt = gr.Text(
                     label="Image description",
-                    info = "Enter your image description ",
+                    info="Enter your image description ",
                     show_label=False,
                     max_lines=1,
                     placeholder="a cake on a table",
                     container=False,
                 )
 
-
             with gr.Accordion("Advanced Settings", open=False):
                 with gr.Row():
                     edit_guidance_scale = gr.Slider(
@@ -159,17 +147,13 @@ with gr.Blocks(css="style.css") as demo:
                 set_button = gr.Button("Set input image & description & settings", scale=1)
 
                 is_set_text = gr.Text("", show_label=False)
-
-                # Create a loading indicator
-                loading_indicator = gr.Markdown(value="⏳ Processing...", visible=False)
-
         with gr.Column(elem_id="col-container-2"):
             result = gr.Image(label="Result")
 
             with gr.Row():
                 target_prompt = gr.Text(
                     label="Edit prompt",
-                    info = "Enter your edit prompt",
+                    info="Enter your edit prompt",
                     show_label=False,
                     max_lines=1,
                     placeholder="an oreo cake on a table",
@@ -179,10 +163,12 @@ with gr.Blocks(css="style.css") as demo:
             with gr.Row():
                 run_button = gr.Button("Edit", scale=1)
 
-            # gr.Examples(
-            #     examples = examples,
-            #     inputs = [prompt]
-            # )
+            with gr.Row():
+                gr.Examples(
+                    examples='examples',
+                    inputs=[input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps,
+                            inversion_max_step, rnri_iterations, rnri_alpha, rnri_lr],
+                )
 
     set_button.click(
         fn=set_pipe,
@@ -197,7 +183,6 @@ with gr.Blocks(css="style.css") as demo:
         outputs=[result]
     )
 
-
 demo.queue().launch()
 
 # im = infer(input_image, description_prompt, target_prompt, edit_guidance_scale, num_inference_steps=4, num_inversion_steps=4,

examples/log.csv

@@ -0,0 +1,2 @@
+input_image,description_prompt,target_prompt,edit_guidance_scale,num_inference_steps,inversion_max_step, rnri_iterations,rnri_alpha,rnri_lr
+./images/kitten.jpeg,A kitten is sitting in a basket on a branch,A lego kitten is sitting in a basket on a branch,1.2,4,0.6,2,0.1,0.2