Update app.py

app.py

@@ -93,7 +93,7 @@ if is_cpu_offload_enabled:
     pipeline.enable_model_cpu_offload()
 
 @spaces.GPU
-def remove(gradio_image, rm_guidance_scale=9, num_inference_steps=50, seed=42, strength=0.8):
+def remove(gradio_image, rm_guidance_scale=9, num_inference_steps=50, seed=42, strength=0.8, similarity_suppression_steps=9, similarity_suppression_scale=0.3):
     try:
         generator = torch.Generator('cuda').manual_seed(seed)
         prompt = "" # Set prompt to null
@@ -107,8 +107,8 @@ def remove(gradio_image, rm_guidance_scale=9, num_inference_steps=50, seed=42, s
         END_STEP = int(strength * num_inference_steps) # AAS end step
         LAYER = 34 # 0~23down,24~33mid,34~69up /AAS start layer
         END_LAYER = 70 # AAS end layer
-        ss_steps = 9 # similarity suppression steps
-        ss_scale = 0.3 # similarity suppression scale
+        ss_steps = similarity_suppression_steps # similarity suppression steps
+        ss_scale = similarity_suppression_scale # similarity suppression scale
 
         image = pipeline(
             prompt=prompt,
@@ -176,6 +176,20 @@ with gr.Blocks() as demo:
                     step=0.1,
                     label="Strength"
                 )
+                similarity_suppression_steps = gr.Slider(
+                    minimum=0,
+                    maximum=10,
+                    value=9,
+                    step=1,
+                    label="Similarity Suppression Steps"
+                )
+                similarity_suppression_scale = gr.Slider(
+                    minimum=0,
+                    maximum=1,
+                    value=0.3,
+                    step=0.1,
+                    label="Similarity Suppression Scale"
+                )
 
             input_image = gr.ImageMask(
                 type="pil", label="Input Image",crop_size=(1200,1200), layers=False
@@ -189,7 +203,7 @@ with gr.Blocks() as demo:
 
     run_button.click(
         fn=remove,
-        inputs=[input_image, guidance_scale, num_steps, seed, strength],
+        inputs=[input_image, guidance_scale, num_steps, seed, strength, similarity_suppression_steps, similarity_suppression_scale],
         outputs=result,
     )