Update app.py

app.py

@@ -124,7 +124,7 @@ pipe = TryonPipeline.from_pretrained(
 pipe.unet_encoder = UNet_Encoder
 
 @spaces.GPU
-def start_tryon(person_img, mask_img, cloth_img, garment_des, denoise_steps, seed):
+def start_tryon(person_img, mask_img, cloth_img, garment_des, denoise_steps=10, seed=42):
     # Assuming device is set up (e.g., "cuda" or "cpu")
     pipe.to(device)
     pipe.unet_encoder.to(device)
@@ -222,13 +222,11 @@ with image_blocks as demo:
             garment_des = gr.Textbox(placeholder="Description of garment ex) Short Sleeve Round Neck T-shirts", label="Garment Description")
 
         with gr.Column():
-            denoise_steps = gr.Number(label="Denoising Steps", minimum=20, maximum=40, value=30, step=1)
-            seed = gr.Number(label="Seed", minimum=-1, maximum=2147483647, step=1, value=42)
 
         with gr.Column():
             image_out = gr.Image(label="Output Image", elem_id="output-img", show_share_button=False)
 
     try_button = gr.Button(value="Try-on")
-    try_button.click(fn=start_tryon, inputs=[person_img, mask_img, cloth_img, garment_des, denoise_steps, seed], outputs=[image_out], api_name='tryon')
+    try_button.click(fn=start_tryon, inputs=[person_img, mask_img, cloth_img, garment_des], outputs=[image_out], api_name='tryon')
 
 image_blocks.launch()