Update app.py

app.py

@@ -177,6 +177,7 @@ with gr.Blocks() as demo:
     * Upload an image and click "Generate" to create a 3D asset. If the image has alpha channel, it be used as the mask. Otherwise, we use `rembg` to remove the background.
     * If you find the generated 3D asset satisfactory, click "Extract GLB" to extract the GLB file and download it.
     * Note that the main difference between Trellis and our Trellis-OA is the orientation alignment. It is recommended to test multiple examples and observe the initial poses of the generated 3D models to validate this alignment.
+    * Guidance strength of sparse structure generation can influence the quality of the generated 3D models. If you find holes in the generated 3D models, please reduce the guidance strength. If you find the generated 3D model is not aligned with the input image, please increase the guidance strength. 
     """)
     
     with gr.Row():
@@ -188,7 +189,7 @@ with gr.Blocks() as demo:
                 randomize_seed = gr.Checkbox(label="Randomize Seed", value=True)
                 gr.Markdown("Stage 1: Sparse Structure Generation")
                 with gr.Row():
-                    ss_guidance_strength = gr.Slider(0.0, 10.0, label="Guidance Strength", value=1.5, step=0.1)
+                    ss_guidance_strength = gr.Slider(0.0, 10.0, label="Guidance Strength", value=3.0, step=0.1)
                     ss_sampling_steps = gr.Slider(1, 50, label="Sampling Steps", value=12, step=1)
                 gr.Markdown("Stage 2: Structured Latent Generation")
                 with gr.Row():