Update app.py

Made changes to the UI

app.py

@@ -180,12 +180,10 @@ def run_partcrafter(image_path: str,
 
     """
     Generate structured 3D meshes from a 2D image using the PartCrafter pipeline.
-
     This function takes a single 2D image as input and produces a set of part-based 3D meshes,
     using compositional latent diffusion with attention to structure and part separation.
     Optionally removes the background using a pretrained background removal model (RMBG),
     and outputs a merged object mesh.
-
     Args:
         image_path (str): Path to the input image file on disk.
         num_parts (int, optional): Number of distinct parts to decompose the object into. Defaults to 1.
@@ -197,11 +195,9 @@ def run_partcrafter(image_path: str,
         rmbg (bool, optional): Whether to apply background removal before processing. Defaults to True.
         session_id (str, optional): Optional session ID to manage export paths. If not provided, a random UUID is generated.
         progress (gr.Progress, optional): Gradio progress object for visual feedback. Automatically handled by Gradio.
-
     Returns:
         Tuple[str, str, str, str]: 
             - `merged_path` (str): File path to the merged full object mesh (`object.glb`).
-
     Notes:
         - This function utilizes HuggingFace pretrained weights for both part generation and background removal.
         - The final output includes merged model parts to visualize object structure.
@@ -291,9 +287,6 @@ def build_demo():
             gr.HTML(
                 """
                 <div style="text-align: center;">
-                    <p style="font-size:16px; display: inline; margin: 0;">
-                        <strong>PartCrafter</strong> – Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers
-                    </p>
                     <a href="https://github.com/wgsxm/PartCrafter" style="display: inline-block; vertical-align: middle; margin-left: 0.5em;">
                         <img src="https://img.shields.io/badge/GitHub-Repo-blue" alt="GitHub Repo">
                     </a>
@@ -310,28 +303,20 @@ def build_demo():
                     
                     input_image = gr.Image(type="filepath", label="Input Image", height=256)
                     num_parts = gr.Slider(1, MAX_NUM_PARTS, value=4, step=1, label="Number of Parts")
-                    run_button = gr.Button("Step 1 - 🧩 Craft 3D Parts", variant="primary")
-                    video_button = gr.Button("Step 2 - 🎥 Generate Split Preview Gif (Optional)")
                     
-                    with gr.Accordion("Advanced Settings", open=False):
+                    with gr.Accordion("Advanced Settings▼", open=False):
                         seed = gr.Number(value=0, label="Random Seed", precision=0)
                         num_tokens = gr.Slider(256, 2048, value=1024, step=64, label="Num Tokens")
                         num_steps = gr.Slider(1, 100, value=50, step=1, label="Inference Steps")
                         guidance = gr.Slider(1.0, 20.0, value=7.0, step=0.1, label="Guidance Scale")
                         flash_decoder = gr.Checkbox(value=False, label="Use Flash Decoder")
                         remove_bg = gr.Checkbox(value=True, label="Remove Background (RMBG)")
+                    
+                    run_button = gr.Button("🚀 Generate 3D Parts")
 
                 with gr.Column(scale=2):
-                    gr.HTML(
-                        """
-                        <p style="opacity: 0.6; font-style: italic;">
-                          The 3D Preview might take a few seconds to load the 3D model
-                        </p>
-                        """
-                    )
-                    with gr.Row():
-                        output_model = gr.Model3D(label="Merged 3D Object", height=512, interactive=False)
-                        video_output = gr.Image(label="Split Preview", height=512)
+                    output_model = gr.Model3D(label="Merged 3D Object", height=512, interactive=False)
+                    
             with gr.Row():
                 with gr.Column():
                     examples = gr.Examples(
@@ -356,8 +341,8 @@ def build_demo():
                             
                         ],
                         inputs=[input_image, num_parts],
-                        outputs=[output_model, video_output],
-                        fn=gen_model_n_video,
+                        outputs=[output_model],
+                        fn=lambda img, parts: gen_model_n_video(img, parts)[0],
                         cache_examples=True
                     )
     
@@ -365,9 +350,6 @@ def build_demo():
                              inputs=[input_image, num_parts, seed, num_tokens, num_steps,
                                      guidance, flash_decoder, remove_bg, session_state],
                              outputs=[output_model])
-            video_button.click(fn=gen_video,
-                             inputs=[output_model],
-                             outputs=[video_output])
             
         return demo