outputs .obj files

app.py

@@ -125,8 +125,10 @@ def run_inference(temp_dir, removed_bg_path):
         else:
             print(f"\nThe folder '{specific_out_folder_path}' does not exist.")
         
-        output_videos = glob(os.path.join(f"out/{removed_bg_file_name}", "*.mp4"))
-        return output_videos
+        output_video = glob(os.path.join(f"out/{removed_bg_file_name}", "*.mp4"))
+        output_objects = glob(os.path.join(f"out/{removed_bg_file_name}", "*.obj"))
+        return output_video, output_objects
+    
     except subprocess.CalledProcessError as e:
         return f"Error during inference: {str(e)}"
 
@@ -143,7 +145,7 @@ def process_image(input_pil, remove_bg):
     removed_bg_path, temp_dir = result  # Unpack only if successful
 
     # Run inference
-    output_video = run_inference(temp_dir, removed_bg_path)
+    output_video, output_objects = run_inference(temp_dir, removed_bg_path)
 
     if isinstance(output_video, str) and output_video.startswith("Error"):
         shutil.rmtree(temp_dir)
@@ -153,7 +155,7 @@ def process_image(input_pil, remove_bg):
     shutil.rmtree(temp_dir)  # Cleanup temporary folder
     print(output_video)
     torch.cuda.empty_cache()
-    return output_video[0]
+    return output_video[0], output_objects
 
 css="""
 div#col-container{
@@ -201,8 +203,10 @@ def gradio_interface():
                         remove_bg = gr.Checkbox(label="Need to remove BG ?", value=False)
                     
                         submit_button = gr.Button("Process")
-        
-                    output_video= gr.Video(label="Output Video", scale=4, elem_id="video-out-elm")
+                    
+                    with gr.Column(scale=4):
+                        output_video= gr.Video(label="Output Video", elem_id="video-out-elm")
+                        output_objects = gr.Files(label=".OBJ outputs")
     
             gr.Examples(
                 examples = examples_folder,
@@ -210,7 +214,7 @@ def gradio_interface():
                 examples_per_page = 11
             )
 
-        submit_button.click(process_image, inputs=[input_image, remove_bg], outputs=[output_video])
+        submit_button.click(process_image, inputs=[input_image, remove_bg], outputs=[output_video, output_objects])
 
     return app