cleanup

app.py

@@ -139,12 +139,10 @@ model = model.to(device)
 
 print('Loading Finished!')
 
-
 def check_input_image(input_image):
     if input_image is None:
         raise gr.Error("No image uploaded!")
 
-
 def preprocess(input_image, do_remove_background):
 
     rembg_session = rembg.new_session() if do_remove_background else None
@@ -221,53 +219,16 @@ def _make3d(output_queue: SimpleQueue, images: Image.Image):
     images = rearrange(images, 'c (n h) (m w) -> (n m) c h w', n=3, m=2)        # (6, 3, 320, 320)
 
     input_cameras = get_zero123plus_input_cameras(batch_size=1, radius=4.0).to(device)
-    render_cameras = get_render_cameras(batch_size=1, radius=2.5, is_flexicubes=IS_FLEXICUBES).to(device)
 
     images = images.unsqueeze(0).to(device)
     images = v2.functional.resize(images, (320, 320), interpolation=3, antialias=True).clamp(0, 1)
 
     mesh_fpath = tempfile.NamedTemporaryFile(suffix=f".obj", delete=False).name
-    mesh_basename = os.path.basename(mesh_fpath).split('.')[0]
-    mesh_dirname = os.path.dirname(mesh_fpath)
-    video_fpath = os.path.join(mesh_dirname, f"{mesh_basename}.mp4")
-    mesh_glb_fpath = os.path.join(mesh_dirname, f"{mesh_basename}.glb")
 
     with torch.no_grad():
         # get triplane
         planes = model.forward_planes(images, input_cameras)
 
-        # get video
-        # chunk_size = 20 if IS_FLEXICUBES else 1
-        # render_size = 384
-
-        
-        # frames = []
-        # for i in tqdm(range(0, render_cameras.shape[1], chunk_size)):
-        #     if IS_FLEXICUBES:
-        #         frame = model.forward_geometry(
-        #             planes,
-        #             render_cameras[:, i:i+chunk_size],
-        #             render_size=render_size,
-        #         )['img']
-        #     else:
-        #         frame = model.synthesizer(
-        #             planes,
-        #             cameras=render_cameras[:, i:i+chunk_size],
-        #             render_size=render_size,
-        #         )['images_rgb']
-
-        #     frames.append(frame)
-
-        # frames = torch.cat(frames, dim=1)
-
-        # images_to_video(
-        #     frames[0],
-        #     video_fpath,
-        #     fps=30,
-        # )
-
-        # print(f"Video saved to {video_fpath}")
-
         # get mesh
         mesh_out = model.extract_mesh(
             planes,
@@ -288,14 +249,6 @@ def _make3d(output_queue: SimpleQueue, images: Image.Image):
                 ),
             )
         )
-
-        vertices = vertices[:, [1, 2, 0]]
-
-        save_glb(vertices, faces, vertex_colors, mesh_glb_fpath)
-        save_obj(vertices, faces, vertex_colors, mesh_fpath)
-
-        print(f"Mesh saved to {mesh_fpath}")
-    
     output_queue.put(("mesh", mesh_out))
 
 def generate_blueprint() -> rrb.Blueprint:
@@ -306,7 +259,7 @@ def generate_blueprint() -> rrb.Blueprint:
                 rrb.Spatial2DView(origin="z123image"),
                 rrb.Spatial2DView(origin="preprocessed_image"),
                 rrb.Spatial2DView(origin="mvs/image"),
-                rrb.TensorView(origin="mvs/latents"),   
+                rrb.TensorView(origin="mvs/latents", ),
             ),
             column_shares=[1, 1],
         ),
@@ -351,15 +304,13 @@ def log_to_rr(input_image, do_remove_background, sample_steps, sample_seed):
     # return mesh
 
 _HEADER_ = '''
-<h2><b>Official 🤗 Gradio Demo</b></h2><h2><a href='https://github.com/TencentARC/InstantMesh' target='_blank'><b>InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models</b></a></h2>
+<h2><b>Duplicate of the <a href=https://huggingface.co/spaces/TencentARC/InstantMesh>InstantMesh space</a> that uses <a href=https://rerun.io/>Rerun</a> for visualization.</b></h2>
+<h2><a href='https://github.com/TencentARC/InstantMesh' target='_blank'><b>InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models</b></a></h2>
 
 **InstantMesh** is a feed-forward framework for efficient 3D mesh generation from a single image based on the LRM/Instant3D architecture.
 
-Code: <a href='https://github.com/TencentARC/InstantMesh' target='_blank'>GitHub</a>. Techenical report: <a href='https://arxiv.org/abs/2404.07191' target='_blank'>ArXiv</a>.
+Technical report: <a href='https://arxiv.org/abs/2404.07191' target='_blank'>ArXiv</a>.
 
-❗️❗️❗️**Important Notes:**
-- Our demo can export a .obj mesh with vertex colors or a .glb mesh now. If you prefer to export a .obj mesh with a **texture map**, please refer to our <a href='https://github.com/TencentARC/InstantMesh?tab=readme-ov-file#running-with-command-line' target='_blank'>Github Repo</a>.
-- The 3D mesh generation results highly depend on the quality of generated multi-view images. Please try a different **seed value** if the result is unsatisfying (Default: 42).
 '''
 
 _CITE_ = r"""
@@ -434,30 +385,6 @@ with gr.Blocks() as demo:
             
             viewer = Rerun(streaming=True, height=800)
 
-            # with gr.Row():
-
-            #     with gr.Column():
-            #         mv_show_images = gr.Image(
-            #             label="Generated Multi-views",
-            #             type="pil",
-            #             width=379,
-            #             interactive=False
-            #         )
-
-            # with gr.Row():
-            #     with gr.Tab("OBJ"):
-            #         output_model_obj = gr.Model3D(
-            #             label="Output Model (OBJ Format)",
-            #             interactive=False,
-            #         )
-            #         gr.Markdown("Note: Downloaded .obj model will be flipped. Export .glb instead or manually flip it before usage.")
-            #     with gr.Tab("GLB"):
-            #         output_model_glb = gr.Model3D(
-            #             label="Output Model (GLB Format)",
-            #             interactive=False,
-            #         )
-            #         gr.Markdown("Note: The model shown here has a darker appearance. Download to get correct results.")
-
             with gr.Row():
                 gr.Markdown('''Try a different <b>seed value</b> if the result is unsatisfying (Default: 42).''')
 
@@ -470,19 +397,5 @@ with gr.Blocks() as demo:
         inputs=[input_image, do_remove_background, sample_steps, sample_seed],
         outputs=[viewer]
     )
-    # submit.click(fn=check_input_image, inputs=[input_image]).success(
-    #     fn=preprocess,
-    #     inputs=[input_image, do_remove_background],
-    #     outputs=[processed_image],
-    # ).success(
-    #     fn=generate_mvs,
-    #     inputs=[processed_image, sample_steps, sample_seed],
-    #     outputs=[mv_images, mv_show_images]
-
-    # ).success(
-    #     fn=make3d,
-    #     inputs=[mv_images],
-    #     outputs=[output_model_obj, output_model_glb]
-    # )
 
 demo.launch()