Added examples (files incoming)

app.py

@@ -42,6 +42,18 @@ def _safe_ext(path: str) -> str:
             return ext
     return os.path.splitext(path)[1].lower()
 
+def convert_and_show(mesh_file):
+    os.makedirs("tmp/glbs", exist_ok=True)
+    if mesh_file is None:
+        return None
+    mesh = trimesh.load(mesh_file.name)
+    tn = int(np.random.rand()*1e10)
+    f_name = f"tmp/glbs/mesh_{tn}.glb"
+    mesh.export(f_name)
+    return f_name
+
+def convert_and_show_twice(mesh_file_1, mesh_file_2):
+    return convert_and_show(mesh_file_1), convert_and_show(mesh_file_2)
 
 def normalize_vertices(vertices: np.ndarray) -> np.ndarray:
     v = vertices.astype(np.float64)
@@ -78,9 +90,9 @@ def export_for_view(surf: Surface, colors: np.ndarray, basename: str, outdir: st
 # -----------------------------
 DEFAULT_SETTINGS = {
     "deepfeat_conf.fmap.lambda_": 1,
-    "sds_conf.zoomout": 40.0,
+    "sds_conf.zoomout": 32,
     "diffusion.time": 1.0,
-    "opt.n_loop": 300,
+    "opt.n_loop": 250,
     "loss.sds": 1.0,
     "loss.proper": 1.0,
 }
@@ -211,28 +223,57 @@ def run_clicked(mesh1_path, mesh2_path, yaml_path, lambda_val, zoomout_val, time
     evecs1, evecs2 = datadicts.shape_dict["evecs"], datadicts.target_dict["evecs"]
     evecs_2trans = evecs2.t() @ torch.diag(datadicts.target_dict["mass"])
     with torch.no_grad():
-        C12_end_zo = torch_zoomout(evecs1, evecs2, evecs_2trans, C12_new.squeeze()[:15, :15], matcher.cfg.sds_conf.zoomout)
+        C12_end_zo = torch_zoomout(evecs1, evecs2, evecs_2trans, C12_new.squeeze(), matcher.cfg.sds_conf.zoomout)
     p2p_zo, _ = extract_p2p_torch_fmap(C12_end_zo, datadicts.shape_dict["evecs"], datadicts.target_dict["evecs"])
     return build_outputs(datadicts.shape_surf, datadicts.target_surf, datadicts.cmap1, p2p_zo, tag="run")
 
 
 with gr.Blocks(title="DiffuMatch demo") as demo:
-    text_in = "Upload two meshes and try our ICCV zero-shot method DiffuMatch! \n"
-    text_in += "*Init* will give you a rough correspondence, and you can click on *Run* to see if our method is able to match the two shapes! \n"
-    text_in += "*Recommended*: The method requires that the meshes are aligned (rotation-wise) to work well. Also might not work with scans (but try it out!)."
-    gr.Markdown(text_in)
+    gr.Markdown(
+        """
+        <div align="center">
+        <h1>DiffuMatch: Category-Agnostic Spectral Diffusion Priors for Robust Non-rigid Shape Matching</h1>
+        </div>
+        <br/>
+        Upload two meshes and try our ICCV zero-shot method <a href="https://daidedou.github.io/publication/nonrigiddiff">DiffuMatch</a> <br/>
+        <b>Init</b> will give you a rough correspondence, and you can click on <b>Run</b> to see if our method is able to match the two shapes! <br/>
+        <b>Recommended</b/>: The method requires that the meshes are aligned (rotation-wise) to work well. Also might not work with scans (but try it out!). <br/>
+        """
+    )
     with gr.Row():
-        mesh1 = gr.File(label="Mesh A (.ply/.obj/.off)")
-        mesh2 = gr.File(label="Mesh B (.ply/.obj/.off)")
+        with gr.Column():
+            mesh1 = gr.File(label="Source Mesh (.ply, .off, .obj)", file_types=[".ply", ".off", ".obj"])
+            mesh1_viewer = gr.Model3D(label="Preview Source")
+            mesh1.upload(fn=convert_and_show, inputs=mesh1, outputs=mesh1_viewer)
+
+        with gr.Column():
+            mesh2 = gr.File(label="Target Mesh (.ply, .off, .obj)", file_types=[".ply", ".off", ".obj"])
+            mesh2_viewer = gr.Model3D(label="Preview Target")
+            mesh2.upload(fn=convert_and_show, inputs=mesh2, outputs=mesh2_viewer)
+
         yaml_file = gr.File(label="Optional YAML config", file_types=[".yaml", ".yml"], visible=True)
+
+    gr.Examples(
+        examples=[
+            ["examples/man.ply", "examples/woman.ply"],
+            ["examples/wolf.ply", "examples/horse.ply"],
+            ["examples/cactus.off", "examples/cactus_deformed.off"],
+        ],
+        fn=convert_and_show_twice,
+        inputs=[mesh1, mesh2],
+        outputs=[mesh1_viewer, mesh2_viewer],
+        label="Try some example pairs",
+        cache_examples=True
+    )
+
     # except Exception:
     with gr.Accordion("Settings", open=True):
         with gr.Row():
-            lambda_val = gr.Slider(minimum=FLOAT_SLIDERS["deepfeat_conf.fmap.lambda_"][0], maximum=FLOAT_SLIDERS["deepfeat_conf.fmap.lambda_"][1], step=FLOAT_SLIDERS["deepfeat_conf.fmap.lambda_"][2], value=1, label="deepfeat_conf.fmap.lambda_")
-            zoomout_val = gr.Slider(minimum=INT_SLIDERS["sds_conf.zoomout"][0], maximum=INT_SLIDERS["sds_conf.zoomout"][1], step=INT_SLIDERS["sds_conf.zoomout"][2], value=40, label="sds_conf.zoomout")
-            time_val = gr.Slider(minimum=FLOAT_SLIDERS["diffusion.time"][0], maximum=FLOAT_SLIDERS["diffusion.time"][1], step=FLOAT_SLIDERS["diffusion.time"][2], value=1, label="diffusion.time")
+            lambda_val = gr.Slider(minimum=FLOAT_SLIDERS["deepfeat_conf.fmap.lambda_"][0], maximum=FLOAT_SLIDERS["deepfeat_conf.fmap.lambda_"][1], step=FLOAT_SLIDERS["deepfeat_conf.fmap.lambda_"][2], value=DEFAULT_SETTINGS["deepfeat_conf.fmap.lambda_"], label="deepfeat_conf.fmap.lambda_")
+            zoomout_val = gr.Slider(minimum=INT_SLIDERS["sds_conf.zoomout"][0], maximum=INT_SLIDERS["sds_conf.zoomout"][1], step=INT_SLIDERS["sds_conf.zoomout"][2], value=DEFAULT_SETTINGS["sds_conf.zoomout"], label="sds_conf.zoomout")
+            time_val = gr.Slider(minimum=FLOAT_SLIDERS["diffusion.time"][0], maximum=FLOAT_SLIDERS["diffusion.time"][1], step=FLOAT_SLIDERS["diffusion.time"][2], value=DEFAULT_SETTINGS["diffusion.time"], label="diffusion.time")
         with gr.Row():
-            nloop_val = gr.Slider(minimum=INT_SLIDERS["opt.n_loop"][0], maximum=INT_SLIDERS["opt.n_loop"][1], step=INT_SLIDERS["opt.n_loop"][2], value=300, label="opt.n_loop")
+            nloop_val = gr.Slider(minimum=INT_SLIDERS["opt.n_loop"][0], maximum=INT_SLIDERS["opt.n_loop"][1], step=INT_SLIDERS["opt.n_loop"][2], value=DEFAULT_SETTINGS["opt.n_loop"], label="opt.n_loop")
             sds_val = gr.Slider(minimum=FLOAT_SLIDERS["loss.sds"][0], maximum=FLOAT_SLIDERS["loss.sds"][1], step=FLOAT_SLIDERS["loss.sds"][2], value=1, label="loss.sds")
             proper_val = gr.Slider(minimum=FLOAT_SLIDERS["loss.proper"][0], maximum=FLOAT_SLIDERS["loss.proper"][1], step=FLOAT_SLIDERS["loss.proper"][2], value=1, label="loss.proper")