fix

app.py

@@ -31,6 +31,32 @@ from vggt.utils.load_fn import load_and_preprocess_images
 from vggt.utils.pose_enc import pose_encoding_to_extri_intri
 from vggt.utils.geometry import unproject_depth_map_to_point_map
 
+# set random seed
+# (random seed affect pca color, yet change random seed need manual adjustment kmeans)
+# (the pca prevent in paper is with another version of cuda and pytorch environment)
+concerto.utils.set_seed(53124)
+# Load model (to CPU; moved to GPU on-demand via @spaces.GPU)
+if flash_attn is not None:
+    print("Loading model with Flash Attention.")
+    concerto_model = concerto.load("concerto_large", repo_id="Pointcept/Concerto")
+    sonata_model = concerto.model.load("sonata", repo_id="facebook/sonata")
+else:
+    print("Loading model without Flash Attention.")
+    custom_config = dict(
+        # enc_patch_size=[1024 for _ in range(5)],  # reduce patch size if necessary
+        enable_flash=False,
+    )
+    concerto_model = concerto.load(
+        "concerto_large", repo_id="Pointcept/Concerto", custom_config=custom_config
+    )
+    sonata_model = concerto.load("sonata", repo_id="facebook/sonata", custom_config=custom_config)
+
+transform = concerto.transform.default()
+
+VGGT_model = VGGT()
+_URL = "https://huggingface.co/facebook/VGGT-1B/resolve/main/model.pt"
+VGGT_model.load_state_dict(torch.hub.load_state_dict_from_url(_URL))
+
 @spaces.GPU
 def _gpu_run_vggt_inference(images_tensor):
     """
@@ -568,27 +594,23 @@ def get_pca_color(feat, start = 0, brightness=1.25, center=True):
     return color
 
 @spaces.GPU
-def _gpu_concerto_forward_pca(point, model_type, pca_slider, bright_slider):
+def _gpu_concerto_forward_pca(point, concerto_model_, pca_slider, bright_slider):
     """
     GPU-only function: Run Concerto/Sonata model forward pass and PCA.
     """
-    global concerto_model, sonata_model
     device = "cuda" if torch.cuda.is_available() else "cpu"
 
     for key in point.keys():
         if isinstance(point[key], torch.Tensor):
             point[key] = point[key].to(device, non_blocking=True)
 
-    if model_type == "Concerto":
-        model = concerto_model.to(device)
-    elif model_type == "Sonata":
-        model = sonata_model.to(device)
-    model.eval()
+    concerto_model_ = concerto_model_.to(device)
+    concerto_model_.eval()
 
     with torch.inference_mode():
         concerto_start_time = time.time()
         with torch.inference_mode(False):
-            point = model(point)
+            point = concerto_model_(point)
         concerto_end_time = time.time()
 
         # upcast point feature
@@ -628,9 +650,17 @@ def Concerto_process(target_dir, original_points, original_colors, original_norm
     original_coord = point["coord"].copy()
     point = transform(point)
 
+    # Select model based on type
+    if model_type == "Concerto":
+        selected_model = concerto_model
+    elif model_type == "Sonata":
+        selected_model = sonata_model
+    else:
+        selected_model = concerto_model
+
     # GPU: Run model forward + PCA
     processed_colors, point_feat, point_inverse, concerto_time, pca_time = _gpu_concerto_forward_pca(
-        point, model_type, slider_value, bright_value
+        point, selected_model, slider_value, bright_value
     )
 
     # CPU: Save features
@@ -705,33 +735,6 @@ def concerto_slider_update(target_dir,pca_slider,bright_slider,is_example,log_ou
             log_output = "No representations saved, please click PCA generate first."
     return processed_temp, log_output
 
-# set random seed
-# (random seed affect pca color, yet change random seed need manual adjustment kmeans)
-# (the pca prevent in paper is with another version of cuda and pytorch environment)
-concerto.utils.set_seed(53124)
-# Load model (to CPU; moved to GPU on-demand via @spaces.GPU)
-if flash_attn is not None:
-    print("Loading model with Flash Attention.")
-    concerto_model = concerto.load("concerto_large", repo_id="Pointcept/Concerto")
-    sonata_model = concerto.model.load("sonata", repo_id="facebook/sonata")
-else:
-    print("Loading model without Flash Attention.")
-    custom_config = dict(
-        # enc_patch_size=[1024 for _ in range(5)],  # reduce patch size if necessary
-        enable_flash=False,
-    )
-    concerto_model = concerto.load(
-        "concerto_large", repo_id="Pointcept/Concerto", custom_config=custom_config
-    )
-    sonata_model = concerto.load("sonata", repo_id="facebook/sonata", custom_config=custom_config)
-
-transform = concerto.transform.default()
-
-VGGT_model = VGGT()
-_URL = "https://huggingface.co/facebook/VGGT-1B/resolve/main/model.pt"
-VGGT_model.load_state_dict(torch.hub.load_state_dict_from_url(_URL))
-# VGGT_model.load_state_dict(torch.load("vggt/ckpt/model.pt",weights_only=True))
-
 
 BASE_URL = "https://huggingface.co/datasets/pointcept-bot/concerto_huggingface_demo/resolve/main/"
 def get_url(path):