Upgrade pyright

nerfstudio/exporter/marching_cubes.py

@@ -249,7 +249,7 @@ def evaluate(points: torch.Tensor) -> torch.Tensor:
                     )
                     verts = verts + np.array([x_min, y_min, z_min])
 
-                    meshcrop = trimesh.Trimesh(verts, faces, normals)
+                    meshcrop = trimesh.Trimesh(verts, faces, normals)  # type: ignore
                     meshes.append(meshcrop)
 
     combined_mesh: trimesh.Trimesh = trimesh.util.concatenate(meshes)  # type: ignore

nerfstudio/process_data/hloc_utils.py

@@ -29,7 +29,7 @@
 try:
     # TODO(1480) un-hide pycolmap import
     import pycolmap
-    from hloc import (
+    from hloc import (  # type: ignore
         extract_features,
         match_features,
         pairs_from_exhaustive,
@@ -38,6 +38,7 @@
     )
 except ImportError:
     _HAS_HLOC = False
+
 else:
     _HAS_HLOC = True
 
@@ -95,24 +96,24 @@ def run_hloc(
     features = outputs / "features.h5"
     matches = outputs / "matches.h5"
 
-    retrieval_conf = extract_features.confs["netvlad"]
-    feature_conf = extract_features.confs[feature_type]
-    matcher_conf = match_features.confs[matcher_type]
+    retrieval_conf = extract_features.confs["netvlad"]  # type: ignore
+    feature_conf = extract_features.confs[feature_type]  # type: ignore
+    matcher_conf = match_features.confs[matcher_type]  # type: ignore
 
     references = [p.relative_to(image_dir).as_posix() for p in image_dir.iterdir()]
-    extract_features.main(feature_conf, image_dir, image_list=references, feature_path=features)
+    extract_features.main(feature_conf, image_dir, image_list=references, feature_path=features)  # type: ignore
     if matching_method == "exhaustive":
-        pairs_from_exhaustive.main(sfm_pairs, image_list=references)
+        pairs_from_exhaustive.main(sfm_pairs, image_list=references)  # type: ignore
     else:
-        retrieval_path = extract_features.main(retrieval_conf, image_dir, outputs)
+        retrieval_path = extract_features.main(retrieval_conf, image_dir, outputs)  # type: ignore
         if num_matched >= len(references):
             num_matched = len(references)
-        pairs_from_retrieval.main(retrieval_path, sfm_pairs, num_matched=num_matched)
-    match_features.main(matcher_conf, sfm_pairs, features=features, matches=matches)
+        pairs_from_retrieval.main(retrieval_path, sfm_pairs, num_matched=num_matched)  # type: ignore
+    match_features.main(matcher_conf, sfm_pairs, features=features, matches=matches)  # type: ignore
 
-    image_options = pycolmap.ImageReaderOptions(camera_model=camera_model.value)
+    image_options = pycolmap.ImageReaderOptions(camera_model=camera_model.value)  # type: ignore
     if refine_pixsfm:
-        sfm = PixSfM(
+        sfm = PixSfM(  # type: ignore
             conf={
                 "dense_features": {"use_cache": True},
                 "KA": {"dense_features": {"use_cache": True}, "max_kps_per_problem": 1000},
@@ -126,20 +127,20 @@ def run_hloc(
             features,
             matches,
             image_list=references,
-            camera_mode=pycolmap.CameraMode.SINGLE,
+            camera_mode=pycolmap.CameraMode.SINGLE,  # type: ignore
             image_options=image_options,
             verbose=verbose,
         )
         print("Refined", refined.summary())
 
     else:
-        reconstruction.main(
+        reconstruction.main(  # type: ignore
             sfm_dir,
             image_dir,
             sfm_pairs,
             features,
             matches,
-            camera_mode=pycolmap.CameraMode.SINGLE,
+            camera_mode=pycolmap.CameraMode.SINGLE,  # type: ignore
             image_options=image_options,
             verbose=verbose,
         )

nerfstudio/scripts/render.py

@@ -18,12 +18,12 @@
 """
 from __future__ import annotations
 
+import gzip
 import json
 import os
-import struct
 import shutil
+import struct
 import sys
-import gzip
 from contextlib import ExitStack, contextmanager
 from dataclasses import dataclass, field
 from pathlib import Path
@@ -54,11 +54,14 @@
     get_spiral_path,
 )
 from nerfstudio.cameras.cameras import Cameras, CameraType, RayBundle
+from nerfstudio.data.datamanagers.base_datamanager import (
+    VanillaDataManager,
+    VanillaDataManagerConfig,
+)
 from nerfstudio.data.datasets.base_dataset import Dataset
-from nerfstudio.data.datamanagers.base_datamanager import VanillaDataManager, VanillaDataManagerConfig
+from nerfstudio.data.scene_box import OrientedBox
 from nerfstudio.data.utils.dataloaders import FixedIndicesEvalDataloader
 from nerfstudio.engine.trainer import TrainerConfig
-from nerfstudio.data.scene_box import OrientedBox
 from nerfstudio.model_components import renderers
 from nerfstudio.pipelines.base_pipeline import Pipeline
 from nerfstudio.utils import colormaps, install_checks
@@ -318,6 +321,9 @@ def get_crop_from_json(camera_json: Dict[str, Any]) -> Optional[CropData]:
     center = camera_json["crop"]["crop_center"]
     scale = camera_json["crop"]["crop_scale"]
     rot = (0.0, 0.0, 0.0) if "crop_rot" not in camera_json["crop"] else tuple(camera_json["crop"]["crop_rot"])
+    assert len(center) == 3
+    assert len(scale) == 3
+    assert len(rot) == 3
     return CropData(
         background_color=torch.Tensor([bg_color["r"] / 255.0, bg_color["g"] / 255.0, bg_color["b"] / 255.0]),
         obb=OrientedBox.from_params(center, rot, scale),

nerfstudio/utils/plotly_utils.py

@@ -239,6 +239,7 @@ def get_cube(
     if isinstance(side_length, float):
         pts *= side_length / 2.0
     else:
+        assert isinstance(side_length, torch.Tensor)
         pts[0] *= side_length[0].item() / 2.0
         pts[1] *= side_length[1].item() / 2.0
         pts[2] *= side_length[2].item() / 2.0

nerfstudio/viewer/server/control_panel.py

@@ -196,7 +196,7 @@ def update_output_options(self, new_options: List[str]):
         self._split_output_render.set_options(new_options)
         self._split_output_render.value = new_options[-1]
 
-    def add_element(self, e: ViewerElement, additional_tags: Tuple[str] = tuple()) -> None:
+    def add_element(self, e: ViewerElement, additional_tags: Tuple[str, ...] = tuple()) -> None:
         """Adds an element to the control panel
 
         Args:

nerfstudio/viewer/server/viewer_state.py

@@ -198,8 +198,8 @@ def _crop_params_update(self, _) -> None:
         self.viser_server.send_crop_params(
             crop_enabled=self.control_panel.crop_viewport,
             crop_bg_color=self.control_panel.background_color,
-            crop_scale=tuple(crop_scale.tolist()),
-            crop_center=tuple(crop_center.tolist()),
+            crop_scale=tuple(crop_scale.tolist()),  # type: ignore
+            crop_center=tuple(crop_center.tolist()),  # type: ignore
         )
         if self.camera_message is not None:
             self.render_statemachine.action(RenderAction("rerender", self.camera_message))
@@ -258,8 +258,8 @@ def _handle_crop_params_message(self, message: NerfstudioMessage) -> None:
         scale = np.array(message.crop_scale)
         crop_min = center - scale / 2.0
         crop_max = center + scale / 2.0
-        self.control_panel.crop_min = tuple(crop_min.tolist())
-        self.control_panel.crop_max = tuple(crop_max.tolist())
+        self.control_panel.crop_min = tuple(crop_min.tolist())  # type: ignore
+        self.control_panel.crop_max = tuple(crop_max.tolist())  # type: ignore
 
     def _handle_click_message(self, message: NerfstudioMessage) -> None:
         """Handle click message from viewer."""

nerfstudio/viewer/viser/message_api.py

@@ -501,8 +501,8 @@ def update_scene_box(self, scene_box: SceneBox) -> None:
         """
         self._queue(
             messages.SceneBoxMessage(
-                min=tuple(scene_box.aabb[0].tolist()),
-                max=tuple(scene_box.aabb[1].tolist()),
+                min=tuple(scene_box.aabb[0].tolist()),  # type: ignore
+                max=tuple(scene_box.aabb[1].tolist()),  # type: ignore
             )
         )
 

nerfstudio/viewer_beta/control_panel.py

@@ -19,6 +19,8 @@
 import numpy as np
 import torch
 import viser.transforms as vtf
+from viser import ViserServer
+
 from nerfstudio.data.scene_box import OrientedBox
 from nerfstudio.utils.colormaps import ColormapOptions, Colormaps
 from nerfstudio.viewer_beta.viewer_elements import (  # ViewerButtonGroup,
@@ -32,7 +34,6 @@
     ViewerSlider,
     ViewerVec3,
 )
-from viser import ViserServer
 
 
 class ControlPanel:
@@ -147,7 +148,7 @@ def __init__(
         self._crop_handle = self.viser_server.add_transform_controls("Crop", depth_test=False, line_width=4.0)
 
         def update_center(han):
-            self._crop_handle.position = tuple(p * self.viser_scale_ratio for p in han.value)
+            self._crop_handle.position = tuple(p * self.viser_scale_ratio for p in han.value)  # type: ignore
 
         self._crop_center = ViewerVec3(
             "Crop Center",
@@ -175,7 +176,7 @@ def update_rot(han):
         @self._crop_handle.on_update
         def _update_crop_handle(han):
             pos = self._crop_handle.position
-            self._crop_center.value = tuple(p / self.viser_scale_ratio for p in pos)
+            self._crop_center.value = tuple(p / self.viser_scale_ratio for p in pos)  # type: ignore
             rpy = vtf.SO3(self._crop_handle.wxyz).as_rpy_radians()
             self._crop_rot.value = (float(rpy.roll), float(rpy.pitch), float(rpy.yaw))
 
@@ -280,7 +281,7 @@ def update_output_options(self, new_options: List[str]):
         self._split_output_render.set_options(new_options)
         self._split_output_render.value = new_options[-1]
 
-    def add_element(self, e: ViewerElement, additional_tags: Tuple[str] = tuple()) -> None:
+    def add_element(self, e: ViewerElement, additional_tags: Tuple[str, ...] = tuple()) -> None:
         """Adds an element to the control panel
 
         Args:

nerfstudio/viewer_beta/viewer.py

@@ -326,7 +326,7 @@ def init_scene(
             )
 
             @camera_handle.on_click
-            def _(event: viser.ClickEvent[viser.CameraFrustumHandle]) -> None:
+            def _(event: viser.SceneNodePointerEvent[viser.CameraFrustumHandle]) -> None:
                 assert self.client is not None
                 with self.client.atomic():
                     self.client.camera.position = event.target.position

pyproject.toml

@@ -53,7 +53,7 @@ dependencies = [
     "torchvision>=0.14.1",
     "torchmetrics[image]>=1.0.1",
     "typing_extensions>=4.4.0",
-    "viser==0.1.6",
+    "viser==0.1.7",
     "nuscenes-devkit>=1.1.1",
     "wandb>=0.13.3",
     "xatlas",
@@ -90,7 +90,7 @@ dev = [
     "diffusers==0.16.1",
     "opencv-stubs==0.0.7",
     "transformers==4.29.2",
-    "pyright==1.1.308",
+    "pyright==1.1.331",
 ]
 
 # Documentation related packages