From d413ca42042ae7b2dabdbe137c7eca7bceb42b88 Mon Sep 17 00:00:00 2001
From: Milan van Wouden <56082205+MvWouden@users.noreply.github.com>
Date: Tue, 23 May 2023 19:41:49 +0200
Subject: [PATCH] fix large number of typos in repository (#1977)

* fix large number of typos in repository

* fix typos in tests
---
 docs/developer_guides/pipelines/dataparsers.md       |  2 +-
 docs/extensions/sdfstudio.md                         |  2 +-
 docs/index.md                                        |  2 +-
 docs/nerfology/methods/in2n.md                       |  2 +-
 docs/nerfology/methods/instant_ngp.md                |  6 +++---
 nerfstudio/cameras/cameras.py                        |  2 +-
 nerfstudio/configs/method_configs.py                 |  2 +-
 nerfstudio/data/datamanagers/base_datamanager.py     |  8 ++++----
 .../data/dataparsers/arkitscenes_dataparser.py       |  2 +-
 .../data/dataparsers/instant_ngp_dataparser.py       |  2 +-
 nerfstudio/data/pixel_samplers.py                    |  2 +-
 nerfstudio/fields/nerfplayer_ngp_field.py            |  2 +-
 nerfstudio/model_components/scene_colliders.py       |  2 +-
 nerfstudio/models/base_surface_model.py              |  6 +++---
 nerfstudio/process_data/colmap_utils.py              | 12 ++++++------
 nerfstudio/process_data/equirect_utils.py            |  2 +-
 nerfstudio/scripts/blender/nerfstudio_blender.py     |  4 ++--
 nerfstudio/scripts/completions/install.py            |  2 +-
 nerfstudio/scripts/exporter.py                       |  2 +-
 nerfstudio/utils/plotly_utils.py                     |  2 +-
 nerfstudio/viewer/app/src/index.scss                 |  2 +-
 .../modules/SidePanel/CameraPanel/CameraPanel.jsx    |  2 +-
 .../ViewportControlsModal/ViewportControlsModal.jsx  |  2 +-
 nerfstudio/viewer/server/gui_utils.py                |  2 +-
 nerfstudio/viewer/server/render_state_machine.py     |  6 +++---
 nerfstudio/viewer/server/viewer_state.py             |  2 +-
 nerfstudio/viewer/viser/__init__.py                  |  2 +-
 nerfstudio/viewer/viser/message_api.py               |  2 +-
 nerfstudio/viewer/viser/messages.py                  |  4 ++--
 tests/model_components/test_losses.py                |  2 +-
 tests/process_data/test_process_images.py            |  2 +-
 tests/utils/test_aabb_intersection.py                |  2 +-
 32 files changed, 48 insertions(+), 48 deletions(-)

diff --git a/docs/developer_guides/pipelines/dataparsers.md b/docs/developer_guides/pipelines/dataparsers.md
index 19b964e5a..cb1693aa7 100644
--- a/docs/developer_guides/pipelines/dataparsers.md
+++ b/docs/developer_guides/pipelines/dataparsers.md
@@ -117,7 +117,7 @@ dataparser_outputs = dataparser.get_dataparser_outputs(split="train")
 input_dataset = InputDataset(dataparser_outputs)
 ```
 
-You can also pull out information from the DataParserOutputs for other DataMangager components, such as the RayGenerator. The RayGenerator generates RayBundle objects from camera and pixel indices.
+You can also pull out information from the DataParserOutputs for other DataManager components, such as the RayGenerator. The RayGenerator generates RayBundle objects from camera and pixel indices.
 
 ```python
 ray_generator = RayGenerator(dataparser_outputs.cameras)
diff --git a/docs/extensions/sdfstudio.md b/docs/extensions/sdfstudio.md
index 4c8f24874..fa2625d0f 100644
--- a/docs/extensions/sdfstudio.md
+++ b/docs/extensions/sdfstudio.md
@@ -29,7 +29,7 @@ You can learn more about these methods [here](https://github.com/autonomousvisio
 
 ## Surface models in nerfstudio
 
-We intend to integrate many of the SDFStudio improvments back into the nerstudio core repository.
+We intend to integrate many of the SDFStudio improvements back into the nerfstudio core repository.
 
 Supported methods:
 
diff --git a/docs/index.md b/docs/index.md
index e34650018..5da1ec477 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -103,7 +103,7 @@ This documentation is organized into 3 parts:
 
 - [**Nerfacto**](nerfology/methods/nerfacto.md): Recommended method, integrates mutiple methods into one.
 - [Instant-NGP](nerfology/methods/instant_ngp.md): Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
-- [NeRF](nerfology/methods/nerf.md): OG Nerual Radiance Fields
+- [NeRF](nerfology/methods/nerf.md): OG Neural Radiance Fields
 - [Mip-NeRF](nerfology/methods/mipnerf.md): A Multiscale Representation for Anti-Aliasing Neural Radiance Fields
 - [TensoRF](nerfology/methods/tensorf.md): Tensorial Radiance Fields
 
diff --git a/docs/nerfology/methods/in2n.md b/docs/nerfology/methods/in2n.md
index bd9ebccb6..3b75d9a51 100644
--- a/docs/nerfology/methods/in2n.md
+++ b/docs/nerfology/methods/in2n.md
@@ -83,7 +83,7 @@ The code snippet for how an image is edited in the pipeline can be found [here](
 
 When NeRF training starts, the dataset consists of the original, unedited images used to train the original scene. These images are saved separately to use as conditioning for InstructPix2Pix. At each optimization step, some number of NeRF optimization steps are performed, and then some number of images (often just one) are updated. The images are randomly ordered prior to training and then at each step, the images are chosen in order to edit. Once an image has been edited, it is replaced in the dataset. Importantly, at each NeRF step, rays are sampled across the entire dataset, meaning there is a mixed source of supervision between edited images and unedited images. This allows for a gradual optimization that balances maintaining the 3D structure and consistency of the NeRF as well as performing the edit.
 
-At early iterations of this process, the edited images may be inconistent with one another, as InstructPix2Pix often doesn't perform consistent edits across viewpoints. However, over time, since images are edited using the current render of the NeRF, the edits begin to converge towards a globally consistent depiction of the underlying scene. Here is an example of how the underlying dataset evolves and becomes more consistent.
+At early iterations of this process, the edited images may be inconsistent with one another, as InstructPix2Pix often doesn't perform consistent edits across viewpoints. However, over time, since images are edited using the current render of the NeRF, the edits begin to converge towards a globally consistent depiction of the underlying scene. Here is an example of how the underlying dataset evolves and becomes more consistent.
 
 <video id="idu" muted autoplay playsinline loop controls width="100%">
     <source id="mp4" src="https://instruct-nerf2nerf.github.io/data/videos/du_update.mp4" type="video/mp4">
diff --git a/docs/nerfology/methods/instant_ngp.md b/docs/nerfology/methods/instant_ngp.md
index 98d253011..c7589e295 100644
--- a/docs/nerfology/methods/instant_ngp.md
+++ b/docs/nerfology/methods/instant_ngp.md
@@ -36,7 +36,7 @@ The core idea behind the improved sampling technique is that sampling over empty
 
 Nerfstudio uses [NerfAcc](https://www.nerfacc.com/en/latest/index.html) as the sampling algorithm implementation. The details on NerfAcc's sampling and occupancy grid is discussed [here](https://www.nerfacc.com/en/stable/methodology/sampling.html#occupancy-grid-estimator).
 
-Another major bottleneck for NeRF's training speed has been querying the neural network. The authors of this work implement the network such that it runs entirely on a single CUDA kernal. The network is also shrunk down to be just 4 layers with 64 neurons in each layer. They show that their fully-fused neural network is 5-10x faster than a Tensorflow implementation.
+Another major bottleneck for NeRF's training speed has been querying the neural network. The authors of this work implement the network such that it runs entirely on a single CUDA kernel. The network is also shrunk down to be just 4 layers with 64 neurons in each layer. They show that their fully-fused neural network is 5-10x faster than a Tensorflow implementation.
 
 Nerfstudio uses the [tinycudann](https://github.com/NVlabs/tiny-cuda-nn) framework to utilize the fully-fused neural networks.
 
@@ -62,8 +62,8 @@ Steps 1-3 are done independently at each resolution level. Thus, since these fea
 
 An important note is that hash collisions are not explicitly handled. At each hash index, there may be multiple vertices which index to that feature vector, but because these vectors are trainable, the vertices that are most important to the specific output will have the highest gradient, and therefore automatically dominate the optimization of that feature.
 
-This encoding structure creates a tradeoff betweewn quality, memory, and performance. The main parameters which can be adjusted are the size of the hash table (T), the size of the feature vectors (F), and the number of resolutions (L).
+This encoding structure creates a tradeoff between quality, memory, and performance. The main parameters which can be adjusted are the size of the hash table (T), the size of the feature vectors (F), and the number of resolutions (L).
 
-Instant-NGP encodes the vieweing direction using spherical harmonic encodings.
+Instant-NGP encodes the viewing direction using spherical harmonic encodings.
 
 Our [`nerfacto`](./nerfacto.md) model uses both the fully-fused MLP and the hash encoder, which were inspired by Instant-NGP. Lastly, our implementation covers the major ideas from Instant-NGP, but it doesn't strictly follow every detail. Some known differences include learning rate schedulers, hyper-parameters for sampling, and how camera gradients are calculated if enabled.
diff --git a/nerfstudio/cameras/cameras.py b/nerfstudio/cameras/cameras.py
index 2bff5575c..33ca498aa 100644
--- a/nerfstudio/cameras/cameras.py
+++ b/nerfstudio/cameras/cameras.py
@@ -357,7 +357,7 @@ class Cameras(TensorDataclass):
                 keeping dimensions. If False, we flatten at the end. If True, then we keep the shape of the
                 camera_indices and coords tensors (if we can).
             disable_distortion: If True, disables distortion.
-            aabb_box: if not None will calculate nears and fars of the ray according to aabb box intesection
+            aabb_box: if not None will calculate nears and fars of the ray according to aabb box intersection
 
         Returns:
             Rays for the given camera indices and coords.
diff --git a/nerfstudio/configs/method_configs.py b/nerfstudio/configs/method_configs.py
index 8fe4ac57b..027b01352 100644
--- a/nerfstudio/configs/method_configs.py
+++ b/nerfstudio/configs/method_configs.py
@@ -562,7 +562,7 @@ method_configs["neus-facto"] = TrainerConfig(
             ),
         ),
         model=NeuSFactoModelConfig(
-            # proposal network allows for signifanctly smaller sdf/color network
+            # proposal network allows for significantly smaller sdf/color network
             sdf_field=SDFFieldConfig(
                 use_grid_feature=True,
                 num_layers=2,
diff --git a/nerfstudio/data/datamanagers/base_datamanager.py b/nerfstudio/data/datamanagers/base_datamanager.py
index e0954f3e8..707659d95 100644
--- a/nerfstudio/data/datamanagers/base_datamanager.py
+++ b/nerfstudio/data/datamanagers/base_datamanager.py
@@ -246,7 +246,7 @@ class DataManager(nn.Module):
             step: the step number of the eval image to retrieve
         Returns:
             A tuple of the ray bundle for the image, and a dictionary of additional batch information
-            such as the groudtruth image.
+            such as the groundtruth image.
         """
         raise NotImplementedError
 
@@ -258,19 +258,19 @@ class DataManager(nn.Module):
             step: the step number of the eval image to retrieve
         Returns:
             A tuple of the ray bundle for the image, and a dictionary of additional batch information
-            such as the groudtruth image.
+            such as the groundtruth image.
         """
         raise NotImplementedError
 
     @abstractmethod
     def next_eval_image(self, step: int) -> Tuple[int, RayBundle, Dict]:
-        """Retreive the next eval image.
+        """Retrieve the next eval image.
 
         Args:
             step: the step number of the eval image to retrieve
         Returns:
             A tuple of the step number, the ray bundle for the image, and a dictionary of
-            additional batch information such as the groudtruth image.
+            additional batch information such as the groundtruth image.
         """
         raise NotImplementedError
 
diff --git a/nerfstudio/data/dataparsers/arkitscenes_dataparser.py b/nerfstudio/data/dataparsers/arkitscenes_dataparser.py
index 290bd6810..ada6f941a 100644
--- a/nerfstudio/data/dataparsers/arkitscenes_dataparser.py
+++ b/nerfstudio/data/dataparsers/arkitscenes_dataparser.py
@@ -64,7 +64,7 @@ def traj_string_to_matrix(traj_string: str):
 class ARKitScenesDataParserConfig(DataParserConfig):
     """ARKitScenes dataset config.
     ARKitScenes dataset (http://github.com/apple/ARKitScenes) is a large-scale 3D dataset of indoor scenes.
-    This dataparser uses 3D deteciton subset of the ARKitScenes dataset.
+    This dataparser uses 3D detection subset of the ARKitScenes dataset.
     """
 
     _target: Type = field(default_factory=lambda: ARKitScenes)
diff --git a/nerfstudio/data/dataparsers/instant_ngp_dataparser.py b/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
index 9aeda39d8..12546cfeb 100644
--- a/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
+++ b/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
@@ -72,7 +72,7 @@ class InstantNGP(DataParser):
             if not fname.exists():
                 fname = data_dir / Path(frame["file_path"] + ".png")
             if not fname.exists():
-                CONSOLE.log(f"couldnt find {fname} image")
+                CONSOLE.log(f"couldn't find {fname} image")
                 num_skipped_image_filenames += 1
             else:
                 if "w" not in meta:
diff --git a/nerfstudio/data/pixel_samplers.py b/nerfstudio/data/pixel_samplers.py
index 396ba57a1..a145dce46 100644
--- a/nerfstudio/data/pixel_samplers.py
+++ b/nerfstudio/data/pixel_samplers.py
@@ -261,7 +261,7 @@ class PatchPixelSampler(PixelSampler):
         super().__init__(num_rays, keep_full_image, **kwargs)
 
     def set_num_rays_per_batch(self, num_rays_per_batch: int):
-        """Set the number of rays to sample per batch. Overrided to deal with patch-based sampling.
+        """Set the number of rays to sample per batch. Overridden to deal with patch-based sampling.
 
         Args:
             num_rays_per_batch: number of rays to sample per batch
diff --git a/nerfstudio/fields/nerfplayer_ngp_field.py b/nerfstudio/fields/nerfplayer_ngp_field.py
index 38f70e547..cdd122e13 100644
--- a/nerfstudio/fields/nerfplayer_ngp_field.py
+++ b/nerfstudio/fields/nerfplayer_ngp_field.py
@@ -64,7 +64,7 @@ class NerfplayerNGPField(Field):
             Sometimes we need to disable viewing dependent effects in a dynamic scene, because there is
             ambiguity between being dynamic and viewing dependent effects. For example, the shadow of the camera
             should be a dynamic effect, but may be reconstructed as viewing dependent effects.
-        num_images: number of images, requried if use_appearance_embedding is True
+        num_images: number of images, required if use_appearance_embedding is True
         appearance_embedding_dim: dimension of appearance embedding
         contraction_type: type of contraction
     """
diff --git a/nerfstudio/model_components/scene_colliders.py b/nerfstudio/model_components/scene_colliders.py
index fa6242011..3e2e793ae 100644
--- a/nerfstudio/model_components/scene_colliders.py
+++ b/nerfstudio/model_components/scene_colliders.py
@@ -137,7 +137,7 @@ class SphereCollider(SceneCollider):
 
     Args:
         center: center of sphere to intersect [3]
-        redius: radius of sphere to intersect
+        radius: radius of sphere to intersect
         near_plane: near plane to clamp to
     """
 
diff --git a/nerfstudio/models/base_surface_model.py b/nerfstudio/models/base_surface_model.py
index cd0e745d4..b5e2d373a 100644
--- a/nerfstudio/models/base_surface_model.py
+++ b/nerfstudio/models/base_surface_model.py
@@ -84,9 +84,9 @@ class SurfaceModelConfig(ModelConfig):
     background_model: Literal["grid", "mlp", "none"] = "mlp"
     """background models"""
     num_samples_outside: int = 32
-    """Number of samples outside the bounding sphere for backgound"""
+    """Number of samples outside the bounding sphere for background"""
     periodic_tvl_mult: float = 0.0
-    """Total variational loss mutliplier"""
+    """Total variational loss multiplier"""
     overwrite_near_far_plane: bool = False
     """whether to use near and far collider from command line"""
 
@@ -243,7 +243,7 @@ class SurfaceModel(Model):
             depth_bg = self.renderer_depth(weights=weights_bg, ray_samples=ray_samples_bg)
             accumulation_bg = self.renderer_accumulation(weights=weights_bg)
 
-            # merge background color to forgound color
+            # merge background color to foregound color
             rgb = rgb + bg_transmittance * rgb_bg
 
             bg_outputs = {
diff --git a/nerfstudio/process_data/colmap_utils.py b/nerfstudio/process_data/colmap_utils.py
index 4f17026f1..bccdaa2f1 100644
--- a/nerfstudio/process_data/colmap_utils.py
+++ b/nerfstudio/process_data/colmap_utils.py
@@ -605,28 +605,28 @@ def create_sfm_depth(
     return image_id_to_depth_path
 
 
-def get_matching_summary(num_intial_frames: int, num_matched_frames: int) -> str:
+def get_matching_summary(num_initial_frames: int, num_matched_frames: int) -> str:
     """Returns a summary of the matching results.
 
     Args:
-        num_intial_frames: The number of initial frames.
+        num_initial_frames: The number of initial frames.
         num_matched_frames: The number of matched frames.
 
     Returns:
         A summary of the matching results.
     """
-    match_ratio = num_matched_frames / num_intial_frames
+    match_ratio = num_matched_frames / num_initial_frames
     if match_ratio == 1:
         return "[bold green]COLMAP found poses for all images, CONGRATS!"
     if match_ratio < 0.4:
-        result = f"[bold red]COLMAP only found poses for {num_matched_frames / num_intial_frames * 100:.2f}%"
+        result = f"[bold red]COLMAP only found poses for {num_matched_frames / num_initial_frames * 100:.2f}%"
         result += " of the images. This is low.\nThis can be caused by a variety of reasons,"
         result += " such poor scene coverage, blurry images, or large exposure changes."
         return result
     if match_ratio < 0.8:
-        result = f"[bold yellow]COLMAP only found poses for {num_matched_frames / num_intial_frames * 100:.2f}%"
+        result = f"[bold yellow]COLMAP only found poses for {num_matched_frames / num_initial_frames * 100:.2f}%"
         result += " of the images.\nThis isn't great, but may be ok."
         result += "\nMissing poses can be caused by a variety of reasons, such poor scene coverage, blurry images,"
         result += " or large exposure changes."
         return result
-    return f"[bold green]COLMAP found poses for {num_matched_frames / num_intial_frames * 100:.2f}% of the images."
+    return f"[bold green]COLMAP found poses for {num_matched_frames / num_initial_frames * 100:.2f}% of the images."
diff --git a/nerfstudio/process_data/equirect_utils.py b/nerfstudio/process_data/equirect_utils.py
index 4217c97f2..a04f66363 100644
--- a/nerfstudio/process_data/equirect_utils.py
+++ b/nerfstudio/process_data/equirect_utils.py
@@ -199,7 +199,7 @@ def generate_planar_projections_from_equirectangular(
 
 
 def compute_resolution_from_equirect(image_dir: Path, num_images: int) -> Tuple[int, int]:
-    """Compute the resolution of the persepctive projections of equirectangular images
+    """Compute the resolution of the perspective projections of equirectangular images
        from the heuristic: num_image * res**2 = orig_height * orig_width.
 
     Args:
diff --git a/nerfstudio/scripts/blender/nerfstudio_blender.py b/nerfstudio/scripts/blender/nerfstudio_blender.py
index 8a2fa9908..c5f6e3251 100644
--- a/nerfstudio/scripts/blender/nerfstudio_blender.py
+++ b/nerfstudio/scripts/blender/nerfstudio_blender.py
@@ -244,7 +244,7 @@ class ReadJSONinputCameraPath(bpy.types.Operator):
     transformed_camera_path_mat = []  # final transformed world matrix of the camera at each frame
     input_json = None
 
-    def read_camera_coodinates(self):
+    def read_camera_coordinates(self):
         """Read the camera coordinates (world matrix and fov) from the json camera path."""
 
         json_cam_path = self.input_json["camera_path"]
@@ -333,7 +333,7 @@ class ReadJSONinputCameraPath(bpy.types.Operator):
             self.input_json = json.load(json_ns_file)
 
         # call methods to read cam path and create camera
-        self.read_camera_coodinates()
+        self.read_camera_coordinates()
         self.generate_camera()
 
         return {"FINISHED"}
diff --git a/nerfstudio/scripts/completions/install.py b/nerfstudio/scripts/completions/install.py
index 5f73bd2d2..d6d8b63b2 100644
--- a/nerfstudio/scripts/completions/install.py
+++ b/nerfstudio/scripts/completions/install.py
@@ -395,7 +395,7 @@ def main(mode: ConfigureMode = "install") -> None:
         assert_never(mode)
 
     if conda_path is not None:
-        # In conda environment we add the completitions activation scripts.
+        # In conda environment we add the completions activation scripts.
         commands = _get_all_entry_points()
         _update_conda_scripts(commands, completions_dir, mode)
     else:
diff --git a/nerfstudio/scripts/exporter.py b/nerfstudio/scripts/exporter.py
index aee9723a9..d8c8a0ac9 100644
--- a/nerfstudio/scripts/exporter.py
+++ b/nerfstudio/scripts/exporter.py
@@ -370,7 +370,7 @@ class ExportMarchingCubesMesh(Exporter):
             self.resolution % 512 == 0
         ), f"""resolution must be divisible by 512, got {self.resolution}.
         This is important because the algorithm uses a multi-resolution approach
-        to evaluate the SDF where the mimimum resolution is 512."""
+        to evaluate the SDF where the minimum resolution is 512."""
 
         # Extract mesh using marching cubes for sdf at a multi-scale resolution.
         multi_res_mesh = generate_mesh_with_multires_marching_cubes(
diff --git a/nerfstudio/utils/plotly_utils.py b/nerfstudio/utils/plotly_utils.py
index 9dbc7c851..00cab4760 100644
--- a/nerfstudio/utils/plotly_utils.py
+++ b/nerfstudio/utils/plotly_utils.py
@@ -16,7 +16,7 @@
 Visualization code for plotly.
 The function use prefix conventions in the following way:
     - 'get_*' functions (e.g., 'get_camera_frustums')
-        return data that can be ploted with plotly
+        return data that can be plotted with plotly
     - 'vis_*' functions (e.g., 'vis_camera_rays')
         return 'go.Figure' objects which are the plots. Go Figure! :')
 """
diff --git a/nerfstudio/viewer/app/src/index.scss b/nerfstudio/viewer/app/src/index.scss
index 3a63228b6..ed7196b2a 100644
--- a/nerfstudio/viewer/app/src/index.scss
+++ b/nerfstudio/viewer/app/src/index.scss
@@ -200,7 +200,7 @@ $sidebar-width: 100% !default;
 // ------------------------------------
 // Viewport Controls Modal styling
 
-.ViewportConstrolsModal-box {
+.ViewportControlsModal-box {
   position: absolute;
   top: 50%;
   left: 50%;
diff --git a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
index 1ea1595cd..9ef5ae60f 100644
--- a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
+++ b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
@@ -737,7 +737,7 @@ export default function CameraPanel(props) {
   transform_controls.addEventListener('mouseDown', (event) => {
     // prevent multiple loops
     if (update_cameras_interval === null) {
-      // hardcoded for 100 ms per udpate
+      // hardcoded for 100 ms per update
       update_cameras_interval = setInterval(() => {}, 100);
     }
   });
diff --git a/nerfstudio/viewer/app/src/modules/ViewportControlsModal/ViewportControlsModal.jsx b/nerfstudio/viewer/app/src/modules/ViewportControlsModal/ViewportControlsModal.jsx
index 7a6d10380..192bc262b 100644
--- a/nerfstudio/viewer/app/src/modules/ViewportControlsModal/ViewportControlsModal.jsx
+++ b/nerfstudio/viewer/app/src/modules/ViewportControlsModal/ViewportControlsModal.jsx
@@ -26,7 +26,7 @@ export default function ControlsModal() {
         aria-labelledby="modal-modal-title"
         aria-describedby="modal-modal-description"
       >
-        <Box className="ViewportConstrolsModal-box">
+        <Box className="ViewportControlsModal-box">
           <center>
             <img
               style={{ height: 37, margin: 'auto' }}
diff --git a/nerfstudio/viewer/server/gui_utils.py b/nerfstudio/viewer/server/gui_utils.py
index 42b3edf52..901425c5d 100644
--- a/nerfstudio/viewer/server/gui_utils.py
+++ b/nerfstudio/viewer/server/gui_utils.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-""" Utilites for generating custom gui elements in the viewer """
+""" Utilities for generating custom gui elements in the viewer """
 
 from __future__ import annotations
 
diff --git a/nerfstudio/viewer/server/render_state_machine.py b/nerfstudio/viewer/server/render_state_machine.py
index 1ad691b28..540a8378b 100644
--- a/nerfstudio/viewer/server/render_state_machine.py
+++ b/nerfstudio/viewer/server/render_state_machine.py
@@ -98,7 +98,7 @@ class RenderStateMachine(threading.Thread):
             # never overwrite rerenders
             pass
         else:
-            #  monimal use case, just set the next action
+            #  minimal use case, just set the next action
             self.next_action = action
 
         # handle interrupt logic
@@ -107,7 +107,7 @@ class RenderStateMachine(threading.Thread):
         self.render_trigger.set()
 
     def _render_img(self, cam_msg: CameraMessage):
-        """Takes the current camera, generates rays, and renders the iamge
+        """Takes the current camera, generates rays, and renders the image
 
         Args:
             cam_msg: the camera message to render
@@ -238,7 +238,7 @@ class RenderStateMachine(threading.Thread):
         """Calculate the maximum image height that can be rendered in the time budget
 
         Args:
-            apect_ratio: the aspect ratio of the current view
+            aspect_ratio: the aspect ratio of the current view
         Returns:
             image_height: the maximum image height that can be rendered in the time budget
             image_width: the maximum image width that can be rendered in the time budget
diff --git a/nerfstudio/viewer/server/viewer_state.py b/nerfstudio/viewer/server/viewer_state.py
index 838d26034..0e948d2cc 100644
--- a/nerfstudio/viewer/server/viewer_state.py
+++ b/nerfstudio/viewer/server/viewer_state.py
@@ -332,7 +332,7 @@ class ViewerState:
         return camera
 
     def _pick_drawn_image_idxs(self, total_num: int) -> list[int]:
-        """Determine indicies of images to display in viewer.
+        """Determine indices of images to display in viewer.
 
         Args:
             total_num: total number of training images.
diff --git a/nerfstudio/viewer/viser/__init__.py b/nerfstudio/viewer/viser/__init__.py
index 915465d94..683b145c3 100644
--- a/nerfstudio/viewer/viser/__init__.py
+++ b/nerfstudio/viewer/viser/__init__.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-""" Viser is used for the nerfstudio viewr backend """
+""" Viser is used for the nerfstudio viewer backend """
 
 
 from .message_api import GuiHandle as GuiHandle
diff --git a/nerfstudio/viewer/viser/message_api.py b/nerfstudio/viewer/viser/message_api.py
index ec602e4df..3c8ce752c 100644
--- a/nerfstudio/viewer/viser/message_api.py
+++ b/nerfstudio/viewer/viser/message_api.py
@@ -124,7 +124,7 @@ class MessageApi(abc.ABC):
     """Interface for all commands we can use to send messages over a websocket connection.
 
     Should be implemented by both our global server object (for broadcasting) and by
-    invidividual clients."""
+    individual clients."""
 
     def __init__(self) -> None:
         self._handle_state_from_gui_name: Dict[str, _GuiHandleState[Any]] = {}
diff --git a/nerfstudio/viewer/viser/messages.py b/nerfstudio/viewer/viser/messages.py
index 2ce9de61d..4a9aab999 100644
--- a/nerfstudio/viewer/viser/messages.py
+++ b/nerfstudio/viewer/viser/messages.py
@@ -186,10 +186,10 @@ class DatasetImageMessage(NerfstudioMessage):
 
 @dataclasses.dataclass
 class TrainingStateMessage(NerfstudioMessage):
-    """Wheather the scene is in training mode or not."""
+    """Whether the scene is in training mode or not."""
 
     training_state: Literal["training", "paused", "completed"]
-    """True if the model is currently trianing, False otherwise"""
+    """True if the model is currently training, False otherwise"""
 
 
 @dataclasses.dataclass
diff --git a/tests/model_components/test_losses.py b/tests/model_components/test_losses.py
index 8dbbbc443..17ffdaf0b 100644
--- a/tests/model_components/test_losses.py
+++ b/tests/model_components/test_losses.py
@@ -20,7 +20,7 @@ def test_tv_loss():
             for k in range(10):
                 grids[0, k, i, j] = grid_location
 
-    # TV_row = 1, TV_col = 1. Totol tv should be 2 * (TV_row + TV_col)
+    # TV_row = 1, TV_col = 1. Total tv should be 2 * (TV_row + TV_col)
     assert tv_loss(grids).item() == 4.0
 
 
diff --git a/tests/process_data/test_process_images.py b/tests/process_data/test_process_images.py
index 4911d7edd..f143f2b1f 100644
--- a/tests/process_data/test_process_images.py
+++ b/tests/process_data/test_process_images.py
@@ -23,7 +23,7 @@ from nerfstudio.process_data.images_to_nerfstudio_dataset import (
 
 def random_quaternion(num_poses: int):
     """
-    Generates random rotation quatenion.
+    Generates random rotation quaternion.
     """
     u, v, w = np.random.uniform(size=(3, num_poses))
     quaternion = np.stack(
diff --git a/tests/utils/test_aabb_intersection.py b/tests/utils/test_aabb_intersection.py
index ab8e2ce0e..625ae6edb 100644
--- a/tests/utils/test_aabb_intersection.py
+++ b/tests/utils/test_aabb_intersection.py
@@ -48,7 +48,7 @@ def _get_random_aabb_box(max_box, device):
 
 def _get_random_rays(num_rays, max_box, aabb, device):
     """
-    genrate random rays that distribute in the general direction of the box.
+    generate random rays that distribute in the general direction of the box.
     The implementation is naive for now.
     :param num_rays:
     :param max_box: