From 2a62d8a14e08242987339f8eab0a73ae45760190 Mon Sep 17 00:00:00 2001
From: Ethan Weber <ethanweber@berkeley.edu>
Date: Mon, 5 Dec 2022 15:37:49 -0800
Subject: [PATCH 01/24] Update mipnerf defaults (#1092)

update mipnerf defaults
---
 nerfstudio/configs/method_configs.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nerfstudio/configs/method_configs.py b/nerfstudio/configs/method_configs.py
index f666b5ed1..6fb532e14 100644
--- a/nerfstudio/configs/method_configs.py
+++ b/nerfstudio/configs/method_configs.py
@@ -116,13 +116,13 @@ method_configs["instant-ngp"] = Config(
 method_configs["mipnerf"] = Config(
     method_name="mipnerf",
     pipeline=VanillaPipelineConfig(
-        datamanager=VanillaDataManagerConfig(dataparser=BlenderDataParserConfig(), train_num_rays_per_batch=8192),
+        datamanager=VanillaDataManagerConfig(dataparser=NerfstudioDataParserConfig(), train_num_rays_per_batch=1024),
         model=VanillaModelConfig(
             _target=MipNerfModel,
             loss_coefficients={"rgb_loss_coarse": 0.1, "rgb_loss_fine": 1.0},
             num_coarse_samples=128,
             num_importance_samples=128,
-            eval_num_rays_per_chunk=8192,
+            eval_num_rays_per_chunk=1024,
         ),
     ),
     optimizers={

From f3442c8b7b21218364000ef88c17a86afd7d0700 Mon Sep 17 00:00:00 2001
From: machenmusik <machenmusik@users.noreply.github.com>
Date: Mon, 5 Dec 2022 19:03:09 -0500
Subject: [PATCH 02/24] Use max resolution when not moving or training (#1091)

use max resolution when not moving or training
---
 nerfstudio/viewer/server/viewer_utils.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/nerfstudio/viewer/server/viewer_utils.py b/nerfstudio/viewer/server/viewer_utils.py
index 05be19ea0..ce70426f6 100644
--- a/nerfstudio/viewer/server/viewer_utils.py
+++ b/nerfstudio/viewer/server/viewer_utils.py
@@ -672,9 +672,12 @@ class ViewerState:
 
         aspect_ratio = camera_object["aspect"]
 
-        image_height = (num_vis_rays / aspect_ratio) ** 0.5
-        image_height = int(round(image_height, -1))
-        image_height = min(self.max_resolution, image_height)
+        if not self.camera_moving and not is_training:
+            image_height = self.max_resolution
+        else:
+            image_height = (num_vis_rays / aspect_ratio) ** 0.5
+            image_height = int(round(image_height, -1))
+            image_height = min(self.max_resolution, image_height)
         image_width = int(image_height * aspect_ratio)
         if image_width > self.max_resolution:
             image_width = self.max_resolution

From 6896028fc503b00947d04b7ed142a8dbd685749d Mon Sep 17 00:00:00 2001
From: Nicolas Zunhammer <smashdroid@gmail.com>
Date: Tue, 6 Dec 2022 02:04:40 +0100
Subject: [PATCH 03/24] Fix mask filenames misaligned after splitting set into
 train and eval (#1093)

* Added Dockerfile to build docker image including all dependencies and nerfstudio, added description on how to user docker.

* Move docker description to Installation.md.

* Fix mask_filename indices after splitting train set.

Co-authored-by: Nicolas Zunhammer <n.zunhammer@tum.de>
---
 nerfstudio/data/dataparsers/nerfstudio_dataparser.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
index e2b86bd6d..6dd41738b 100644
--- a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
+++ b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
@@ -196,6 +196,7 @@ class Nerfstudio(DataParser):
 
         # Choose image_filenames and poses based on split, but after auto orient and scaling the poses.
         image_filenames = [image_filenames[i] for i in indices]
+        mask_filenames = [mask_filenames[i] for i in indices]
         poses = poses[indices]
 
         # in x,y,z order

From 006703bb64b729ffedd3c991dcf612e31c3fcb3d Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Mon, 5 Dec 2022 17:35:12 -0800
Subject: [PATCH 04/24] Fix crash on camera delete (#1094)

---
 .../app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx  | 7 ++++++-
 nerfstudio/viewer/server/utils.py                          | 3 +++
 2 files changed, 9 insertions(+), 1 deletion(-)

diff --git a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
index b71266d4a..6a741d156 100644
--- a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
+++ b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
@@ -612,6 +612,11 @@ export default function CameraPanel(props) {
 
     sceneTree.delete(['Camera Path', 'Cameras']); // delete old cameras, which is important
     if (cameras.length < 1) {
+      dispatch({
+        type: 'write',
+        path: 'renderingState/camera_choice',
+        data: 'Main Camera',
+      });
       camera_render_helper.set_visibility(false);
     } else {
       camera_render_helper.set_visibility(true);
@@ -625,7 +630,7 @@ export default function CameraPanel(props) {
       labelDiv.className = 'label';
       labelDiv.textContent = camera.properties.get('NAME');
       labelDiv.style.color = 'black';
-      labelDiv.style.backgroundColor = "rgba(255, 255, 255, 0.61)";
+      labelDiv.style.backgroundColor = 'rgba(255, 255, 255, 0.61)';
       labelDiv.style.backdropFilter = 'blur(5px)';
       labelDiv.style.padding = '6px';
       labelDiv.style.borderRadius = '6px';
diff --git a/nerfstudio/viewer/server/utils.py b/nerfstudio/viewer/server/utils.py
index 92ccc0ef7..6d13f9378 100644
--- a/nerfstudio/viewer/server/utils.py
+++ b/nerfstudio/viewer/server/utils.py
@@ -54,6 +54,9 @@ def three_js_perspective_camera_focal_length(fov: float, image_height: int):
         fov: the field of view of the camera in degrees.
         image_height: the height of the image in pixels.
     """
+    if fov is None:
+        print("Warning: fov is None, using default value")
+        return 50
     pp_h = image_height / 2.0
     focal_length = pp_h / np.tan(fov * (np.pi / 180.0) / 2.0)
     return focal_length

From e605b3344ac623fd96e2458ef98f8fbc7a97d718 Mon Sep 17 00:00:00 2001
From: ksnzh <ksnzher@gmail.com>
Date: Tue, 6 Dec 2022 14:10:55 +0800
Subject: [PATCH 05/24] Fix IndexError if ther is no mask filenames (#1095)

---
 nerfstudio/data/dataparsers/nerfstudio_dataparser.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
index 6dd41738b..347a292a5 100644
--- a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
+++ b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
@@ -196,7 +196,7 @@ class Nerfstudio(DataParser):
 
         # Choose image_filenames and poses based on split, but after auto orient and scaling the poses.
         image_filenames = [image_filenames[i] for i in indices]
-        mask_filenames = [mask_filenames[i] for i in indices]
+        mask_filenames = [mask_filenames[i] for i in indices] if len(mask_filenames) > 0 else []
         poses = poses[indices]
 
         # in x,y,z order

From 90447ab2236946f2e22477b53001f17af1392d9e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fran=C3=A7ois=20Darmon?= <fra.darmon@gmail.com>
Date: Wed, 7 Dec 2022 18:40:53 +0100
Subject: [PATCH 06/24] Bug correction auto_orient_and_center_poses (#1098)

When using auto_orient_and_center_poses with method="none" the returned pose if 4x4 (contrary to up and pca) which triggers an assertion error later. This modification solves it.
---
 nerfstudio/cameras/camera_utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nerfstudio/cameras/camera_utils.py b/nerfstudio/cameras/camera_utils.py
index 30d755596..97599d239 100644
--- a/nerfstudio/cameras/camera_utils.py
+++ b/nerfstudio/cameras/camera_utils.py
@@ -457,7 +457,7 @@ def auto_orient_and_center_poses(
         transform = torch.cat([rotation, rotation @ -translation[..., None]], dim=-1)
         oriented_poses = transform @ poses
     elif method == "none":
-        oriented_poses = poses
-        poses[:, :3, 3] -= translation
+        oriented_poses = poses[:, :3]
+        oriented_poses[..., 3] -= translation
 
     return oriented_poses

From b41ce8060ac38113ea0d940e3f17f3cecb0f43e2 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Sun, 11 Dec 2022 13:02:50 -0800
Subject: [PATCH 07/24] Save out dataparser transforms (#1105)

* Save out dataparser transforms

* Make missing folder
---
 nerfstudio/cameras/camera_utils.py            |  12 +-
 .../data/datamanagers/base_datamanager.py     |   7 +-
 .../data/dataparsers/base_dataparser.py       |  21 +++
 .../data/dataparsers/blender_dataparser.py    |   1 +
 .../data/dataparsers/dnerf_dataparser.py      |   6 +-
 .../data/dataparsers/friends_dataparser.py    |   1 +
 .../dataparsers/instant_ngp_dataparser.py     |   1 +
 .../data/dataparsers/nerfstudio_dataparser.py |   9 +-
 .../dataparsers/phototourism_dataparser.py    |   9 +-
 .../data/dataparsers/record3d_dataparser.py   | 160 ------------------
 nerfstudio/engine/trainer.py                  |   4 +
 11 files changed, 56 insertions(+), 175 deletions(-)
 delete mode 100644 nerfstudio/data/dataparsers/record3d_dataparser.py

diff --git a/nerfstudio/cameras/camera_utils.py b/nerfstudio/cameras/camera_utils.py
index 97599d239..d3b0ca619 100644
--- a/nerfstudio/cameras/camera_utils.py
+++ b/nerfstudio/cameras/camera_utils.py
@@ -409,7 +409,7 @@ def rotation_matrix(a: TensorType[3], b: TensorType[3]) -> TensorType[3, 3]:
 
 def auto_orient_and_center_poses(
     poses: TensorType["num_poses":..., 4, 4], method: Literal["pca", "up", "none"] = "up", center_poses: bool = True
-) -> TensorType["num_poses":..., 3, 4]:
+) -> Tuple[TensorType["num_poses":..., 3, 4], TensorType[4, 4]]:
     """Orients and centers the poses. We provide two methods for orientation: pca and up.
 
     pca: Orient the poses so that the principal component of the points is aligned with the axes.
@@ -424,7 +424,7 @@ def auto_orient_and_center_poses(
         center_poses: If True, the poses are centered around the origin.
 
     Returns:
-        The oriented poses.
+        Tuple of the oriented poses and the transform matrix.
     """
 
     translation = poses[..., :3, 3]
@@ -457,7 +457,9 @@ def auto_orient_and_center_poses(
         transform = torch.cat([rotation, rotation @ -translation[..., None]], dim=-1)
         oriented_poses = transform @ poses
     elif method == "none":
-        oriented_poses = poses[:, :3]
-        oriented_poses[..., 3] -= translation
+        transform = torch.eye(4)
+        transform[:3, 3] = -translation
+        transform = transform[:3, :]
+        oriented_poses = transform @ poses
 
-    return oriented_poses
+    return oriented_poses, transform
diff --git a/nerfstudio/data/datamanagers/base_datamanager.py b/nerfstudio/data/datamanagers/base_datamanager.py
index 7adf8cd05..7f1282c87 100644
--- a/nerfstudio/data/datamanagers/base_datamanager.py
+++ b/nerfstudio/data/datamanagers/base_datamanager.py
@@ -35,6 +35,7 @@ from nerfstudio.cameras.camera_optimizers import CameraOptimizerConfig
 from nerfstudio.cameras.cameras import CameraType
 from nerfstudio.cameras.rays import RayBundle
 from nerfstudio.configs.base_config import InstantiateConfig
+from nerfstudio.data.dataparsers.base_dataparser import DataparserOutputs
 from nerfstudio.data.dataparsers.blender_dataparser import BlenderDataParserConfig
 from nerfstudio.data.dataparsers.dnerf_dataparser import DNeRFDataParserConfig
 from nerfstudio.data.dataparsers.friends_dataparser import FriendsDataParserConfig
@@ -46,7 +47,6 @@ from nerfstudio.data.dataparsers.nuscenes_dataparser import NuScenesDataParserCo
 from nerfstudio.data.dataparsers.phototourism_dataparser import (
     PhototourismDataParserConfig,
 )
-from nerfstudio.data.dataparsers.record3d_dataparser import Record3DDataParserConfig
 from nerfstudio.data.datasets.base_dataset import InputDataset
 from nerfstudio.data.pixel_samplers import EquirectangularPixelSampler, PixelSampler
 from nerfstudio.data.utils.dataloaders import (
@@ -69,7 +69,6 @@ AnnotatedDataParserUnion = tyro.conf.OmitSubcommandPrefixes[  # Omit prefixes of
             "friends-data": FriendsDataParserConfig(),
             "instant-ngp-data": InstantNGPDataParserConfig(),
             "nuscenes-data": NuScenesDataParserConfig(),
-            "record3d-data": Record3DDataParserConfig(),
             "dnerf-data": DNeRFDataParserConfig(),
             "phototourism-data": PhototourismDataParserConfig(),
         },
@@ -296,6 +295,7 @@ class VanillaDataManager(DataManager):  # pylint: disable=abstract-method
     config: VanillaDataManagerConfig
     train_dataset: InputDataset
     eval_dataset: InputDataset
+    train_dataparser_outputs: DataparserOutputs
 
     def __init__(
         self,
@@ -321,8 +321,9 @@ class VanillaDataManager(DataManager):  # pylint: disable=abstract-method
 
     def create_train_dataset(self) -> InputDataset:
         """Sets up the data loaders for training"""
+        self.train_dataparser_outputs = self.dataparser.get_dataparser_outputs(split="train")
         return InputDataset(
-            dataparser_outputs=self.dataparser.get_dataparser_outputs(split="train"),
+            dataparser_outputs=self.train_dataparser_outputs,
             scale_factor=self.config.camera_res_scale_factor,
         )
 
diff --git a/nerfstudio/data/dataparsers/base_dataparser.py b/nerfstudio/data/dataparsers/base_dataparser.py
index 3b99f274e..0caf24cea 100644
--- a/nerfstudio/data/dataparsers/base_dataparser.py
+++ b/nerfstudio/data/dataparsers/base_dataparser.py
@@ -16,6 +16,7 @@
 
 from __future__ import annotations
 
+import json
 from abc import abstractmethod
 from dataclasses import dataclass, field
 from pathlib import Path
@@ -63,11 +64,31 @@ class DataparserOutputs:
     """Dictionary of any metadata that be required for the given experiment.
     Will be processed by the InputDataset to create any additional tensors that may be required.
     """
+    dataparser_transform: TensorType[3, 4] = torch.eye(4)[:3, :]
+    """Transform applied by the dataparser."""
+    dataparser_scale: float = 1.0
+    """Scale applied by the dataparser."""
 
     def as_dict(self) -> dict:
         """Returns the dataclass as a dictionary."""
         return vars(self)
 
+    def save_dataparser_transform(self, path: Path):
+        """Save dataparser transform to json file. Some dataparsers will apply a transform to the poses,
+        this method allows the transform to be saved so that it can be used in other applications.
+
+        Args:
+            path: path to save transform to
+        """
+        data = {
+            "transform": self.dataparser_transform.tolist(),
+            "scale": self.dataparser_scale,
+        }
+        if not path.parent.exists():
+            path.parent.mkdir(parents=True)
+        with open(path, "w", encoding="UTF-8") as file:
+            json.dump(data, file, indent=4)
+
 
 @dataclass
 class DataParserConfig(cfg.InstantiateConfig):
diff --git a/nerfstudio/data/dataparsers/blender_dataparser.py b/nerfstudio/data/dataparsers/blender_dataparser.py
index 0f31acff1..f1044e826 100644
--- a/nerfstudio/data/dataparsers/blender_dataparser.py
+++ b/nerfstudio/data/dataparsers/blender_dataparser.py
@@ -104,6 +104,7 @@ class Blender(DataParser):
             cameras=cameras,
             alpha_color=alpha_color_tensor,
             scene_box=scene_box,
+            dataparser_scale=self.scale_factor,
         )
 
         return dataparser_outputs
diff --git a/nerfstudio/data/dataparsers/dnerf_dataparser.py b/nerfstudio/data/dataparsers/dnerf_dataparser.py
index 56a9f232b..c26621e92 100644
--- a/nerfstudio/data/dataparsers/dnerf_dataparser.py
+++ b/nerfstudio/data/dataparsers/dnerf_dataparser.py
@@ -102,7 +102,11 @@ class DNeRF(DataParser):
         )
 
         dataparser_outputs = DataparserOutputs(
-            image_filenames=image_filenames, cameras=cameras, alpha_color=alpha_color_tensor, scene_box=scene_box
+            image_filenames=image_filenames,
+            cameras=cameras,
+            alpha_color=alpha_color_tensor,
+            scene_box=scene_box,
+            dataparser_scale=self.scale_factor,
         )
 
         return dataparser_outputs
diff --git a/nerfstudio/data/dataparsers/friends_dataparser.py b/nerfstudio/data/dataparsers/friends_dataparser.py
index 06fceef3c..604dbd7c0 100644
--- a/nerfstudio/data/dataparsers/friends_dataparser.py
+++ b/nerfstudio/data/dataparsers/friends_dataparser.py
@@ -146,5 +146,6 @@ class Friends(DataParser):
             cameras=cameras,
             scene_box=scene_box,
             metadata={"semantics": semantics} if self.config.include_semantics else {},
+            dataparser_scale=scale,
         )
         return dataparser_outputs
diff --git a/nerfstudio/data/dataparsers/instant_ngp_dataparser.py b/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
index 1e5a69b99..289e23d55 100644
--- a/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
+++ b/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
@@ -115,6 +115,7 @@ class InstantNGP(DataParser):
             image_filenames=image_filenames,
             cameras=cameras,
             scene_box=scene_box,
+            dataparser_scale=self.config.scene_scale,
         )
 
         return dataparser_outputs
diff --git a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
index 347a292a5..d2c8c2d2e 100644
--- a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
+++ b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
@@ -181,7 +181,7 @@ class Nerfstudio(DataParser):
             orientation_method = self.config.orientation_method
 
         poses = torch.from_numpy(np.array(poses).astype(np.float32))
-        poses = camera_utils.auto_orient_and_center_poses(
+        poses, transform_matrix = camera_utils.auto_orient_and_center_poses(
             poses,
             method=orientation_method,
             center_poses=self.config.center_poses,
@@ -190,9 +190,10 @@ class Nerfstudio(DataParser):
         # Scale poses
         scale_factor = 1.0
         if self.config.auto_scale_poses:
-            scale_factor /= torch.max(torch.abs(poses[:, :3, 3]))
+            scale_factor /= float(torch.max(torch.abs(poses[:, :3, 3])))
+        scale_factor *= self.config.scale_factor
 
-        poses[:, :3, 3] *= scale_factor * self.config.scale_factor
+        poses[:, :3, 3] *= scale_factor
 
         # Choose image_filenames and poses based on split, but after auto orient and scaling the poses.
         image_filenames = [image_filenames[i] for i in indices]
@@ -252,6 +253,8 @@ class Nerfstudio(DataParser):
             cameras=cameras,
             scene_box=scene_box,
             mask_filenames=mask_filenames if len(mask_filenames) > 0 else None,
+            dataparser_scale=scale_factor,
+            dataparser_transform=transform_matrix,
         )
         return dataparser_outputs
 
diff --git a/nerfstudio/data/dataparsers/phototourism_dataparser.py b/nerfstudio/data/dataparsers/phototourism_dataparser.py
index f0f6987e0..bb401d9dc 100644
--- a/nerfstudio/data/dataparsers/phototourism_dataparser.py
+++ b/nerfstudio/data/dataparsers/phototourism_dataparser.py
@@ -137,16 +137,17 @@ class Phototourism(DataParser):
         else:
             raise ValueError(f"Unknown dataparser split {split}")
 
-        poses = camera_utils.auto_orient_and_center_poses(
+        poses, transform_matrix = camera_utils.auto_orient_and_center_poses(
             poses, method=self.config.orientation_method, center_poses=self.config.center_poses
         )
 
         # Scale poses
         scale_factor = 1.0
         if self.config.auto_scale_poses:
-            scale_factor /= torch.max(torch.abs(poses[:, :3, 3]))
+            scale_factor /= float(torch.max(torch.abs(poses[:, :3, 3])))
+        scale_factor *= self.config.scale_factor
 
-        poses[:, :3, 3] *= scale_factor * self.config.scale_factor
+        poses[:, :3, 3] *= scale_factor
 
         # in x,y,z order
         # assumes that the scene is centered at the origin
@@ -175,6 +176,8 @@ class Phototourism(DataParser):
             image_filenames=image_filenames,
             cameras=cameras,
             scene_box=scene_box,
+            dataparser_scale=scale_factor,
+            dataparser_transform=transform_matrix,
         )
 
         return dataparser_outputs
diff --git a/nerfstudio/data/dataparsers/record3d_dataparser.py b/nerfstudio/data/dataparsers/record3d_dataparser.py
deleted file mode 100644
index 099470d01..000000000
--- a/nerfstudio/data/dataparsers/record3d_dataparser.py
+++ /dev/null
@@ -1,160 +0,0 @@
-# Copyright 2022 The Nerfstudio Team. All rights reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Data parser for record3d dataset"""
-from __future__ import annotations
-
-from dataclasses import dataclass, field
-from pathlib import Path
-from typing import Type
-
-import numpy as np
-import torch
-from rich.console import Console
-from scipy.spatial.transform import Rotation
-from typing_extensions import Literal
-
-from nerfstudio.cameras import camera_utils
-from nerfstudio.cameras.cameras import Cameras, CameraType
-from nerfstudio.data.dataparsers.base_dataparser import (
-    DataParser,
-    DataParserConfig,
-    DataparserOutputs,
-)
-from nerfstudio.data.scene_box import SceneBox
-from nerfstudio.utils import poses as pose_utils
-from nerfstudio.utils.io import load_from_json
-
-CONSOLE = Console(width=120)
-
-
-@dataclass
-class Record3DDataParserConfig(DataParserConfig):
-    """Record3D dataset config"""
-
-    _target: Type = field(default_factory=lambda: Record3D)
-    """target class to instantiate"""
-    data: Path = Path("data/record3d/bear")
-    """Location of data"""
-    val_skip: int = 8
-    """1/val_skip images to use for validation."""
-    aabb_scale: float = 4.0
-    """Scene scale."""
-    orientation_method: Literal["pca", "up"] = "up"
-    """The method to use for orientation"""
-    max_dataset_size: int = 300
-    """Max number of images to train on. If the dataset has more, images will be sampled approximately evenly. If -1,
-    use all images."""
-
-
-@dataclass
-class Record3D(DataParser):
-    """Record3D Dataset"""
-
-    config: Record3DDataParserConfig
-
-    def _generate_dataparser_outputs(self, split: str = "train") -> DataparserOutputs:
-
-        CONSOLE.print(
-            "[bold red]DEPRECATION WARNING: The Record3D dataparser will be deprecated in future versions. "
-            "Use `ns-data-process record3d` to convert the data into the nerfstudio format instead."
-        )
-
-        image_dir = self.config.data / "rgb"
-
-        if not image_dir.exists():
-            raise ValueError(f"Image directory {image_dir} doesn't exist")
-
-        image_filenames = []
-        for f in image_dir.iterdir():
-            if f.stem.isdigit():  # removes possible duplicate images (for example, 123(3).jpg)
-                image_filenames.append(f)
-
-        image_filenames = sorted(image_filenames, key=lambda fn: int(fn.stem))
-        image_filenames = np.array(image_filenames)
-        num_images = len(image_filenames)
-
-        metadata_path = self.config.data / "metadata.json"
-        metadata_dict = load_from_json(metadata_path)
-
-        poses_data = np.array(metadata_dict["poses"])
-        # (N, 3, 4)
-        poses = np.concatenate(
-            [Rotation.from_quat(poses_data[:, :4]).as_matrix(), poses_data[:, 4:, None]],
-            axis=-1,
-        ).astype(np.float32)
-
-        if self.config.max_dataset_size != -1 and num_images > self.config.max_dataset_size:
-            # Evenly select max_dataset_size images from dataset, including first
-            # and last indices.
-            idx = np.round(np.linspace(0, num_images - 1, self.config.max_dataset_size)).astype(int)
-            poses = poses[idx]
-            image_filenames = image_filenames[idx]
-            num_images = len(image_filenames)
-
-        idx_test = np.arange(num_images)[:: self.config.val_skip]
-        idx_train = np.array([i for i in np.arange(num_images) if i not in idx_test])
-        idx = idx_train if split == "train" else idx_test
-        if num_images != poses.shape[0]:
-            raise RuntimeError(f"Different number of images ({num_images}), and poses ({poses.shape[0]})")
-
-        image_filenames = image_filenames[idx]
-        poses = poses[idx]
-
-        # convert to Tensors
-        poses = torch.from_numpy(poses[:, :3, :4])
-
-        poses = camera_utils.auto_orient_and_center_poses(
-            pose_utils.to4x4(poses), method=self.config.orientation_method
-        )[:, :3, :4]
-
-        # Centering poses
-        poses[:, :3, 3] = poses[:, :3, 3] - torch.mean(poses[:, :3, 3], dim=0)
-        poses = pose_utils.normalize(poses)
-
-        # Camera intrinsics
-        K = np.array(metadata_dict["K"]).reshape((3, 3)).T
-        focal_length = K[0, 0]
-
-        H = metadata_dict["h"]
-        W = metadata_dict["w"]
-
-        # TODO(akristoffersen): The metadata dict comes with principle points,
-        # but caused errors in image coord indexing. Should update once that is fixed.
-        cx, cy = W / 2, H / 2
-
-        num_cameras = len(image_filenames)
-        num_intrinsics_params = 3
-        intrinsics = torch.ones((num_cameras, num_intrinsics_params), dtype=torch.float32)
-        intrinsics *= torch.tensor([cx, cy, focal_length])
-
-        aabb = torch.tensor([[-1, -1, -1], [1, 1, 1]], dtype=torch.float32) * self.config.aabb_scale
-        scene_box = SceneBox(aabb=aabb)
-
-        cameras = Cameras(
-            fx=focal_length,
-            fy=focal_length,
-            cx=cx,
-            cy=cy,
-            camera_to_worlds=poses,
-            camera_type=CameraType.PERSPECTIVE,
-        )
-
-        dataparser_outputs = DataparserOutputs(
-            image_filenames=image_filenames,
-            cameras=cameras,
-            scene_box=scene_box,
-        )
-
-        return dataparser_outputs
diff --git a/nerfstudio/engine/trainer.py b/nerfstudio/engine/trainer.py
index ae9da1ec2..445788fbf 100644
--- a/nerfstudio/engine/trainer.py
+++ b/nerfstudio/engine/trainer.py
@@ -132,6 +132,10 @@ class Trainer:
         """Train the model."""
         assert self.pipeline.datamanager.train_dataset is not None, "Missing DatsetInputs"
 
+        self.pipeline.datamanager.train_dataparser_outputs.save_dataparser_transform(
+            self.base_dir / "dataparser_transforms.json"
+        )
+
         self._init_viewer_state()
         with TimeWriter(writer, EventName.TOTAL_TRAIN_TIME):
             num_iterations = self.config.trainer.max_num_iterations

From 676f816156d05b581562774410381e811e9d69c1 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Sun, 11 Dec 2022 13:03:35 -0800
Subject: [PATCH 08/24] Bump max res default (#1106)

---
 nerfstudio/fields/nerfacto_field.py | 2 +-
 nerfstudio/models/nerfacto.py       | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/nerfstudio/fields/nerfacto_field.py b/nerfstudio/fields/nerfacto_field.py
index da51f417a..95ed66c1e 100644
--- a/nerfstudio/fields/nerfacto_field.py
+++ b/nerfstudio/fields/nerfacto_field.py
@@ -91,7 +91,7 @@ class TCNNNerfactoField(Field):
         hidden_dim: int = 64,
         geo_feat_dim: int = 15,
         num_levels: int = 16,
-        max_res: int = 1024,
+        max_res: int = 2048,
         log2_hashmap_size: int = 19,
         num_layers_color: int = 3,
         num_layers_transient: int = 2,
diff --git a/nerfstudio/models/nerfacto.py b/nerfstudio/models/nerfacto.py
index b1e772b03..11adadbd7 100644
--- a/nerfstudio/models/nerfacto.py
+++ b/nerfstudio/models/nerfacto.py
@@ -71,7 +71,7 @@ class NerfactoModelConfig(ModelConfig):
     """Whether to randomize the background color."""
     num_levels: int = 16
     """Number of levels of the hashmap for the base mlp."""
-    max_res: int = 1024
+    max_res: int = 2048
     """Maximum resolution of the hashmap for the base mlp."""
     log2_hashmap_size: int = 19
     """Size of the hashmap for the base mlp"""

From 910e7bfb0558767670920c80aa9b705173a81f0d Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Sun, 11 Dec 2022 13:05:03 -0800
Subject: [PATCH 09/24] v0.1.13 (#1107)

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 064ff1cf8..fe908f8c6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "nerfstudio"
-version = "0.1.12"
+version = "0.1.13"
 description = "All-in-one repository for state-of-the-art NeRFs"
 readme = "README.md"
 license = { text="Apache 2.0"}

From 986f3a565d601b977a881bd2da22594259043de4 Mon Sep 17 00:00:00 2001
From: Alexander Kristoffersen <akristoffersen@berkeley.edu>
Date: Mon, 12 Dec 2022 11:47:09 -0800
Subject: [PATCH 10/24] Colab working with Python3.8 (#1109)

changed away from the wheel, couldn't get it to work
---
 colab/demo.ipynb | 24 ++++++++++++------------
 1 file changed, 12 insertions(+), 12 deletions(-)

diff --git a/colab/demo.ipynb b/colab/demo.ipynb
index c47045b48..9609a6db4 100644
--- a/colab/demo.ipynb
+++ b/colab/demo.ipynb
@@ -3,11 +3,11 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "colab_type": "text",
-        "id": "view-in-github"
+        "id": "view-in-github",
+        "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://colab.research.google.com/github/nerfstudio-project/nerfstudio/blob/tancik%2Fpolycam/colab/demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+        "<a href=\"https://colab.research.google.com/github/nerfstudio-project/nerfstudio/blob/alex%2Fcolab_38/colab/demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -63,7 +63,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 1,
+      "execution_count": null,
       "metadata": {
         "cellView": "form",
         "colab": {
@@ -103,7 +103,7 @@
       },
       "outputs": [],
       "source": [
-        "#@markdown <h1>Install Nerfstudio and Dependencies (~10 min)</h1>\n",
+        "#@markdown <h1>Install Nerfstudio and Dependencies (~15 min)</h1>\n",
         "\n",
         "%cd /content/\n",
         "!pip install --upgrade pip\n",
@@ -111,8 +111,9 @@
         "\n",
         "# Installing TinyCuda\n",
         "%cd /content/\n",
-        "!gdown \"https://drive.google.com/u/1/uc?id=1q8fuc-Mqiev5GTBTRA5UPgCaQDzuqKqj\" \n",
-        "!pip install tinycudann-1.6-cp37-cp37m-linux_x86_64.whl\n",
+        "# !gdown \"https://drive.google.com/u/1/uc?id=1wglEFPbI4BjWMFYaKk7gHCNsWCZphKjs\" \n",
+        "# !pip install tinycudann-1.6-cp38-cp38-linux_x86_64.whl\n",
+        "!pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch\n",
         "\n",
         "# Installing COLMAP\n",
         "%cd /content/\n",
@@ -202,7 +203,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 2,
+      "execution_count": null,
       "metadata": {
         "cellView": "form",
         "colab": {
@@ -362,9 +363,8 @@
   "metadata": {
     "accelerator": "GPU",
     "colab": {
-      "collapsed_sections": [],
-      "include_colab_link": true,
-      "provenance": []
+      "provenance": [],
+      "include_colab_link": true
     },
     "gpuClass": "standard",
     "kernelspec": {
@@ -384,4 +384,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}
\ No newline at end of file

From 98f13cbed48bb5e7cf7d11fe1f5e2f935820680d Mon Sep 17 00:00:00 2001
From: Nikhil Mohan <47728081+nikmo33@users.noreply.github.com>
Date: Tue, 13 Dec 2022 18:09:31 +0000
Subject: [PATCH 11/24] Fix circular imports (#1115)

* wip

* remove bad changes

* update dmeo

* cleanup

* change name

* cleanup
---
 nerfstudio/configs/base_config.py       | 101 +------------------
 nerfstudio/configs/experiment_config.py | 123 ++++++++++++++++++++++++
 nerfstudio/configs/method_configs.py    |  27 +++---
 nerfstudio/engine/optimizers.py         |  23 -----
 nerfstudio/engine/trainer.py            |  27 +++++-
 nerfstudio/exporter/exporter_utils.py   |   1 -
 nerfstudio/utils/eval_utils.py          |   9 +-
 nerfstudio/utils/writer.py              |   6 +-
 scripts/render.py                       |   1 -
 scripts/train.py                        |  14 +--
 tests/test_train.py                     |   4 +-
 11 files changed, 175 insertions(+), 161 deletions(-)
 create mode 100644 nerfstudio/configs/experiment_config.py

diff --git a/nerfstudio/configs/base_config.py b/nerfstudio/configs/base_config.py
index 53bc7b4c4..a74f07ed7 100644
--- a/nerfstudio/configs/base_config.py
+++ b/nerfstudio/configs/base_config.py
@@ -20,23 +20,14 @@ from __future__ import annotations
 
 import warnings
 from dataclasses import dataclass
-from datetime import datetime
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Tuple, Type
-
-import yaml
-from rich.console import Console
-from typing_extensions import Literal
-
-from nerfstudio.configs.config_utils import to_immutable_dict
+from typing import Any, List, Optional, Tuple, Type
 
 # model instances
 from nerfstudio.utils import writer
 
 warnings.filterwarnings("ignore", module="torchvision")
 
-CONSOLE = Console(width=120)
-
 # Pretty printing class
 class PrintableConfig:  # pylint: disable=too-few-public-methods
     """Printable Config defining str function"""
@@ -186,93 +177,3 @@ class ViewerConfig(PrintableConfig):
     skip_openrelay: bool = False
     """Avoid using openrelay to communicate with the viewer. Try disabling if you have trouble
     connecting to the viewer"""
-
-
-from nerfstudio.engine.optimizers import OptimizerConfig
-from nerfstudio.engine.schedulers import SchedulerConfig
-from nerfstudio.pipelines.base_pipeline import VanillaPipelineConfig
-
-
-@dataclass
-class Config(PrintableConfig):
-    """Full config contents"""
-
-    output_dir: Path = Path("outputs")
-    """relative or absolute output directory to save all checkpoints and logging"""
-    method_name: Optional[str] = None
-    """Method name. Required to set in python or via cli"""
-    experiment_name: Optional[str] = None
-    """Experiment name. If None, will automatically be set to dataset name"""
-    timestamp: str = "{timestamp}"
-    """Experiment timestamp."""
-    machine: MachineConfig = MachineConfig()
-    """Machine configuration"""
-    logging: LoggingConfig = LoggingConfig()
-    """Logging configuration"""
-    viewer: ViewerConfig = ViewerConfig()
-    """Viewer configuration"""
-    trainer: TrainerConfig = TrainerConfig()
-    """Trainer configuration"""
-    pipeline: VanillaPipelineConfig = VanillaPipelineConfig()
-    """Pipeline configuration"""
-    optimizers: Dict[str, Any] = to_immutable_dict(
-        {
-            "fields": {
-                "optimizer": OptimizerConfig(),
-                "scheduler": SchedulerConfig(),
-            }
-        }
-    )
-    """Dictionary of optimizer groups and their schedulers"""
-    vis: Literal["viewer", "wandb", "tensorboard"] = "wandb"
-    """Which visualizer to use."""
-    data: Optional[Path] = None
-    """Alias for --pipeline.datamanager.dataparser.data"""
-
-    def is_viewer_enabled(self) -> bool:
-        """Checks if a viewer is enabled."""
-        return "viewer" == self.vis
-
-    def is_wandb_enabled(self) -> bool:
-        """Checks if wandb is enabled."""
-        return "wandb" == self.vis
-
-    def is_tensorboard_enabled(self) -> bool:
-        """Checks if tensorboard is enabled."""
-        return "tensorboard" == self.vis
-
-    def set_timestamp(self) -> None:
-        """Dynamically set the experiment timestamp"""
-        if self.timestamp == "{timestamp}":
-            self.timestamp = datetime.now().strftime("%Y-%m-%d_%H%M%S")
-
-    def set_experiment_name(self) -> None:
-        """Dynamically set the experiment name"""
-        if self.experiment_name is None:
-            self.experiment_name = str(self.pipeline.datamanager.dataparser.data).replace("../", "").replace("/", "-")
-
-    def get_base_dir(self) -> Path:
-        """Retrieve the base directory to set relative paths"""
-        # check the experiment and method names
-        assert self.method_name is not None, "Please set method name in config or via the cli"
-        self.set_experiment_name()
-        return Path(f"{self.output_dir}/{self.experiment_name}/{self.method_name}/{self.timestamp}")
-
-    def get_checkpoint_dir(self) -> Path:
-        """Retrieve the checkpoint directory"""
-        return Path(self.get_base_dir() / self.trainer.relative_model_dir)
-
-    def print_to_terminal(self) -> None:
-        """Helper to pretty print config to terminal"""
-        CONSOLE.rule("Config")
-        CONSOLE.print(self)
-        CONSOLE.rule("")
-
-    def save_config(self) -> None:
-        """Save config to base directory"""
-        base_dir = self.get_base_dir()
-        assert base_dir is not None
-        base_dir.mkdir(parents=True, exist_ok=True)
-        config_yaml_path = base_dir / "config.yml"
-        CONSOLE.log(f"Saving config to: {config_yaml_path}")
-        config_yaml_path.write_text(yaml.dump(self), "utf8")
diff --git a/nerfstudio/configs/experiment_config.py b/nerfstudio/configs/experiment_config.py
new file mode 100644
index 000000000..e78c8de59
--- /dev/null
+++ b/nerfstudio/configs/experiment_config.py
@@ -0,0 +1,123 @@
+# Copyright 2022 The Nerfstudio Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Config used for running an experiment"""
+
+from dataclasses import dataclass
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, Optional
+
+import yaml
+from rich.console import Console
+from typing_extensions import Literal
+
+from nerfstudio.configs.base_config import (
+    LoggingConfig,
+    MachineConfig,
+    PrintableConfig,
+    TrainerConfig,
+    ViewerConfig,
+)
+from nerfstudio.configs.config_utils import to_immutable_dict
+from nerfstudio.engine.optimizers import OptimizerConfig
+from nerfstudio.engine.schedulers import SchedulerConfig
+from nerfstudio.pipelines.base_pipeline import VanillaPipelineConfig
+
+CONSOLE = Console(width=120)
+
+
+@dataclass
+class ExperimentConfig(PrintableConfig):
+    """Full config contents"""
+
+    output_dir: Path = Path("outputs")
+    """relative or absolute output directory to save all checkpoints and logging"""
+    method_name: Optional[str] = None
+    """Method name. Required to set in python or via cli"""
+    experiment_name: Optional[str] = None
+    """Experiment name. If None, will automatically be set to dataset name"""
+    timestamp: str = "{timestamp}"
+    """Experiment timestamp."""
+    machine: MachineConfig = MachineConfig()
+    """Machine configuration"""
+    logging: LoggingConfig = LoggingConfig()
+    """Logging configuration"""
+    viewer: ViewerConfig = ViewerConfig()
+    """Viewer configuration"""
+    trainer: TrainerConfig = TrainerConfig()
+    """Trainer configuration"""
+    pipeline: VanillaPipelineConfig = VanillaPipelineConfig()
+    """Pipeline configuration"""
+    optimizers: Dict[str, Any] = to_immutable_dict(
+        {
+            "fields": {
+                "optimizer": OptimizerConfig(),
+                "scheduler": SchedulerConfig(),
+            }
+        }
+    )
+    """Dictionary of optimizer groups and their schedulers"""
+    vis: Literal["viewer", "wandb", "tensorboard"] = "wandb"
+    """Which visualizer to use."""
+    data: Optional[Path] = None
+    """Alias for --pipeline.datamanager.dataparser.data"""
+
+    def is_viewer_enabled(self) -> bool:
+        """Checks if a viewer is enabled."""
+        return "viewer" == self.vis
+
+    def is_wandb_enabled(self) -> bool:
+        """Checks if wandb is enabled."""
+        return "wandb" == self.vis
+
+    def is_tensorboard_enabled(self) -> bool:
+        """Checks if tensorboard is enabled."""
+        return "tensorboard" == self.vis
+
+    def set_timestamp(self) -> None:
+        """Dynamically set the experiment timestamp"""
+        if self.timestamp == "{timestamp}":
+            self.timestamp = datetime.now().strftime("%Y-%m-%d_%H%M%S")
+
+    def set_experiment_name(self) -> None:
+        """Dynamically set the experiment name"""
+        if self.experiment_name is None:
+            self.experiment_name = str(self.pipeline.datamanager.dataparser.data).replace("../", "").replace("/", "-")
+
+    def get_base_dir(self) -> Path:
+        """Retrieve the base directory to set relative paths"""
+        # check the experiment and method names
+        assert self.method_name is not None, "Please set method name in config or via the cli"
+        self.set_experiment_name()
+        return Path(f"{self.output_dir}/{self.experiment_name}/{self.method_name}/{self.timestamp}")
+
+    def get_checkpoint_dir(self) -> Path:
+        """Retrieve the checkpoint directory"""
+        return Path(self.get_base_dir() / self.trainer.relative_model_dir)
+
+    def print_to_terminal(self) -> None:
+        """Helper to pretty print config to terminal"""
+        CONSOLE.rule("Config")
+        CONSOLE.print(self)
+        CONSOLE.rule("")
+
+    def save_config(self) -> None:
+        """Save config to base directory"""
+        base_dir = self.get_base_dir()
+        assert base_dir is not None
+        base_dir.mkdir(parents=True, exist_ok=True)
+        config_yaml_path = base_dir / "config.yml"
+        CONSOLE.log(f"Saving config to: {config_yaml_path}")
+        config_yaml_path.write_text(yaml.dump(self), "utf8")
diff --git a/nerfstudio/configs/method_configs.py b/nerfstudio/configs/method_configs.py
index 6fb532e14..b02d782b9 100644
--- a/nerfstudio/configs/method_configs.py
+++ b/nerfstudio/configs/method_configs.py
@@ -23,12 +23,8 @@ from typing import Dict
 import tyro
 
 from nerfstudio.cameras.camera_optimizers import CameraOptimizerConfig
-from nerfstudio.configs.base_config import (
-    Config,
-    SchedulerConfig,
-    TrainerConfig,
-    ViewerConfig,
-)
+from nerfstudio.configs.base_config import TrainerConfig, ViewerConfig
+from nerfstudio.configs.experiment_config import ExperimentConfig
 from nerfstudio.data.datamanagers.base_datamanager import VanillaDataManagerConfig
 from nerfstudio.data.datamanagers.semantic_datamanager import SemanticDataManagerConfig
 from nerfstudio.data.datamanagers.variable_res_datamanager import (
@@ -42,6 +38,7 @@ from nerfstudio.data.dataparsers.phototourism_dataparser import (
     PhototourismDataParserConfig,
 )
 from nerfstudio.engine.optimizers import AdamOptimizerConfig, RAdamOptimizerConfig
+from nerfstudio.engine.schedulers import SchedulerConfig
 from nerfstudio.field_components.temporal_distortions import TemporalDistortionKind
 from nerfstudio.models.instant_ngp import InstantNGPModelConfig
 from nerfstudio.models.mipnerf import MipNerfModel
@@ -52,7 +49,7 @@ from nerfstudio.models.vanilla_nerf import NeRFModel, VanillaModelConfig
 from nerfstudio.pipelines.base_pipeline import VanillaPipelineConfig
 from nerfstudio.pipelines.dynamic_batch import DynamicBatchPipelineConfig
 
-method_configs: Dict[str, Config] = {}
+method_configs: Dict[str, ExperimentConfig] = {}
 descriptions = {
     "nerfacto": "Recommended real-time model tuned for real captures. This model will be continually updated.",
     "instant-ngp": "Implementation of Instant-NGP. Recommended real-time model for bounded synthetic data.",
@@ -64,7 +61,7 @@ descriptions = {
     "phototourism": "Uses the Phototourism data.",
 }
 
-method_configs["nerfacto"] = Config(
+method_configs["nerfacto"] = ExperimentConfig(
     method_name="nerfacto",
     trainer=TrainerConfig(
         steps_per_eval_batch=500, steps_per_save=2000, max_num_iterations=30000, mixed_precision=True
@@ -94,7 +91,7 @@ method_configs["nerfacto"] = Config(
     vis="viewer",
 )
 
-method_configs["instant-ngp"] = Config(
+method_configs["instant-ngp"] = ExperimentConfig(
     method_name="instant-ngp",
     trainer=TrainerConfig(
         steps_per_eval_batch=500, steps_per_save=2000, max_num_iterations=30000, mixed_precision=True
@@ -113,7 +110,7 @@ method_configs["instant-ngp"] = Config(
     vis="viewer",
 )
 
-method_configs["mipnerf"] = Config(
+method_configs["mipnerf"] = ExperimentConfig(
     method_name="mipnerf",
     pipeline=VanillaPipelineConfig(
         datamanager=VanillaDataManagerConfig(dataparser=NerfstudioDataParserConfig(), train_num_rays_per_batch=1024),
@@ -133,7 +130,7 @@ method_configs["mipnerf"] = Config(
     },
 )
 
-method_configs["semantic-nerfw"] = Config(
+method_configs["semantic-nerfw"] = ExperimentConfig(
     method_name="semantic-nerfw",
     trainer=TrainerConfig(
         steps_per_eval_batch=500, steps_per_save=2000, max_num_iterations=30000, mixed_precision=True
@@ -158,7 +155,7 @@ method_configs["semantic-nerfw"] = Config(
     vis="viewer",
 )
 
-method_configs["vanilla-nerf"] = Config(
+method_configs["vanilla-nerf"] = ExperimentConfig(
     method_name="vanilla-nerf",
     pipeline=VanillaPipelineConfig(
         datamanager=VanillaDataManagerConfig(
@@ -178,7 +175,7 @@ method_configs["vanilla-nerf"] = Config(
     },
 )
 
-method_configs["tensorf"] = Config(
+method_configs["tensorf"] = ExperimentConfig(
     method_name="tensorf",
     trainer=TrainerConfig(mixed_precision=False),
     pipeline=VanillaPipelineConfig(
@@ -199,7 +196,7 @@ method_configs["tensorf"] = Config(
     },
 )
 
-method_configs["dnerf"] = Config(
+method_configs["dnerf"] = ExperimentConfig(
     method_name="dnerf",
     pipeline=VanillaPipelineConfig(
         datamanager=VanillaDataManagerConfig(dataparser=DNeRFDataParserConfig()),
@@ -221,7 +218,7 @@ method_configs["dnerf"] = Config(
     },
 )
 
-method_configs["phototourism"] = Config(
+method_configs["phototourism"] = ExperimentConfig(
     method_name="phototourism",
     trainer=TrainerConfig(
         steps_per_eval_batch=500, steps_per_save=2000, max_num_iterations=30000, mixed_precision=True
diff --git a/nerfstudio/engine/optimizers.py b/nerfstudio/engine/optimizers.py
index 5bae109d0..c97b10580 100644
--- a/nerfstudio/engine/optimizers.py
+++ b/nerfstudio/engine/optimizers.py
@@ -61,29 +61,6 @@ class RAdamOptimizerConfig(OptimizerConfig):
     _target: Type = torch.optim.RAdam
 
 
-def setup_optimizers(config: base_config.Config, param_groups: Dict[str, List[Parameter]]) -> "Optimizers":
-    """Helper to set up the optimizers
-
-    Args:
-        config: The trainer configuration object.
-        param_groups: A dictionary of parameter groups to optimize.
-
-    Returns:
-        The optimizers object.
-    """
-    optimizer_config = config.optimizers.copy()
-
-    # Add the camera optimizer if enabled.
-    camera_optimizer_config = config.pipeline.datamanager.camera_optimizer
-    if camera_optimizer_config.mode != "off":
-        assert camera_optimizer_config.param_group not in optimizer_config
-        optimizer_config[camera_optimizer_config.param_group] = {
-            "optimizer": config.pipeline.datamanager.camera_optimizer.optimizer,
-            "scheduler": config.pipeline.datamanager.camera_optimizer.scheduler,
-        }
-    return Optimizers(optimizer_config, param_groups)
-
-
 class Optimizers:
     """A set of optimizers.
 
diff --git a/nerfstudio/engine/trainer.py b/nerfstudio/engine/trainer.py
index 445788fbf..513fb194e 100644
--- a/nerfstudio/engine/trainer.py
+++ b/nerfstudio/engine/trainer.py
@@ -28,13 +28,13 @@ from rich.console import Console
 from torch.cuda.amp.grad_scaler import GradScaler
 from typing_extensions import Literal
 
-from nerfstudio.configs import base_config as cfg
+from nerfstudio.configs.experiment_config import ExperimentConfig
 from nerfstudio.engine.callbacks import (
     TrainingCallback,
     TrainingCallbackAttributes,
     TrainingCallbackLocation,
 )
-from nerfstudio.engine.optimizers import Optimizers, setup_optimizers
+from nerfstudio.engine.optimizers import Optimizers
 from nerfstudio.pipelines.base_pipeline import VanillaPipeline
 from nerfstudio.utils import profiler, writer
 from nerfstudio.utils.decorators import (
@@ -71,7 +71,7 @@ class Trainer:
     optimizers: Optimizers
     callbacks: List[TrainingCallback]
 
-    def __init__(self, config: cfg.Config, local_rank: int = 0, world_size: int = 1):
+    def __init__(self, config: ExperimentConfig, local_rank: int = 0, world_size: int = 1):
         self.config = config
         self.local_rank = local_rank
         self.world_size = world_size
@@ -96,7 +96,7 @@ class Trainer:
         self._check_viewer_warnings()
         # set up writers/profilers if enabled
         writer_log_path = self.base_dir / config.logging.relative_log_dir
-        writer.setup_event_writer(config, log_dir=writer_log_path)
+        writer.setup_event_writer(config.is_wandb_enabled(), config.is_tensorboard_enabled(), log_dir=writer_log_path)
         writer.setup_local_writer(
             config.logging, max_iter=config.trainer.max_num_iterations, banner_messages=banner_messages
         )
@@ -115,7 +115,7 @@ class Trainer:
         self.pipeline = self.config.pipeline.setup(
             device=self.device, test_mode=test_mode, world_size=self.world_size, local_rank=self.local_rank
         )
-        self.optimizers = setup_optimizers(self.config, self.pipeline.get_param_groups())
+        self.optimizers = self.setup_optimizers()
 
         self._load_checkpoint()
 
@@ -128,6 +128,23 @@ class Trainer:
             )
         )
 
+    def setup_optimizers(self) -> Optimizers:
+        """Helper to set up the optimizers
+
+        Returns:
+            The optimizers object given the experiment config.
+        """
+        optimizer_config = self.config.optimizers.copy()
+        camera_optimizer_config = self.config.pipeline.datamanager.camera_optimizer
+        param_groups = self.pipeline.get_param_groups()
+        if camera_optimizer_config.mode != "off":
+            assert camera_optimizer_config.param_group not in optimizer_config
+            optimizer_config[camera_optimizer_config.param_group] = {
+                "optimizer": camera_optimizer_config.optimizer,
+                "scheduler": camera_optimizer_config.scheduler,
+            }
+        return Optimizers(optimizer_config, param_groups)
+
     def train(self) -> None:
         """Train the model."""
         assert self.pipeline.datamanager.train_dataset is not None, "Missing DatsetInputs"
diff --git a/nerfstudio/exporter/exporter_utils.py b/nerfstudio/exporter/exporter_utils.py
index c3db219ed..3e5f4425e 100644
--- a/nerfstudio/exporter/exporter_utils.py
+++ b/nerfstudio/exporter/exporter_utils.py
@@ -39,7 +39,6 @@ from rich.progress import (
 from torchtyping import TensorType
 
 from nerfstudio.cameras.cameras import Cameras
-from nerfstudio.configs.base_config import Config  # pylint: disable=unused-import
 from nerfstudio.pipelines.base_pipeline import Pipeline
 from nerfstudio.utils.rich_utils import ItersPerSecColumn
 
diff --git a/nerfstudio/utils/eval_utils.py b/nerfstudio/utils/eval_utils.py
index 7401a916c..8d780cc82 100644
--- a/nerfstudio/utils/eval_utils.py
+++ b/nerfstudio/utils/eval_utils.py
@@ -27,13 +27,14 @@ import yaml
 from rich.console import Console
 from typing_extensions import Literal
 
-from nerfstudio.configs import base_config as cfg
+from nerfstudio.configs.base_config import TrainerConfig
+from nerfstudio.configs.experiment_config import ExperimentConfig
 from nerfstudio.pipelines.base_pipeline import Pipeline
 
 CONSOLE = Console(width=120)
 
 
-def eval_load_checkpoint(config: cfg.TrainerConfig, pipeline: Pipeline) -> Path:
+def eval_load_checkpoint(config: TrainerConfig, pipeline: Pipeline) -> Path:
     ## TODO: ideally eventually want to get this to be the same as whatever is used to load train checkpoint too
     """Helper function to load checkpointed pipeline
 
@@ -68,7 +69,7 @@ def eval_setup(
     config_path: Path,
     eval_num_rays_per_chunk: Optional[int] = None,
     test_mode: Literal["test", "val", "inference"] = "test",
-) -> Tuple[cfg.Config, Pipeline, Path]:
+) -> Tuple[ExperimentConfig, Pipeline, Path]:
     """Shared setup for loading a saved pipeline for evaluation.
 
     Args:
@@ -85,7 +86,7 @@ def eval_setup(
     """
     # load save config
     config = yaml.load(config_path.read_text(), Loader=yaml.Loader)
-    assert isinstance(config, cfg.Config)
+    assert isinstance(config, ExperimentConfig)
 
     if eval_num_rays_per_chunk:
         config.pipeline.model.eval_num_rays_per_chunk = eval_num_rays_per_chunk
diff --git a/nerfstudio/utils/writer.py b/nerfstudio/utils/writer.py
index 76d7a3aa9..d85c75bcf 100644
--- a/nerfstudio/utils/writer.py
+++ b/nerfstudio/utils/writer.py
@@ -188,7 +188,7 @@ def setup_local_writer(config: cfg.LoggingConfig, max_iter: int, banner_messages
 
 
 @check_main_thread
-def setup_event_writer(config: cfg.Config, log_dir: Path) -> None:
+def setup_event_writer(is_wandb_enabled: bool, is_tensorboard_enabled: bool, log_dir: Path) -> None:
     """Initialization of all event writers specified in config
 
     Args:
@@ -197,11 +197,11 @@ def setup_event_writer(config: cfg.Config, log_dir: Path) -> None:
         banner_messages: list of messages to always display at bottom of screen
     """
     using_event_writer = False
-    if config.is_wandb_enabled():
+    if is_wandb_enabled:
         curr_writer = WandbWriter(log_dir=log_dir)
         EVENT_WRITERS.append(curr_writer)
         using_event_writer = True
-    if config.is_tensorboard_enabled():
+    if is_tensorboard_enabled:
         curr_writer = TensorboardWriter(log_dir=log_dir)
         EVENT_WRITERS.append(curr_writer)
         using_event_writer = True
diff --git a/scripts/render.py b/scripts/render.py
index 60154f8b7..c8bb4fdae 100644
--- a/scripts/render.py
+++ b/scripts/render.py
@@ -26,7 +26,6 @@ from typing_extensions import Literal, assert_never
 
 from nerfstudio.cameras.camera_paths import get_path_from_json, get_spiral_path
 from nerfstudio.cameras.cameras import Cameras
-from nerfstudio.configs.base_config import Config  # pylint: disable=unused-import
 from nerfstudio.pipelines.base_pipeline import Pipeline
 from nerfstudio.utils import install_checks
 from nerfstudio.utils.eval_utils import eval_setup
diff --git a/scripts/train.py b/scripts/train.py
index 37717a11c..910dbff1c 100755
--- a/scripts/train.py
+++ b/scripts/train.py
@@ -45,8 +45,8 @@ import tyro
 import yaml
 from rich.console import Console
 
-from nerfstudio.configs import base_config as cfg
 from nerfstudio.configs.config_utils import convert_markup_to_ansi
+from nerfstudio.configs.experiment_config import ExperimentConfig
 from nerfstudio.configs.method_configs import AnnotatedBaseConfigUnion
 from nerfstudio.engine.trainer import Trainer
 from nerfstudio.utils import comms, profiler
@@ -74,7 +74,7 @@ def _set_random_seed(seed) -> None:
     torch.manual_seed(seed)
 
 
-def train_loop(local_rank: int, world_size: int, config: cfg.Config, global_rank: int = 0):
+def train_loop(local_rank: int, world_size: int, config: ExperimentConfig, global_rank: int = 0):
     """Main training function that sets up and runs the trainer per process
 
     Args:
@@ -95,7 +95,7 @@ def _distributed_worker(
     num_gpus_per_machine: int,
     machine_rank: int,
     dist_url: str,
-    config: cfg.Config,
+    config: ExperimentConfig,
     timeout: timedelta = DEFAULT_TIMEOUT,
 ) -> Any:
     """Spawned distributed worker that handles the initialization of process group and handles the
@@ -110,7 +110,7 @@ def _distributed_worker(
         dist_url: URL to connect to for distributed jobs, including protocol
             E.g., "tcp://127.0.0.1:8686".
             It can be set to "auto" to automatically select a free port on localhost.
-        config: Config specifying training regimen.
+        config: ExperimentConfig specifying training regimen.
         timeout: Timeout of the distributed workers.
 
     Raises:
@@ -150,7 +150,7 @@ def launch(
     num_machines: int = 1,
     machine_rank: int = 0,
     dist_url: str = "auto",
-    config: Optional[cfg.Config] = None,
+    config: Optional[ExperimentConfig] = None,
     timeout: timedelta = DEFAULT_TIMEOUT,
 ) -> None:
     """Function that spawns muliple processes to call on main_func
@@ -161,7 +161,7 @@ def launch(
         num_machines (int, optional): total number of machines
         machine_rank (int, optional): rank of this machine.
         dist_url (str, optional): url to connect to for distributed jobs.
-        config (Config, optional): config file specifying training regimen.
+        config (ExperimentConfig, optional): config file specifying training regimen.
         timeout (timedelta, optional): timeout of the distributed workers.
     """
     assert config is not None
@@ -215,7 +215,7 @@ def launch(
             profiler.flush_profiler(config.logging)
 
 
-def main(config: cfg.Config) -> None:
+def main(config: ExperimentConfig) -> None:
     """Main function."""
 
     config.set_timestamp()
diff --git a/tests/test_train.py b/tests/test_train.py
index 6332ba260..dfc2d651e 100644
--- a/tests/test_train.py
+++ b/tests/test_train.py
@@ -9,7 +9,7 @@ from pathlib import Path
 
 import pytest
 
-from nerfstudio.configs.base_config import Config
+from nerfstudio.configs.experiment_config import ExperimentConfig
 from nerfstudio.configs.method_configs import method_configs
 from nerfstudio.data.dataparsers.blender_dataparser import BlenderDataParserConfig
 from scripts.train import train_loop
@@ -17,7 +17,7 @@ from scripts.train import train_loop
 BLACKLIST = ["base", "semantic-nerfw", "instant-ngp", "nerfacto", "phototourism"]
 
 
-def set_reduced_config(config: Config):
+def set_reduced_config(config: ExperimentConfig):
     """Reducing the config settings to speedup test"""
     config.machine.num_gpus = 0
     config.trainer.max_num_iterations = 2

From 1a70665e76bfbc71ef193cc6d3429efa582ddaff Mon Sep 17 00:00:00 2001
From: Tao <ttaoREtw@gmail.com>
Date: Wed, 14 Dec 2022 02:16:34 +0800
Subject: [PATCH 12/24] Fix slow training issue when using mask (#1114)

---
 nerfstudio/data/pixel_samplers.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/nerfstudio/data/pixel_samplers.py b/nerfstudio/data/pixel_samplers.py
index 1066155c7..b76d39f16 100644
--- a/nerfstudio/data/pixel_samplers.py
+++ b/nerfstudio/data/pixel_samplers.py
@@ -38,7 +38,7 @@ def collate_image_dataset_batch(batch: Dict, num_rays_per_batch: int, keep_full_
 
     # only sample within the mask, if the mask is in the batch
     if "mask" in batch:
-        nonzero_indices = torch.nonzero(batch["mask"][..., 0].to(device), as_tuple=False)
+        nonzero_indices = torch.nonzero(batch["mask"][..., 0], as_tuple=False)
         chosen_indices = random.sample(range(len(nonzero_indices)), k=num_rays_per_batch)
         indices = nonzero_indices[chosen_indices]
     else:

From 008cc8f144b65272645471c6748ac3fe2af1427c Mon Sep 17 00:00:00 2001
From: Terrance Wang <terrance.3512@gmail.com>
Date: Tue, 13 Dec 2022 12:39:41 -0800
Subject: [PATCH 13/24] change normals grad calculation (#1108)

* change normals grad calculation

* changing normal calc
---
 nerfstudio/fields/base_field.py | 13 +++++++++----
 1 file changed, 9 insertions(+), 4 deletions(-)

diff --git a/nerfstudio/fields/base_field.py b/nerfstudio/fields/base_field.py
index 043a29e01..c24d9659c 100644
--- a/nerfstudio/fields/base_field.py
+++ b/nerfstudio/fields/base_field.py
@@ -74,10 +74,15 @@ class Field(nn.Module):
             self._sample_locations.shape[:-1] == self._density_before_activation.shape[:-1]
         ), "Sample locations and density must have the same shape besides the last dimension."
 
-        self._density_before_activation.backward(
-            gradient=torch.ones_like(self._density_before_activation), inputs=self._sample_locations, retain_graph=True
-        )
-        normals = -torch.nn.functional.normalize(self._sample_locations.grad, dim=-1)
+        normals = torch.autograd.grad(
+            self._density_before_activation,
+            self._sample_locations,
+            grad_outputs=torch.ones_like(self._density_before_activation),
+            retain_graph=True,
+        )[0]
+
+        normals = -torch.nn.functional.normalize(normals, dim=-1)
+
         return normals
 
     @abstractmethod

From 21e0ec6cd8e880265fe5644802dfd3ef2b0e1ed5 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Tue, 13 Dec 2022 12:50:12 -0800
Subject: [PATCH 14/24] Log start iter (#1119)

log start iter
---
 nerfstudio/utils/writer.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/nerfstudio/utils/writer.py b/nerfstudio/utils/writer.py
index d85c75bcf..d90e13b92 100644
--- a/nerfstudio/utils/writer.py
+++ b/nerfstudio/utils/writer.py
@@ -382,12 +382,12 @@ class LocalWriter:
         Args:
             step: current train step
         """
-        valid_step = step > 0 and step % GLOBAL_BUFFER["steps_per_log"] == 0
+        valid_step = step % GLOBAL_BUFFER["steps_per_log"] == 0
         if valid_step:
             if not self.has_printed and self.config.max_log_size:
                 CONSOLE.log(
                     f"Printing max of {self.config.max_log_size} lines. "
-                    "Set flag çççç[yellow]--logging.local-writer.max-log-size=0[/yellow] "
+                    "Set flag [yellow]--logging.local-writer.max-log-size=0[/yellow] "
                     "to disable line wrapping."
                 )
             latest_map, new_key = self._consolidate_events()

From 96f269cc1a5313dc5bc4ce742006305e4f68dfb6 Mon Sep 17 00:00:00 2001
From: dozeri83 <109915435+dozeri83@users.noreply.github.com>
Date: Tue, 13 Dec 2022 23:05:48 +0200
Subject: [PATCH 15/24] instant-ngp-bounded model (#1116)

* inerted a new model configuration instant-ngp-bounded

* added more remarks and small fixes

* went back to old near plane

* added the oprtion to get a file as well as directory in nerfstudio data parser

* pretify prev commit

* review fixes

* more clear explanation in README.md

* reverted readme changes

* fixed merge bug

* review changes. update config.data docs support for json files inputs

Co-authored-by: dror <you@example.com>
---
 nerfstudio/configs/method_configs.py          | 35 +++++++++-
 .../dataparsers/instant_ngp_dataparser.py     | 64 ++++++++++++++-----
 .../data/dataparsers/nerfstudio_dataparser.py | 32 +++++++---
 nerfstudio/model_components/ray_samplers.py   |  3 +-
 nerfstudio/models/instant_ngp.py              | 10 ++-
 scripts/benchmarking/launch_train_blender.sh  | 11 +++-
 tests/test_train.py                           |  2 +-
 7 files changed, 123 insertions(+), 34 deletions(-)

diff --git a/nerfstudio/configs/method_configs.py b/nerfstudio/configs/method_configs.py
index b02d782b9..3d4b694d9 100644
--- a/nerfstudio/configs/method_configs.py
+++ b/nerfstudio/configs/method_configs.py
@@ -21,6 +21,7 @@ from __future__ import annotations
 from typing import Dict
 
 import tyro
+from nerfacc import ContractionType
 
 from nerfstudio.cameras.camera_optimizers import CameraOptimizerConfig
 from nerfstudio.configs.base_config import TrainerConfig, ViewerConfig
@@ -33,6 +34,9 @@ from nerfstudio.data.datamanagers.variable_res_datamanager import (
 from nerfstudio.data.dataparsers.blender_dataparser import BlenderDataParserConfig
 from nerfstudio.data.dataparsers.dnerf_dataparser import DNeRFDataParserConfig
 from nerfstudio.data.dataparsers.friends_dataparser import FriendsDataParserConfig
+from nerfstudio.data.dataparsers.instant_ngp_dataparser import (
+    InstantNGPDataParserConfig,
+)
 from nerfstudio.data.dataparsers.nerfstudio_dataparser import NerfstudioDataParserConfig
 from nerfstudio.data.dataparsers.phototourism_dataparser import (
     PhototourismDataParserConfig,
@@ -52,7 +56,8 @@ from nerfstudio.pipelines.dynamic_batch import DynamicBatchPipelineConfig
 method_configs: Dict[str, ExperimentConfig] = {}
 descriptions = {
     "nerfacto": "Recommended real-time model tuned for real captures. This model will be continually updated.",
-    "instant-ngp": "Implementation of Instant-NGP. Recommended real-time model for bounded synthetic data.",
+    "instant-ngp": "Implementation of Instant-NGP. Recommended real-time model for unbounded scenes.",
+    "instant-ngp-bounded": "Implementation of Instant-NGP. Recommended for bounded real and synthetic scenes",
     "mipnerf": "High quality model for bounded scenes. (slow)",
     "semantic-nerfw": "Predicts semantic segmentations and filters out transient objects.",
     "vanilla-nerf": "Original NeRF model. (slow)",
@@ -110,6 +115,34 @@ method_configs["instant-ngp"] = ExperimentConfig(
     vis="viewer",
 )
 
+
+method_configs["instant-ngp-bounded"] = ExperimentConfig(
+    method_name="instant-ngp-bounded",
+    trainer=TrainerConfig(
+        steps_per_eval_batch=500, steps_per_save=2000, max_num_iterations=30000, mixed_precision=True
+    ),
+    pipeline=DynamicBatchPipelineConfig(
+        datamanager=VanillaDataManagerConfig(dataparser=InstantNGPDataParserConfig(), train_num_rays_per_batch=8192),
+        model=InstantNGPModelConfig(
+            eval_num_rays_per_chunk=8192,
+            contraction_type=ContractionType.AABB,
+            render_step_size=0.001,
+            max_num_samples_per_ray=48,
+            near_plane=0.01,
+            background_color="black",
+        ),
+    ),
+    optimizers={
+        "fields": {
+            "optimizer": AdamOptimizerConfig(lr=1e-2, eps=1e-15),
+            "scheduler": None,
+        }
+    },
+    viewer=ViewerConfig(num_rays_per_chunk=64000),
+    vis="viewer",
+)
+
+
 method_configs["mipnerf"] = ExperimentConfig(
     method_name="mipnerf",
     pipeline=VanillaPipelineConfig(
diff --git a/nerfstudio/data/dataparsers/instant_ngp_dataparser.py b/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
index 289e23d55..6a3478749 100644
--- a/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
+++ b/nerfstudio/data/dataparsers/instant_ngp_dataparser.py
@@ -20,6 +20,7 @@ from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Dict, Tuple, Type
 
+import imageio
 import numpy as np
 import torch
 from rich.console import Console
@@ -44,10 +45,10 @@ class InstantNGPDataParserConfig(DataParserConfig):
     _target: Type = field(default_factory=lambda: InstantNGP)
     """target class to instantiate"""
     data: Path = Path("data/ours/posterv2")
-    """Directory specifying location of data."""
+    """Directory or explicit json file path specifying location of data."""
     scale_factor: float = 1.0
     """How much to scale the camera origins by."""
-    scene_scale: float = 0.33
+    scene_scale: float = 0.3333
     """How much to scale the scene."""
 
 
@@ -58,16 +59,34 @@ class InstantNGP(DataParser):
     config: InstantNGPDataParserConfig
 
     def _generate_dataparser_outputs(self, split="train"):
+        if self.config.data.suffix == ".json":
+            meta = load_from_json(self.config.data)
+            data_dir = self.config.data.parent
+        else:
+            meta = load_from_json(self.config.data / "transforms.json")
+            data_dir = self.config.data
 
-        meta = load_from_json(self.config.data / "transforms.json")
         image_filenames = []
         poses = []
         num_skipped_image_filenames = 0
         for frame in meta["frames"]:
-            fname = self.config.data / Path(frame["file_path"])
-            if not fname:
+            fname = data_dir / Path(frame["file_path"])
+            # search for png file
+            if not fname.exists():
+                fname = data_dir / Path(frame["file_path"] + ".png")
+            if not fname.exists():
+                CONSOLE.log(f"couldnt find {fname} image")
                 num_skipped_image_filenames += 1
             else:
+                if "w" not in meta:
+                    img_0 = imageio.imread(fname)
+                    h, w = img_0.shape[:2]
+                    meta["w"] = w
+                    if "h" in meta:
+                        meta_h = meta["h"]
+                        assert meta_h == h, f"height of image dont not correspond metadata {h} != {meta_h}"
+                    else:
+                        meta["h"] = h
                 image_filenames.append(fname)
                 poses.append(np.array(frame["transform_matrix"]))
         if num_skipped_image_filenames >= 0:
@@ -84,12 +103,18 @@ class InstantNGP(DataParser):
         camera_to_world = torch.from_numpy(poses[:, :3])  # camera to world transform
 
         distortion_params = camera_utils.get_distortion_params(
-            k1=float(meta["k1"]), k2=float(meta["k2"]), p1=float(meta["p1"]), p2=float(meta["p2"])
+            k1=float(meta.get("k1", 0)),
+            k2=float(meta.get("k2", 0)),
+            k3=float(meta.get("k3", 0)),
+            k4=float(meta.get("k4", 0)),
+            p1=float(meta.get("p1", 0)),
+            p2=float(meta.get("p2", 0)),
         )
 
         # in x,y,z order
         # assumes that the scene is centered at the origin
-        aabb_scale = meta["aabb_scale"]
+        aabb_scale = 0.5 * meta.get("aabb_scale", 1)
+
         scene_box = SceneBox(
             aabb=torch.tensor(
                 [[-aabb_scale, -aabb_scale, -aabb_scale], [aabb_scale, aabb_scale, aabb_scale]], dtype=torch.float32
@@ -98,14 +123,16 @@ class InstantNGP(DataParser):
 
         fl_x, fl_y = InstantNGP.get_focal_lengths(meta)
 
+        w, h = meta["w"], meta["h"]
+
         cameras = Cameras(
             fx=float(fl_x),
             fy=float(fl_y),
-            cx=float(meta["cx"]),
-            cy=float(meta["cy"]),
+            cx=float(meta.get("cx", 0.5 * w)),
+            cy=float(meta.get("cy", 0.5 * h)),
             distortion_params=distortion_params,
-            height=int(meta["h"]),
-            width=int(meta["w"]),
+            height=int(h),
+            width=int(w),
             camera_to_worlds=camera_to_world,
             camera_type=CameraType.PERSPECTIVE,
         )
@@ -140,12 +167,15 @@ class InstantNGP(DataParser):
         elif "camera_angle_x" in meta:
             fl_x = fov_to_focal_length(meta["camera_angle_x"], meta["w"])
 
-        if "fl_y" in meta:
-            fl_y = meta["fl_y"]
-        elif "y_fov" in meta:
-            fl_y = fov_to_focal_length(np.deg2rad(meta["y_fov"]), meta["h"])
-        elif "camera_angle_y" in meta:
-            fl_y = fov_to_focal_length(meta["camera_angle_y"], meta["h"])
+        if "camera_angle_y" not in meta or "y_fov" not in meta:
+            fl_y = fl_x
+        else:
+            if "fl_y" in meta:
+                fl_y = meta["fl_y"]
+            elif "y_fov" in meta:
+                fl_y = fov_to_focal_length(np.deg2rad(meta["y_fov"]), meta["h"])
+            elif "camera_angle_y" in meta:
+                fl_y = fov_to_focal_length(meta["camera_angle_y"], meta["h"])
 
         if fl_x == 0 or fl_y == 0:
             raise AttributeError("Focal length cannot be calculated from transforms.json (missing fields).")
diff --git a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
index d2c8c2d2e..e311a08cc 100644
--- a/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
+++ b/nerfstudio/data/dataparsers/nerfstudio_dataparser.py
@@ -47,7 +47,7 @@ class NerfstudioDataParserConfig(DataParserConfig):
     _target: Type = field(default_factory=lambda: Nerfstudio)
     """target class to instantiate"""
     data: Path = Path("data/nerfstudio/poster")
-    """Directory specifying location of data."""
+    """Directory or explicit json file path specifying location of data."""
     scale_factor: float = 1.0
     """How much to scale the camera origins by."""
     downscale_factor: Optional[int] = None
@@ -74,7 +74,13 @@ class Nerfstudio(DataParser):
     def _generate_dataparser_outputs(self, split="train"):
         # pylint: disable=too-many-statements
 
-        meta = load_from_json(self.config.data / "transforms.json")
+        if self.config.data.suffix == ".json":
+            meta = load_from_json(self.config.data)
+            data_dir = self.config.data.parent
+        else:
+            meta = load_from_json(self.config.data / "transforms.json")
+            data_dir = self.config.data
+
         image_filenames = []
         mask_filenames = []
         poses = []
@@ -101,7 +107,7 @@ class Nerfstudio(DataParser):
 
         for frame in meta["frames"]:
             filepath = PurePath(frame["file_path"])
-            fname = self._get_fname(filepath)
+            fname = self._get_fname(filepath, data_dir)
             if not fname.exists():
                 num_skipped_image_filenames += 1
                 continue
@@ -140,7 +146,11 @@ class Nerfstudio(DataParser):
             poses.append(np.array(frame["transform_matrix"]))
             if "mask_path" in frame:
                 mask_filepath = PurePath(frame["mask_path"])
-                mask_fname = self._get_fname(mask_filepath, downsample_folder_prefix="masks_")
+                mask_fname = self._get_fname(
+                    mask_filepath,
+                    data_dir,
+                    downsample_folder_prefix="masks_",
+                )
                 mask_filenames.append(mask_fname)
         if num_skipped_image_filenames >= 0:
             CONSOLE.log(f"Skipping {num_skipped_image_filenames} files in dataset split {split}.")
@@ -258,21 +268,25 @@ class Nerfstudio(DataParser):
         )
         return dataparser_outputs
 
-    def _get_fname(self, filepath: PurePath, downsample_folder_prefix="images_") -> Path:
+    def _get_fname(self, filepath: PurePath, data_dir: PurePath, downsample_folder_prefix="images_") -> Path:
         """Get the filename of the image file.
         downsample_folder_prefix can be used to point to auxillary image data, e.g. masks
+
+        filepath: the base file name of the transformations.
+        data_dir: the directory of the data that contains the transform file
+        downsample_folder_prefix: prefix of the newly generated downsampled images
         """
 
         if self.downscale_factor is None:
             if self.config.downscale_factor is None:
-                test_img = Image.open(self.config.data / filepath)
+                test_img = Image.open(data_dir / filepath)
                 h, w = test_img.size
                 max_res = max(h, w)
                 df = 0
                 while True:
                     if (max_res / 2 ** (df)) < MAX_AUTO_RESOLUTION:
                         break
-                    if not (self.config.data / f"{downsample_folder_prefix}{2**(df+1)}" / filepath.name).exists():
+                    if not (data_dir / f"{downsample_folder_prefix}{2**(df+1)}" / filepath.name).exists():
                         break
                     df += 1
 
@@ -282,5 +296,5 @@ class Nerfstudio(DataParser):
                 self.downscale_factor = self.config.downscale_factor
 
         if self.downscale_factor > 1:
-            return self.config.data / f"{downsample_folder_prefix}{self.downscale_factor}" / filepath.name
-        return self.config.data / filepath
+            return data_dir / f"{downsample_folder_prefix}{self.downscale_factor}" / filepath.name
+        return data_dir / filepath
diff --git a/nerfstudio/model_components/ray_samplers.py b/nerfstudio/model_components/ray_samplers.py
index a65bd2128..4bc16fc05 100644
--- a/nerfstudio/model_components/ray_samplers.py
+++ b/nerfstudio/model_components/ray_samplers.py
@@ -460,7 +460,8 @@ class VolumetricSampler(Sampler):
             rays_d=rays_d,
             scene_aabb=self.scene_aabb,
             grid=self.occupancy_grid,
-            sigma_fn=self.get_sigma_fn(rays_o, rays_d),
+            # this is a workaround - using density causes crash and damage quality. should be fixed
+            sigma_fn=None,  # self.get_sigma_fn(rays_o, rays_d),
             render_step_size=render_step_size,
             near_plane=near_plane,
             far_plane=far_plane,
diff --git a/nerfstudio/models/instant_ngp.py b/nerfstudio/models/instant_ngp.py
index f30d2ad9a..a67c1ec7d 100644
--- a/nerfstudio/models/instant_ngp.py
+++ b/nerfstudio/models/instant_ngp.py
@@ -28,6 +28,7 @@ from torch.nn import Parameter
 from torchmetrics import PeakSignalNoiseRatio
 from torchmetrics.functional import structural_similarity_index_measure
 from torchmetrics.image.lpip import LearnedPerceptualImagePatchSimilarity
+from typing_extensions import Literal
 
 from nerfstudio.cameras.rays import RayBundle
 from nerfstudio.engine.callbacks import (
@@ -76,8 +77,8 @@ class InstantNGPModelConfig(ModelConfig):
     """How far along ray to stop sampling."""
     use_appearance_embedding: bool = False
     """Whether to use an appearance embedding."""
-    randomize_background: bool = True
-    """Whether to randomize the background color."""
+    background_color: Literal["random", "black", "white"] = "random"
+    """The color that is given to untrained areas."""
 
 
 class NGPModel(Model):
@@ -122,7 +123,10 @@ class NGPModel(Model):
         )
 
         # renderers
-        background_color = "random" if self.config.randomize_background else colors.WHITE
+        background_color = "random"
+        if self.config.background_color in ["white", "black"]:
+            background_color = colors.COLORS_DICT[self.config.background_color]
+
         self.renderer_rgb = RGBRenderer(background_color=background_color)
         self.renderer_accumulation = AccumulationRenderer()
         self.renderer_depth = DepthRenderer(method="expected")
diff --git a/scripts/benchmarking/launch_train_blender.sh b/scripts/benchmarking/launch_train_blender.sh
index e57561e02..332ec95ef 100755
--- a/scripts/benchmarking/launch_train_blender.sh
+++ b/scripts/benchmarking/launch_train_blender.sh
@@ -62,6 +62,13 @@ timestamp=$(date "+%Y-%m-%d_%H%M%S")
 # kill all the background jobs if terminated:
 trap "trap - SIGTERM && kill -- -$$" SIGINT SIGTERM EXIT
 
+dataparser="blender-data"
+trans_file=""
+if [ "$method_name" = "instant-ngp-bounded" ]; then
+    dataparser=""
+    trans_file="/transforms_train.json"
+fi
+
 for dataset in "${DATASETS[@]}"; do
     if "$single" && [ -n "${GPU_PID[$idx]+x}" ]; then
         echo "Waiting for GPU ${GPU_IDX[$idx]}"
@@ -70,7 +77,7 @@ for dataset in "${DATASETS[@]}"; do
     fi
     export CUDA_VISIBLE_DEVICES="${GPU_IDX[$idx]}"
     ns-train "${method_name}" "${method_opts[@]}" \
-             --data="data/blender/${dataset}" \
+             --data="data/blender/${dataset}${trans_file}" \
              --experiment-name="blender_${dataset}_${tag}" \
              --trainer.relative-model-dir=nerfstudio_models/ \
              --trainer.steps-per-save=1000 \
@@ -79,7 +86,7 @@ for dataset in "${DATASETS[@]}"; do
              --logging.enable-profiler=False \
              --vis "${vis}" \
              --timestamp "$timestamp" \
-             blender-data & GPU_PID[$idx]=$!
+             ${dataparser} & GPU_PID[$idx]=$!
     echo "Launched ${method_name} ${dataset} on gpu ${GPU_IDX[$idx]}, ${tag}"
     
     # update gpu
diff --git a/tests/test_train.py b/tests/test_train.py
index dfc2d651e..f7e860275 100644
--- a/tests/test_train.py
+++ b/tests/test_train.py
@@ -14,7 +14,7 @@ from nerfstudio.configs.method_configs import method_configs
 from nerfstudio.data.dataparsers.blender_dataparser import BlenderDataParserConfig
 from scripts.train import train_loop
 
-BLACKLIST = ["base", "semantic-nerfw", "instant-ngp", "nerfacto", "phototourism"]
+BLACKLIST = ["base", "semantic-nerfw", "instant-ngp", "instant-ngp-bounded", "nerfacto", "phototourism"]
 
 
 def set_reduced_config(config: ExperimentConfig):

From c8daa1a1d756128a2bbdba4ee39d49ffbf4a2325 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Tue, 13 Dec 2022 13:24:22 -0800
Subject: [PATCH 16/24] Missing images error warning (#1122)

---
 nerfstudio/process_data/process_data_utils.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/nerfstudio/process_data/process_data_utils.py b/nerfstudio/process_data/process_data_utils.py
index e291d898a..e028bf1c0 100644
--- a/nerfstudio/process_data/process_data_utils.py
+++ b/nerfstudio/process_data/process_data_utils.py
@@ -167,6 +167,10 @@ def copy_images(data: Path, image_dir: Path, verbose) -> int:
         allowed_exts = [".jpg", ".jpeg", ".png", ".tif", ".tiff"]
         image_paths = sorted([p for p in data.glob("[!.]*") if p.suffix.lower() in allowed_exts])
 
+        if len(image_paths) == 0:
+            CONSOLE.log("[bold red]:skull: No usable images in the data folder.")
+            sys.exit(1)
+
         num_frames = len(copy_images_list(image_paths, image_dir, verbose))
 
     return num_frames

From a0a3def1623c8849776d4c03c6ffc448726492a2 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Tue, 13 Dec 2022 13:53:09 -0800
Subject: [PATCH 17/24] Fix datamanager dataparser_outputs (#1123)

* Fix datamanager dataparser_outputs

* Cast to float
---
 nerfstudio/data/datamanagers/base_datamanager.py     | 2 +-
 nerfstudio/data/datamanagers/semantic_datamanager.py | 2 +-
 nerfstudio/data/dataparsers/base_dataparser.py       | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/nerfstudio/data/datamanagers/base_datamanager.py b/nerfstudio/data/datamanagers/base_datamanager.py
index 7f1282c87..140d018ba 100644
--- a/nerfstudio/data/datamanagers/base_datamanager.py
+++ b/nerfstudio/data/datamanagers/base_datamanager.py
@@ -314,6 +314,7 @@ class VanillaDataManager(DataManager):  # pylint: disable=abstract-method
         self.test_mode = test_mode
         self.test_split = "test" if test_mode in ["test", "inference"] else "val"
         self.dataparser = self.config.dataparser.setup()
+        self.train_dataparser_outputs = self.dataparser.get_dataparser_outputs(split="train")
 
         self.train_dataset = self.create_train_dataset()
         self.eval_dataset = self.create_eval_dataset()
@@ -321,7 +322,6 @@ class VanillaDataManager(DataManager):  # pylint: disable=abstract-method
 
     def create_train_dataset(self) -> InputDataset:
         """Sets up the data loaders for training"""
-        self.train_dataparser_outputs = self.dataparser.get_dataparser_outputs(split="train")
         return InputDataset(
             dataparser_outputs=self.train_dataparser_outputs,
             scale_factor=self.config.camera_res_scale_factor,
diff --git a/nerfstudio/data/datamanagers/semantic_datamanager.py b/nerfstudio/data/datamanagers/semantic_datamanager.py
index b3cc223ae..188c7f6c3 100644
--- a/nerfstudio/data/datamanagers/semantic_datamanager.py
+++ b/nerfstudio/data/datamanagers/semantic_datamanager.py
@@ -42,7 +42,7 @@ class SemanticDataManager(VanillaDataManager):  # pylint: disable=abstract-metho
 
     def create_train_dataset(self) -> SemanticDataset:
         return SemanticDataset(
-            dataparser_outputs=self.dataparser.get_dataparser_outputs(split="train"),
+            dataparser_outputs=self.train_dataparser_outputs,
             scale_factor=self.config.camera_res_scale_factor,
         )
 
diff --git a/nerfstudio/data/dataparsers/base_dataparser.py b/nerfstudio/data/dataparsers/base_dataparser.py
index 0caf24cea..89c7c4e21 100644
--- a/nerfstudio/data/dataparsers/base_dataparser.py
+++ b/nerfstudio/data/dataparsers/base_dataparser.py
@@ -82,7 +82,7 @@ class DataparserOutputs:
         """
         data = {
             "transform": self.dataparser_transform.tolist(),
-            "scale": self.dataparser_scale,
+            "scale": float(self.dataparser_scale),
         }
         if not path.parent.exists():
             path.parent.mkdir(parents=True)

From 6f85d7118fc3b317e926515497c4cf5de7650039 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Tue, 13 Dec 2022 18:37:31 -0800
Subject: [PATCH 18/24] Add docs for KIRI Engine (#1124)

Add docs for KIRI engine
---
 README.md                             |  17 +++----
 docs/quickstart/custom_dataset.md     |  65 ++++++++++++++++++++++----
 docs/quickstart/imgs/kiri_capture.png | Bin 0 -> 74639 bytes
 docs/quickstart/imgs/kiri_setup.png   | Bin 0 -> 135526 bytes
 4 files changed, 65 insertions(+), 17 deletions(-)
 create mode 100644 docs/quickstart/imgs/kiri_capture.png
 create mode 100644 docs/quickstart/imgs/kiri_setup.png

diff --git a/README.md b/README.md
index 3050b80dd..edef31622 100644
--- a/README.md
+++ b/README.md
@@ -184,14 +184,15 @@ ns-export pointcloud --help
 
 Using an existing dataset is great, but likely you want to use your own data! We support various methods for using your own data. Before it can be used in nerfstudio, the camera location and orientations must be determined and then converted into our format using `ns-process-data`. We rely on external tools for this, instructions and information can be found in the documentation.
 
-| Data                                                                                              | Requirements     | Preprocessing Speed |
-| ------------------------------------------------------------------------------------------------- | ---------------- | ------------------- |
-| 📷 [Images](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#images-or-video)    | COLMAP           | 🐢                  |
-| 📹 [Video](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#images-or-video)     | COLMAP           | 🐢                  |
-| 📱 [Polycam](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#polycam-capture)   | LiDAR iOS Device | 🐇                  |
-| 📱 [Record3D](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#record3d-capture) | LiDAR iOS Device | 🐇                  |
-| 🖥 [Metashape](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#metashape)        |                  | 🐢                  |
-| 🛠 [Custom](https://docs.nerf.studio/en/latest/quickstart/data_conventions.html)                   | Poses            | 🐇                  |
+| Data                                                                                              | Capture Device | Requirements                                    | `ns-process-data` Speed |
+| ------------------------------------------------------------------------------------------------- | -------------- | ----------------------------------------------- | ----------------------- |
+| 📷 [Images](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#images-and-video)   | Any            | [COLMAP](https://colmap.github.io/install.html) | 🐢                      |
+| 📹 [Video](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#images-and-video)    | Any            | [COLMAP](https://colmap.github.io/install.html) | 🐢                      |
+| 📱 [Polycam](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#polycam-capture)   | IOS with LiDAR | [Polycam App](https://poly.cam/)                | 🐇                      |
+| 📱 [KIRI Engine](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#kiri-capture)  | IOS or Android | [KIRI Engine App](https://www.kiriengine.com/)  | 🐇                      |
+| 📱 [Record3D](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#record3d-capture) | IOS with LiDAR | [Record3D app](https://record3d.app/)           | 🐇                      |
+| 🖥 [Metashape](https://docs.nerf.studio/en/latest/quickstart/custom_dataset.html#metashape)        | Any            | [Metashape](https://www.agisoft.com/)           | 🐇                      |
+| 🛠 [Custom](https://docs.nerf.studio/en/latest/quickstart/data_conventions.html)                   | Any            | Camera Poses                                    | 🐇                      |
 
 ## 5. Advanced Options
 
diff --git a/docs/quickstart/custom_dataset.md b/docs/quickstart/custom_dataset.md
index e883560d8..ea508a661 100644
--- a/docs/quickstart/custom_dataset.md
+++ b/docs/quickstart/custom_dataset.md
@@ -11,14 +11,14 @@ ns-process-data {video,images,polycam,insta360,record3d} --data {DATA_PATH} --ou
 A full set of arguments can be found {doc}`here</reference/cli/ns_process_data>`.
 
 We Currently support the following custom data types:
-| Data | Requirements | Preprocessing Speed |
-| -------- | ----------------------- | ------------------- |
-| 📷 [Images](images_and_video) | COLMAP | 🐢 |
-| 📹 [Video](images_and_video) | COLMAP | 🐢 |
-| 📱 [Polycam](polycam) | LiDAR iOS Device | 🐇 |
-| 📱 [Record3D](record3d) | LiDAR iOS Device | 🐇 |
-| 🖥 [Metashape](metashape) | | 🐢 |
-| 📷 Insta360 | 2 Sensor camera, COLMAP | 🐢 |
+| Data | Capture Device | Requirements | `ns-process-data` Speed |
+| ----------------------------- | -------------- | ----------------------------------------------- | ----------------------- |
+| 📷 [Images](images_and_video) | Any | [COLMAP](https://colmap.github.io/install.html) | 🐢 |
+| 📹 [Video](images_and_video) | Any | [COLMAP](https://colmap.github.io/install.html) | 🐢 |
+| 📱 [Polycam](polycam) | IOS with LiDAR | [Polycam App](https://poly.cam/) | 🐇 |
+| 📱 [KIRI Engine](kiri) | IOS or Android | [KIRI Engine App](https://www.kiriengine.com/) | 🐇 |
+| 📱 [Record3D](record3d) | IOS with LiDAR | [Record3D app](https://record3d.app/) | 🐇 |
+| 🖥 [Metashape](metashape) | Any | [Metashape](https://www.agisoft.com/) | 🐇 |
 
 (images_and_video)=
 
@@ -175,11 +175,58 @@ ns-process-data polycam --data {OUTPUT_FILE.zip} --output-dir {output directory}
 ns-train nerfacto --data {output directory}
 ```
 
+(kiri)=
+
+## KIRI Engine Capture
+
+Nerfstudio can trained from data processed by the [KIRI Engine app](https://www.kiriengine.com/). This works for both Android and iPhone and does not require a LiDAR supported device.
+
+:::{admonition} Note
+:class: info
+`ns-process-data` does not need to be run when using KIRI Engine.
+:::
+
+### Setting up KIRI Engine
+
+```{image} imgs/kiri_setup.png
+:width: 400
+:align: center
+:alt: KIRI Engine setup
+```
+
+After downloading the app, `Developer Mode` needs to be enabled. A toggle can be found in the settings menu.
+
+### Process data
+
+```{image} imgs/kiri_capture.png
+:width: 400
+:align: center
+:alt: KIRI Engine setup
+```
+
+1. Navigate to captures window.
+
+2. Select `Dev.` tab.
+
+3. Tap the `+` button to create a new capture.
+
+4. Choose `Camera pose` as the capture option
+
+5. Capture the scene and provide a name.
+
+6. After processing is complete, export the scene. It will be sent to your email.
+
+7. Unzip the file and run the training script (`ns-process-data` is not necessary).
+
+```
+ns-train nerfacto --data {kiri output directory}
+```
+
 (record3d)=
 
 ## Record3D Capture
 
-Nerfstudio can also be trained directly from >=iPhone 12 Pro captures from the [Record3D app](https://record3d.app/). This uses the iPhone's LiDAR sensors to calculate camera poses, so COLMAP is not needed.
+Nerfstudio can be trained directly from >=iPhone 12 Pro captures from the [Record3D app](https://record3d.app/). This uses the iPhone's LiDAR sensors to calculate camera poses, so COLMAP is not needed.
 
 Click on the image down below 👇 for a 1-minute tutorial on how to run nerfstudio with Record3D from start to finish.
 
diff --git a/docs/quickstart/imgs/kiri_capture.png b/docs/quickstart/imgs/kiri_capture.png
new file mode 100644
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HcmV?d00001


From 5630148c50c776fbf1fa16b69784408949697781 Mon Sep 17 00:00:00 2001
From: Alexander Kristoffersen <akristoffersen@berkeley.edu>
Date: Tue, 13 Dec 2022 23:04:17 -0800
Subject: [PATCH 19/24] Changed tinycudann to wheel to work with py3.8 (#1126)

Created using Colaboratory
---
 colab/demo.ipynb | 15 +++++++--------
 1 file changed, 7 insertions(+), 8 deletions(-)

diff --git a/colab/demo.ipynb b/colab/demo.ipynb
index 9609a6db4..148da3b88 100644
--- a/colab/demo.ipynb
+++ b/colab/demo.ipynb
@@ -7,7 +7,7 @@
         "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://colab.research.google.com/github/nerfstudio-project/nerfstudio/blob/alex%2Fcolab_38/colab/demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+        "<a href=\"https://colab.research.google.com/github/nerfstudio-project/nerfstudio/blob/alex%2Fcolab_py38_wheel/colab/demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -63,25 +63,25 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 1,
       "metadata": {
         "cellView": "form",
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "RGr33zHaHak0",
-        "outputId": "2641dce6-cd57-4d31-d8b1-860bc1adf17f"
+        "outputId": "6ad38334-22d2-4675-bffb-0bae91b17577"
       },
       "outputs": [
         {
-          "name": "stdout",
           "output_type": "stream",
+          "name": "stdout",
           "text": [
             "⏬ Downloading https://github.com/jaimergp/miniforge/releases/latest/download/Mambaforge-colab-Linux-x86_64.sh...\n",
             "📦 Installing...\n",
             "📌 Adjusting configuration...\n",
             "🩹 Patching environment...\n",
-            "⏲ Done in 0:00:27\n",
+            "⏲ Done in 0:00:18\n",
             "🔁 Restarting kernel...\n"
           ]
         }
@@ -111,9 +111,8 @@
         "\n",
         "# Installing TinyCuda\n",
         "%cd /content/\n",
-        "# !gdown \"https://drive.google.com/u/1/uc?id=1wglEFPbI4BjWMFYaKk7gHCNsWCZphKjs\" \n",
-        "# !pip install tinycudann-1.6-cp38-cp38-linux_x86_64.whl\n",
-        "!pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch\n",
+        "!gdown \"https://drive.google.com/u/0/uc?id=1mB3IxcpmTVmQN-So0t2lxjxbHvqWr2zf\" \n",
+        "!pip install tinycudann-1.5-cp38-cp38-linux_x86_64.whl\n",
         "\n",
         "# Installing COLMAP\n",
         "%cd /content/\n",

From d51718ec2bc411b6a0ac16d017f80ae96d3aceb0 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Wed, 14 Dec 2022 16:26:05 -0800
Subject: [PATCH 20/24] Immediately update viewer when output or cmap changes
 (#1131)

* Immediately update viewer when output or cmap changes

* lint
---
 nerfstudio/viewer/server/viewer_utils.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/nerfstudio/viewer/server/viewer_utils.py b/nerfstudio/viewer/server/viewer_utils.py
index ce70426f6..c3ebb950e 100644
--- a/nerfstudio/viewer/server/viewer_utils.py
+++ b/nerfstudio/viewer/server/viewer_utils.py
@@ -454,6 +454,19 @@ class ViewerState:
         else:
             self.prev_camera_matrix = camera_object["matrix"]
             self.camera_moving = True
+
+        output_type = self.vis["renderingState/output_choice"].read()
+        if output_type is None:
+            output_type = OutputTypes.INIT
+        if self.prev_output_type != output_type:
+            self.camera_moving = True
+
+        colormap_type = self.vis["renderingState/colormap_choice"].read()
+        if colormap_type is None:
+            colormap_type = ColormapTypes.INIT
+        if self.prev_colormap_type != colormap_type:
+            self.camera_moving = True
+
         return camera_object
 
     def _apply_colormap(self, outputs: Dict[str, Any], colors: torch.Tensor = None, eps=1e-6):

From bc690632bbffee4d21dd504985e13bca2510bf13 Mon Sep 17 00:00:00 2001
From: Penn <jenkspt@gmail.com>
Date: Thu, 15 Dec 2022 13:24:31 -0800
Subject: [PATCH 21/24] Use `torch.where` for faster contract (#1132)

use where for faster contract
---
 nerfstudio/field_components/spatial_distortions.py | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/nerfstudio/field_components/spatial_distortions.py b/nerfstudio/field_components/spatial_distortions.py
index 449f4b5b9..02da548a3 100644
--- a/nerfstudio/field_components/spatial_distortions.py
+++ b/nerfstudio/field_components/spatial_distortions.py
@@ -65,12 +65,8 @@ class SceneContraction(SpatialDistortion):
 
     def forward(self, positions):
         def contract(x):
-            mag = torch.linalg.norm(x, ord=self.order, dim=-1)
-            mask = mag >= 1
-            x_new = x.clone()
-            x_new[mask] = (2 - (1 / mag[mask][..., None])) * (x[mask] / mag[mask][..., None])
-
-            return x_new
+            mag = torch.linalg.norm(x, ord=self.order, dim=-1)[..., None]
+            return torch.where(mag < 1, x, (2 - (1 / mag)) * (x / mag))
 
         if isinstance(positions, Gaussians):
             means = contract(positions.mean.clone())

From 3da0ca727d560e264cfaa4425c8818fab62601bf Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Thu, 15 Dec 2022 14:18:23 -0800
Subject: [PATCH 22/24] Update render ui to use leva (#1133)

---
 nerfstudio/viewer/app/src/index.scss          |  29 +++-
 .../SidePanel/CameraPanel/CameraPanel.jsx     | 144 ++++--------------
 .../SidePanel/CameraPanel/CameraPropPanel.jsx |  73 +++++++++
 3 files changed, 124 insertions(+), 122 deletions(-)
 create mode 100644 nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPropPanel.jsx

diff --git a/nerfstudio/viewer/app/src/index.scss b/nerfstudio/viewer/app/src/index.scss
index 194c5ac2e..98e968795 100644
--- a/nerfstudio/viewer/app/src/index.scss
+++ b/nerfstudio/viewer/app/src/index.scss
@@ -242,18 +242,37 @@ $sidebar-width: 100% !default;
 // ------------------------------------
 // Camera Pane
 
-.CameraPanel {
+.CameraPanel-props {
+  margin-top: 10px;
+  margin-bottom: 10px;
+  margin-left: 20px;
+  margin-right: 20px;
+}
+
+.CameraPanel-path-row {
+  display: inline-block;
+  width: 45%;
+  margin-top: 8px;
+  margin-bottom: 8px;
+  margin-left: 4px;
+  margin-right: 4px;
+}
+
+.CameraPanel-row {
+  display: inline-block;
+  margin-top: 8px;
+  margin-bottom: 8px;
+  margin-left: 4px;
+  margin-right: 4px;
 }
 
 .CameraPanel-top-button {
-  display: inline-block;
-  margin: 4px;
-  margin-top: 8px;
+  width: 100%;
 }
 
 .CameraPanel-render-button {
   display: inline-block;
-  width: 70%;
+  width: 92%;
   margin: 4px;
   margin-top: 8px;
 }
diff --git a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
index 6a741d156..9958ea7b1 100644
--- a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
+++ b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPanel.jsx
@@ -37,6 +37,7 @@ import { useDispatch, useSelector } from 'react-redux';
 import { CSS2DObject } from 'three/examples/jsm/renderers/CSS2DRenderer';
 import AddAPhotoIcon from '@mui/icons-material/AddAPhoto';
 import FileDownloadOutlinedIcon from '@mui/icons-material/FileDownloadOutlined';
+import { LevaPanel, LevaStoreProvider, useCreateStore } from 'leva';
 import FileUploadOutlinedIcon from '@mui/icons-material/FileUploadOutlined';
 import { Stack } from '@mui/system';
 import TextField from '@mui/material/TextField';
@@ -46,6 +47,8 @@ import { CameraHelper } from './CameraHelper';
 import { get_curve_object_from_cameras, get_transform_matrix } from './curve';
 import { WebSocketContext } from '../../WebSocket/WebSocket';
 import RenderModal from '../../RenderModal';
+import CameraPropPanel from './CameraPropPanel';
+import LevaTheme from '../../../themes/leva_theme.json';
 
 const msgpack = require('msgpack-lite');
 
@@ -460,6 +463,9 @@ export default function CameraPanel(props) {
   const [animate, setAnimate] = React.useState(new Set());
   const [globalFov, setGlobalFov] = React.useState(DEFAULT_FOV);
 
+  // leva store
+  const cameraPropsStore = useCreateStore();
+
   const scene_state = sceneTree.get_scene_state();
 
   // Template for sharing state between Vanilla JS Three.js and React components
@@ -496,10 +502,6 @@ export default function CameraPanel(props) {
   };
 
   // ui state
-  const [ui_render_height, setUIRenderHeight] = React.useState(render_height);
-  const [ui_render_width, setUIRenderWidth] = React.useState(render_width);
-  const [ui_seconds, setUISeconds] = React.useState(seconds);
-  const [ui_fps, setUIfps] = React.useState(fps);
   const [fovLabel, setFovLabel] = React.useState(FOV_LABELS.FOV);
 
   // nonlinear render option
@@ -868,15 +870,10 @@ export default function CameraPanel(props) {
     const new_properties = new Map(cameraProperties);
 
     setRenderHeight(camera_path_object.render_height);
-    setUIRenderHeight(camera_path_object.render_height);
     setRenderWidth(camera_path_object.render_width);
-    setUIRenderWidth(camera_path_object.render_width);
 
     setFps(camera_path_object.fps);
-    setUIfps(camera_path_object.fps);
-
     setSeconds(camera_path_object.seconds);
-    setUISeconds(camera_path_object.seconds);
 
     set_smoothness_value(camera_path_object.smoothness_value);
     setIsCycle(camera_path_object.is_cycle);
@@ -968,7 +965,7 @@ export default function CameraPanel(props) {
   return (
     <div className="CameraPanel">
       <div>
-        <div className="CameraPanel-top-button">
+        <div className="CameraPanel-path-row">
           <Button
             size="small"
             className="CameraPanel-top-button"
@@ -986,7 +983,7 @@ export default function CameraPanel(props) {
             />
           </Button>
         </div>
-        <div className="CameraPanel-top-button">
+        <div className="CameraPanel-path-row">
           <Button
             size="small"
             className="CameraPanel-top-button"
@@ -1009,110 +1006,23 @@ export default function CameraPanel(props) {
           Render
         </Button>
       </div>
-      <div className="CameraList-row-time-interval">
-        <TextField
-          label="Height"
-          inputProps={{
-            inputMode: 'numeric',
-            pattern: '[+-]?([0-9]*[.])?[0-9]+',
-          }}
-          size="small"
-          onChange={(e) => {
-            if (e.target.validity.valid) {
-              setUIRenderHeight(e.target.value);
-            }
-          }}
-          onBlur={(e) => {
-            if (e.target.validity.valid) {
-              if (e.target.value !== '') {
-                setRenderHeight(parseInt(e.target.value, 10));
-              } else {
-                setUIRenderHeight(render_height);
-              }
-            }
-          }}
-          value={ui_render_height}
-          error={ui_render_height <= 0}
-          helperText={ui_render_height <= 0 ? 'Required' : ''}
-          variant="standard"
-        />
-        <TextField
-          label="Width"
-          inputProps={{
-            inputMode: 'numeric',
-            pattern: '[+-]?([0-9]*[.])?[0-9]+',
-          }}
-          size="small"
-          onChange={(e) => {
-            if (e.target.validity.valid) {
-              setUIRenderWidth(e.target.value);
-            }
-          }}
-          onBlur={(e) => {
-            if (e.target.validity.valid) {
-              if (e.target.value !== '') {
-                setRenderWidth(parseInt(e.target.value, 10));
-              } else {
-                setUIRenderWidth(render_width);
-              }
-            }
-          }}
-          value={ui_render_width}
-          error={ui_render_width <= 0}
-          helperText={ui_render_width <= 0 ? 'Required' : ''}
-          variant="standard"
-        />
-      </div>
-      <div className="CameraList-row-time-interval">
-        <TextField
-          label="Seconds"
-          inputProps={{
-            inputMode: 'numeric',
-            pattern: '[+-]?([0-9]*[.])?[0-9]+',
-          }}
-          size="small"
-          onChange={(e) => {
-            if (e.target.validity.valid) {
-              setUISeconds(e.target.value);
-            }
-          }}
-          onBlur={(e) => {
-            if (e.target.validity.valid) {
-              if (e.target.value !== '') {
-                setSeconds(parseInt(e.target.value, 10));
-              } else {
-                setUISeconds(seconds);
-              }
-            }
-          }}
-          value={ui_seconds}
-          error={ui_seconds <= 0}
-          helperText={ui_seconds <= 0 ? 'Required' : ''}
-          variant="standard"
-        />
-        <TextField
-          label="FPS"
-          inputProps={{ inputMode: 'numeric', pattern: '[0-9]*' }}
-          size="small"
-          onChange={(e) => {
-            if (e.target.validity.valid) {
-              setUIfps(e.target.value);
-            }
-          }}
-          onBlur={(e) => {
-            if (e.target.validity.valid) {
-              if (e.target.value !== '') {
-                setFps(parseInt(e.target.value, 10));
-              } else {
-                setUIfps(fps);
-              }
-            }
-          }}
-          value={ui_fps}
-          error={ui_fps <= 0}
-          helperText={ui_fps <= 0 ? 'Required' : ''}
-          variant="standard"
+      <div className="CameraPanel-props">
+        <LevaPanel
+          store={cameraPropsStore}
+          className="Leva-panel"
+          theme={LevaTheme}
+          titleBar={false}
+          fill
+          flat
         />
+        <LevaStoreProvider store={cameraPropsStore}>
+          <CameraPropPanel
+            seconds={seconds}
+            set_seconds={setSeconds}
+            fps={fps}
+            set_fps={setFps}
+          />
+        </LevaStoreProvider>
       </div>
       <div className="CameraList-row-animation-properties">
         <Tooltip title="Animate FOV for Each Camera">
@@ -1161,7 +1071,7 @@ export default function CameraPanel(props) {
         />
       </div>
       <div>
-        <div className="CameraPanel-top-button">
+        <div className="CameraPanel-row">
           <Button
             size="small"
             variant="outlined"
@@ -1171,7 +1081,7 @@ export default function CameraPanel(props) {
             Add Camera
           </Button>
         </div>
-        <div className="CameraPanel-top-button">
+        <div className="CameraPanel-row">
           <Tooltip
             className="curve-button"
             title="Toggle looping camera spline"
@@ -1199,7 +1109,7 @@ export default function CameraPanel(props) {
             )}
           </Tooltip>
         </div>
-        <div className="CameraPanel-top-button">
+        <div className="CameraPanel-row">
           <Tooltip title="Reset Keyframe Timing">
             <Button
               size="small"
diff --git a/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPropPanel.jsx b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPropPanel.jsx
new file mode 100644
index 000000000..841af65bd
--- /dev/null
+++ b/nerfstudio/viewer/app/src/modules/SidePanel/CameraPanel/CameraPropPanel.jsx
@@ -0,0 +1,73 @@
+import { useControls, useStoreContext } from 'leva';
+import { useDispatch, useSelector } from 'react-redux';
+
+export default function CameraPropPanel(props) {
+  const seconds = props.seconds;
+  const set_seconds = props.set_seconds;
+  const fps = props.fps;
+  const set_fps = props.set_fps;
+
+  const store = useStoreContext();
+
+  const dispatch = useDispatch();
+
+  // redux store state
+  const render_height = useSelector(
+    (state) => state.renderingState.render_height,
+  );
+  const render_width = useSelector(
+    (state) => state.renderingState.render_width,
+  );
+
+  const setResolution = (value) => {
+    dispatch({
+      type: 'write',
+      path: 'renderingState/render_width',
+      data: value.width,
+    });
+    dispatch({
+      type: 'write',
+      path: 'renderingState/render_height',
+      data: value.height,
+    });
+  };
+
+  const [, setControls] = useControls(
+    () => ({
+      camera_resolution: {
+        label: 'Resolution',
+        value: { width: render_width, height: render_height },
+        joystick: false,
+        onChange: (v) => {
+          setResolution(v);
+        },
+      },
+      video_duration: {
+        label: 'Duration (Sec)',
+        value: seconds,
+        min: 0.1,
+        step: 0.1,
+        onChange: (v) => {
+          set_seconds(v);
+        },
+      },
+      video_fps: {
+        label: 'Framerate (FPS)',
+        value: fps,
+        min: 0.1,
+        onChange: (v) => {
+          set_fps(v);
+        },
+      },
+    }),
+    { store },
+  );
+
+  setControls({ video_fps: fps });
+  setControls({ video_duration: seconds });
+  setControls({
+    camera_resolution: { width: render_width, height: render_height },
+  });
+
+  return null;
+}

From 67cd746de3b15fa656016fd124b1b5f37a584624 Mon Sep 17 00:00:00 2001
From: Matthew Tancik <tancik@berkeley.edu>
Date: Thu, 15 Dec 2022 16:14:13 -0800
Subject: [PATCH 23/24] Update Render View logic (#1134)

---
 nerfstudio/viewer/app/src/index.scss          |  5 ++-
 .../app/src/modules/SidePanel/SidePanel.jsx   | 18 +++++++++-
 .../SidePanel/StatusPanel/StatusPanel.jsx     | 29 +++++++++-------
 .../src/modules/ViewerWindow/ViewerWindow.jsx | 33 ++++++++++++-------
 nerfstudio/viewer/app/src/themes/theme.ts     |  9 +++--
 5 files changed, 66 insertions(+), 28 deletions(-)

diff --git a/nerfstudio/viewer/app/src/index.scss b/nerfstudio/viewer/app/src/index.scss
index 98e968795..fab8b8a68 100644
--- a/nerfstudio/viewer/app/src/index.scss
+++ b/nerfstudio/viewer/app/src/index.scss
@@ -137,7 +137,10 @@ $sidebar-width: 100% !default;
 }
 
 .StatusPanel .StatusPanel-hide-scene-button {
-  margin: 12px;
+  margin-top: 4px;
+  margin-bottom: 4px;
+  margin-left: 6px;
+  margin-right: 6px;
 }
 
 .StatusPanel .WebSocketUrlField {
diff --git a/nerfstudio/viewer/app/src/modules/SidePanel/SidePanel.jsx b/nerfstudio/viewer/app/src/modules/SidePanel/SidePanel.jsx
index dff6e70b9..35dd126d6 100644
--- a/nerfstudio/viewer/app/src/modules/SidePanel/SidePanel.jsx
+++ b/nerfstudio/viewer/app/src/modules/SidePanel/SidePanel.jsx
@@ -15,6 +15,7 @@ import {
   WidgetsRounded,
   ImportExportRounded,
 } from '@mui/icons-material/';
+import { useSelector } from 'react-redux';
 import StatusPanel from './StatusPanel';
 import LevaTheme from '../../themes/leva_theme.json';
 import CameraPanel from './CameraPanel';
@@ -84,6 +85,15 @@ export function BasicTabs(props: BasicTabsProps) {
     setValue(newValue);
     setShowExportBox(newValue === 3);
   };
+  const camera_choice = useSelector(
+    (state) => state.renderingState.camera_choice,
+  );
+
+  React.useEffect(() => {
+    if (camera_choice === 'Render Camera') {
+      setValue(1);
+    }
+  }, [camera_choice]);
 
   return (
     <div>
@@ -99,10 +109,16 @@ export function BasicTabs(props: BasicTabsProps) {
           >
             <Tab icon={<TuneRounded />} label="Controls" {...a11yProps(0)} />
             <Tab icon={<CameraAltRounded />} label="Render" {...a11yProps(1)} />
-            <Tab icon={<WidgetsRounded />} label="Scene" {...a11yProps(2)} />
+            <Tab
+              icon={<WidgetsRounded />}
+              label="Scene"
+              disabled={camera_choice === 'Render Camera'}
+              {...a11yProps(2)}
+            />
             <Tab
               icon={<ImportExportRounded />}
               label="Export"
+              disabled={camera_choice === 'Render Camera'}
               {...a11yProps(3)}
             />
           </Tabs>
diff --git a/nerfstudio/viewer/app/src/modules/SidePanel/StatusPanel/StatusPanel.jsx b/nerfstudio/viewer/app/src/modules/SidePanel/StatusPanel/StatusPanel.jsx
index 8db09c71f..80a1c38ab 100644
--- a/nerfstudio/viewer/app/src/modules/SidePanel/StatusPanel/StatusPanel.jsx
+++ b/nerfstudio/viewer/app/src/modules/SidePanel/StatusPanel/StatusPanel.jsx
@@ -6,6 +6,7 @@ import { useDispatch, useSelector } from 'react-redux';
 import PauseIcon from '@mui/icons-material/Pause';
 import PlayArrowIcon from '@mui/icons-material/PlayArrow';
 import ViewInArIcon from '@mui/icons-material/ViewInAr';
+import ImageOutlinedIcon from '@mui/icons-material/ImageOutlined';
 
 import { WebSocketContext } from '../../WebSocket/WebSocket';
 
@@ -31,28 +32,30 @@ export default function StatusPanel(props: StatusPanelProps) {
   const vis_train_ratio = useSelector(
     (state) => state.renderingState.vis_train_ratio,
   );
+  const camera_choice = useSelector(
+    (state) => state.renderingState.camera_choice,
+  );
 
   // logic for toggling visibility of the entire scene and just the training images
-  const [is_scene_visible, set_is_scene_visible] = React.useState(1);
-  const [is_images_visible, set_is_images_visible] = React.useState(1);
+  const [is_scene_visible, set_is_scene_visible] = React.useState(true);
+  const [is_images_visible, set_is_images_visible] = React.useState(true);
   const scene_button = is_scene_visible ? 'Hide Scene' : 'Show Scene';
   const cameras_button = is_images_visible ? 'Hide Images' : 'Show Images';
-  sceneTree.object.visible = is_scene_visible;
+  sceneTree.object.visible =
+    is_scene_visible && camera_choice === 'Main Camera';
   if (sceneTree.find_no_create(['Training Cameras']) !== null) {
     sceneTree.find_no_create(['Training Cameras']).object.visible =
       is_images_visible;
   }
 
   React.useEffect(() => {
-    sceneTree.object.traverse(
-      (obj) => {
-        if (obj.name === 'CAMERA_LABEL') {
-          // eslint-disable-next-line no-param-reassign
-          obj.visible = is_scene_visible;
-        }
+    sceneTree.object.traverse((obj) => {
+      if (obj.name === 'CAMERA_LABEL') {
+        // eslint-disable-next-line no-param-reassign
+        obj.visible = is_scene_visible && camera_choice === 'Main Camera';
       }
-    );
-  }, [is_scene_visible]);
+    });
+  }, [camera_choice, is_scene_visible]);
 
   const handlePlayChange = () => {
     dispatch({
@@ -105,6 +108,7 @@ export default function StatusPanel(props: StatusPanelProps) {
         }}
         style={{ textTransform: 'none' }}
         startIcon={<ViewInArIcon />}
+        disabled={camera_choice === 'Render Camera'}
       >
         {scene_button}
       </Button>
@@ -115,7 +119,8 @@ export default function StatusPanel(props: StatusPanelProps) {
           set_is_images_visible(!is_images_visible);
         }}
         style={{ textTransform: 'none' }}
-        startIcon={<ViewInArIcon />}
+        startIcon={<ImageOutlinedIcon />}
+        disabled={camera_choice === 'Render Camera'}
       >
         {cameras_button}
       </Button>
diff --git a/nerfstudio/viewer/app/src/modules/ViewerWindow/ViewerWindow.jsx b/nerfstudio/viewer/app/src/modules/ViewerWindow/ViewerWindow.jsx
index 90fe975e0..94990f2d9 100644
--- a/nerfstudio/viewer/app/src/modules/ViewerWindow/ViewerWindow.jsx
+++ b/nerfstudio/viewer/app/src/modules/ViewerWindow/ViewerWindow.jsx
@@ -9,6 +9,8 @@ import OpenWithIcon from '@mui/icons-material/OpenWith';
 import PublicOffSharpIcon from '@mui/icons-material/PublicOffSharp';
 import PublicSharpIcon from '@mui/icons-material/PublicSharp';
 import SyncOutlinedIcon from '@mui/icons-material/SyncOutlined';
+import ThreeDRotationIcon from '@mui/icons-material/ThreeDRotation';
+import VideoCameraBackIcon from '@mui/icons-material/VideoCameraBackOutlined';
 import WebRtcWindow from '../WebRtcWindow/WebRtcWindow';
 import { WebSocketContext } from '../WebSocket/WebSocket';
 
@@ -19,27 +21,36 @@ function CameraToggle() {
   const camera_choice = useSelector(
     (state) => state.renderingState.camera_choice,
   );
-  const set_camera_choice = (event: SelectChangeEvent) => {
-    const value = event.target.value;
-    dispatch({
-      type: 'write',
-      path: 'renderingState/camera_choice',
-      data: value,
-    });
+  const set_camera_choice = (event: SelectChangeEvent, value: string[]) => {
+    if (value != null) {
+      dispatch({
+        type: 'write',
+        path: 'renderingState/camera_choice',
+        data: value,
+      });
+    }
   };
 
   return (
     <ToggleButtonGroup
-      color="primary"
       value={camera_choice}
       exclusive
       onChange={set_camera_choice}
       aria-label="camera view"
       size="small"
-      varient="filled"
     >
-      <ToggleButton value="Main Camera">Viewport</ToggleButton>
-      <ToggleButton value="Render Camera">Render View</ToggleButton>
+      <ToggleButton value="Main Camera" disableRipple sx={{ width: '160px' }}>
+        <ThreeDRotationIcon fontSize="small" sx={{ mr: 1, ml: -0.5 }} />
+        Viewport
+      </ToggleButton>
+      <ToggleButton value="Render Camera" disableRipple sx={{ width: '160px' }}>
+        <VideoCameraBackIcon
+          value="Render Camera"
+          fontSize="small"
+          sx={{ mr: 1, ml: 0.5 }}
+        />
+        Render View
+      </ToggleButton>
     </ToggleButtonGroup>
   );
 }
diff --git a/nerfstudio/viewer/app/src/themes/theme.ts b/nerfstudio/viewer/app/src/themes/theme.ts
index 554445561..4a973209e 100644
--- a/nerfstudio/viewer/app/src/themes/theme.ts
+++ b/nerfstudio/viewer/app/src/themes/theme.ts
@@ -126,10 +126,13 @@ export const appTheme = createTheme({
       styleOverrides: {
         root: {
           color: '#eeeeee',
-          backgroundColor: '#393e46',
+          backgroundColor: 'FFD369',
           '&.Mui-selected': {
-            color: '#FFD369',
-            backgroundColor: '#555555',
+            color: '#222831',
+            backgroundColor: '#FFD369',
+            ':hover': {
+              backgroundColor: '#FFD369',
+            },
           },
           '&.Mui-disabled': {
             color: '#999999',

From 3bf490e845897a74db278e027f085967758082a2 Mon Sep 17 00:00:00 2001
From: Ethan Weber <ethanweber@berkeley.edu>
Date: Thu, 15 Dec 2022 17:29:41 -0800
Subject: [PATCH 24/24] adding data subset (#1135)

* adding nerfstudio-dataset

* removed file
---
 scripts/downloads/download_data.py | 68 +++++++++++++++++++++++++-----
 1 file changed, 58 insertions(+), 10 deletions(-)

diff --git a/scripts/downloads/download_data.py b/scripts/downloads/download_data.py
index c444991a9..12a0a0227 100755
--- a/scripts/downloads/download_data.py
+++ b/scripts/downloads/download_data.py
@@ -15,6 +15,7 @@ from rich.console import Console
 from typing_extensions import Annotated
 
 from nerfstudio.configs.base_config import PrintableConfig
+from nerfstudio.utils.scripts import run_command
 
 CONSOLE = Console(width=120)
 
@@ -84,17 +85,39 @@ def grab_file_id(zip_url: str) -> str:
     return s.split("/")[0]
 
 
+nerfstudio_dataset = [
+    "Egypt",
+    "person",
+    "kitchen",
+    "plane",
+    "dozer",
+    "floating-tree",
+    "aspen",
+    "stump",
+    "sculpture",
+    "Giannini-Hall",
+]
 nerfstudio_file_ids = {
     "bww_entrance": grab_file_id("https://drive.google.com/file/d/1ylkRHtfB3n3IRLf2wplpfxzPTq7nES9I/view?usp=sharing"),
     "campanile": grab_file_id("https://drive.google.com/file/d/13aOfGJRRH05pOOk9ikYGTwqFc2L1xskU/view?usp=sharing"),
     "desolation": grab_file_id("https://drive.google.com/file/d/14IzOOQm9KBJ3kPbunQbUTHPnXnmZus-f/view?usp=sharing"),
-    "dozer": grab_file_id("https://drive.google.com/file/d/1-OR5F_V5S4s-yzxohbwTylaXjzYLu8ZR/view?usp=sharing"),
     "library": grab_file_id("https://drive.google.com/file/d/1Hjbh_-BuaWETQExn2x2qGD74UwrFugHx/view?usp=sharing"),
     "poster": grab_file_id("https://drive.google.com/file/d/1dmjWGXlJnUxwosN6MVooCDQe970PkD-1/view?usp=sharing"),
     "redwoods2": grab_file_id("https://drive.google.com/file/d/1rg-4NoXT8p6vkmbWxMOY6PSG4j3rfcJ8/view?usp=sharing"),
     "storefront": grab_file_id("https://drive.google.com/file/d/16b792AguPZWDA_YC4igKCwXJqW0Tb21o/view?usp=sharing"),
     "vegetation": grab_file_id("https://drive.google.com/file/d/1wBhLQ2odycrtU39y2akVurXEAt9SsVI3/view?usp=sharing"),
+    "Egypt": "https://data.nerf.studio/nerfstudio/Egypt.zip",
+    "person": "https://data.nerf.studio/nerfstudio/person.zip",
+    "kitchen": "https://data.nerf.studio/nerfstudio/kitchen.zip",
+    "plane": "https://data.nerf.studio/nerfstudio/plane.zip",
+    "dozer": "https://data.nerf.studio/nerfstudio/dozer.zip",
+    "floating-tree": "https://data.nerf.studio/nerfstudio/floating-tree.zip",
+    "aspen": "https://data.nerf.studio/nerfstudio/aspen.zip",
+    "stump": "https://data.nerf.studio/nerfstudio/stump.zip",
+    "sculpture": "https://data.nerf.studio/nerfstudio/sculpture.zip",
+    "Giannini-Hall": "https://data.nerf.studio/nerfstudio/Giannini-Hall.zip",
     "all": None,
+    "nerfstudio-dataset": nerfstudio_dataset,
 }
 
 NerfstudioCaptureName = tyro.extras.literal_type_from_choices(nerfstudio_file_ids.keys())
@@ -103,14 +126,33 @@ NerfstudioCaptureName = tyro.extras.literal_type_from_choices(nerfstudio_file_id
 def download_capture_name(save_dir: Path, dataset_name: str, capture_name: str, capture_name_to_file_id: dict):
     """Download specific captures a given dataset and capture name."""
 
-    url = f"https://drive.google.com/uc?id={capture_name_to_file_id[capture_name]}"
-    target_path = str(save_dir / f"{dataset_name}/{capture_name}")
-    os.makedirs(target_path, exist_ok=True)
-    download_path = Path(f"{target_path}.zip")
-    tmp_path = str(save_dir / ".temp")
-    shutil.rmtree(tmp_path, ignore_errors=True)
-    os.makedirs(tmp_path, exist_ok=True)
-    gdown.download(url, output=str(download_path))
+    file_id_or_zip_url = capture_name_to_file_id[capture_name]
+    if file_id_or_zip_url.endswith(".zip"):
+        url = file_id_or_zip_url  # zip url
+        target_path = str(save_dir / f"{dataset_name}/{capture_name}")
+        os.makedirs(target_path, exist_ok=True)
+        download_path = Path(f"{target_path}.zip")
+        tmp_path = str(save_dir / ".temp")
+        shutil.rmtree(tmp_path, ignore_errors=True)
+        os.makedirs(tmp_path, exist_ok=True)
+        try:
+            os.remove(download_path)
+        except OSError:
+            pass
+        run_command(f"wget {url} -O {download_path}", verbose=True)
+    else:
+        url = f"https://drive.google.com/uc?id={file_id_or_zip_url}"  # file id
+        target_path = str(save_dir / f"{dataset_name}/{capture_name}")
+        os.makedirs(target_path, exist_ok=True)
+        download_path = Path(f"{target_path}.zip")
+        tmp_path = str(save_dir / ".temp")
+        shutil.rmtree(tmp_path, ignore_errors=True)
+        os.makedirs(tmp_path, exist_ok=True)
+        try:
+            os.remove(download_path)
+        except OSError:
+            pass
+        gdown.download(url, output=str(download_path))
     with zipfile.ZipFile(download_path, "r") as zip_ref:
         zip_ref.extractall(tmp_path)
     inner_folders = os.listdir(tmp_path)
@@ -132,7 +174,13 @@ class NerfstudioDownload(DatasetDownload):
         """Download the nerfstudio dataset."""
         if self.capture_name == "all":
             for capture_name in nerfstudio_file_ids:
-                if capture_name != "all":
+                if capture_name not in ("all", "nerfstudio-dataset"):
+                    download_capture_name(save_dir, "nerfstudio", capture_name, nerfstudio_file_ids)
+            return
+
+        if self.capture_name == "nerfstudio-dataset":
+            for capture_name in nerfstudio_dataset:
+                if capture_name not in ("all", "nerfstudio-dataset"):
                     download_capture_name(save_dir, "nerfstudio", capture_name, nerfstudio_file_ids)
             return