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Repository: nianticlabs/mvsanywhere
Branch: main
Commit: 52534320dd6a
Files: 197
Total size: 112.7 MB
Directory structure:
gitextract_knu0jtpw/
├── .gitignore
├── LICENSE
├── Makefile
├── README.md
├── configs/
│ ├── data/
│ │ ├── blendedmvg/
│ │ │ ├── blendedmvg_default_train.yaml
│ │ │ └── blendedmvg_default_val.yaml
│ │ ├── colmap/
│ │ │ └── colmap_empty.yaml
│ │ ├── demo/
│ │ │ ├── demo_colmap.yaml
│ │ │ └── demo_nerf_capture.yaml
│ │ ├── dynamic_replica/
│ │ │ ├── dynamic_replica_default_test.yaml
│ │ │ ├── dynamic_replica_default_train.yaml
│ │ │ └── dynamic_replica_default_val.yaml
│ │ ├── hypersim/
│ │ │ ├── hypersim_default_test.yaml
│ │ │ ├── hypersim_default_train.yaml
│ │ │ └── hypersim_default_val.yaml
│ │ ├── matrix_city/
│ │ │ ├── matrix_city_default_train.yaml
│ │ │ └── matrix_city_default_val.yaml
│ │ ├── mvssynth/
│ │ │ ├── mvssynth_default_train.yaml
│ │ │ └── mvssynth_default_val.yaml
│ │ ├── nerfstudio/
│ │ │ └── nerfstudio_empty.yaml
│ │ ├── sailvos3d/
│ │ │ └── sailvos3d_default_train.yaml
│ │ ├── scannet/
│ │ │ ├── scannet_default_test.yaml
│ │ │ ├── scannet_default_train.yaml
│ │ │ ├── scannet_default_train_inference_style.yaml
│ │ │ ├── scannet_default_train_ray.yaml
│ │ │ ├── scannet_default_val.yaml
│ │ │ ├── scannet_default_val_inference_style.yaml
│ │ │ ├── scannet_dense_test.yaml
│ │ │ └── scannet_dense_val.yaml
│ │ ├── tartanair/
│ │ │ ├── tartanair_default_train.yaml
│ │ │ └── tartanair_default_val.yaml
│ │ ├── vdr/
│ │ │ ├── vdr_default.yaml
│ │ │ ├── vdr_dense.yaml
│ │ │ └── vdr_dense_offline.yaml
│ │ └── vkitti/
│ │ └── vkitti_default_train.yaml
│ └── models/
│ ├── mvsanywhere_dot_model.yaml
│ ├── mvsanywhere_model.yaml
│ └── simplerecon_model.yaml
├── data_splits/
│ ├── ScanNetv2/
│ │ ├── dvmvs_split/
│ │ │ ├── dvmvs_train.txt
│ │ │ ├── dvmvs_val.txt
│ │ │ ├── test_eight_view_deepvmvs.txt
│ │ │ └── test_eight_view_deepvmvs_dense.txt
│ │ └── standard_split/
│ │ ├── scannetv2_test.txt
│ │ ├── scannetv2_test_planes.txt
│ │ ├── scannetv2_train.txt
│ │ ├── scannetv2_val.txt
│ │ ├── test_eight_view_deepvmvs.txt
│ │ ├── test_eight_view_deepvmvs_dense.txt
│ │ ├── test_eight_view_deepvmvs_offline.txt
│ │ ├── test_planes_eight_view_deepvmvs.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ ├── train_test_eight_view_deepvmvs.txt
│ │ ├── val_eight_view_deepvmvs.txt
│ │ └── val_test_eight_view_deepvmvs.txt
│ ├── blendedmvg/
│ │ ├── blendedmvg_train.txt
│ │ ├── blendedmvg_val.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ └── val_eight_view_deepvmvs.txt
│ ├── dynamic_replica/
│ │ ├── dynamic_replica_test.txt
│ │ ├── dynamic_replica_train.txt
│ │ ├── dynamic_replica_val.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ └── val_eight_view_deepvmvs.txt
│ ├── hypersim/
│ │ ├── bd_split/
│ │ │ ├── train_clean_eight_view_deepvmvs_bd.txt
│ │ │ ├── train_eight_view_deepvmvs_bd.txt
│ │ │ ├── train_files_bd.json
│ │ │ ├── train_files_mean_10_m_no_bad_scenes.txt
│ │ │ ├── val_clean_eight_view_deepvmvs_bd.txt
│ │ │ ├── val_eight_view_deepvmvs_bd.txt
│ │ │ ├── val_files_bd.json
│ │ │ └── val_files_mean_10_m_no_bad_scenes.txt
│ │ └── standard_split/
│ │ ├── test_files_all.json
│ │ ├── train_files_all.json
│ │ └── val_files_all.json
│ ├── matrix_city/
│ │ ├── matrix_city_train.json
│ │ ├── matrix_city_train.txt
│ │ ├── matrix_city_val.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ └── val_eight_view_deepvmvs.txt
│ ├── mvssynth/
│ │ ├── train_eight_view_deepvmvs.txt
│ │ ├── train_scans.txt
│ │ ├── val_eight_view_deepvmvs.txt
│ │ └── val_scans.txt
│ ├── sailvos3d/
│ │ ├── split_train.txt
│ │ └── train_eight_view_deepvmvs.txt
│ ├── tartanair/
│ │ ├── all_scans.txt
│ │ ├── train_eight_view_deepvmvs_bd.txt
│ │ ├── train_scans.txt
│ │ ├── val_eight_view_deepvmvs_bd.txt
│ │ └── val_scans.txt
│ ├── vdr/
│ │ ├── scans.txt
│ │ ├── test_eight_view_deepvmvs.txt
│ │ ├── test_eight_view_deepvmvs_dense.txt
│ │ └── test_eight_view_deepvmvs_dense_offline.txt
│ └── vkitti/
│ ├── matrix_city_train.json
│ ├── train_eight_view_deepvmvs.txt
│ └── vkitti_train.txt
├── demo_assets/
│ └── cameras.npy
├── environment.yml
├── eval.py
├── hubconf.py
├── pyproject.toml
├── scripts/
│ ├── create_visibility_volume.py
│ ├── data_scripts/
│ │ ├── filter_hypersim_scenes.py
│ │ ├── fix_nerfcapture_filenames.py
│ │ ├── generate_blendedmvg_tuples.py
│ │ ├── generate_hypersim_planar_depths.py
│ │ ├── generate_matrix_scans.py
│ │ ├── generate_test_tuples.py
│ │ ├── generate_train_tuples.py
│ │ ├── generate_train_tuples_geometry.py
│ │ ├── precompute_valid_frames.py
│ │ ├── scannet_wrangling_scripts/
│ │ │ ├── LICENSE
│ │ │ ├── README.md
│ │ │ ├── SensorData.py
│ │ │ ├── download_scannet.py
│ │ │ ├── env.yml
│ │ │ ├── reader.py
│ │ │ └── splits/
│ │ │ ├── scannetv2_test.txt
│ │ │ ├── scannetv2_train.txt
│ │ │ └── scannetv2_val.txt
│ │ └── undistort_nerfstudio_data.py
│ ├── dust3r_waymo_preprocess.py
│ ├── evals/
│ │ └── mesh_eval.py
│ ├── evaluation.py
│ ├── render_scripts/
│ │ └── render_meshes.py
│ └── strip_checkpoint.py
├── setup.py
├── simple_demo.py
└── src/
├── mvsanywhere/
│ ├── datasets/
│ │ ├── __init__.py
│ │ ├── blendedmvg.py
│ │ ├── change_of_basis.py
│ │ ├── colmap_dataset.py
│ │ ├── dynamic_replica.py
│ │ ├── generic_mvs_dataset.py
│ │ ├── hypersim.py
│ │ ├── matrix_city.py
│ │ ├── mvssynth.py
│ │ ├── nerf_dataset.py
│ │ ├── nerfstudio_dataset.py
│ │ ├── read_write_colmap_model.py
│ │ ├── sailvos3d.py
│ │ ├── scannet_dataset.py
│ │ ├── tartanair.py
│ │ ├── vdr_dataset.py
│ │ └── vkitti.py
│ ├── experiment_modules/
│ │ ├── rmvd_mvsa.py
│ │ └── sr_depth_model.py
│ ├── losses.py
│ ├── modules/
│ │ ├── cost_volume.py
│ │ ├── depth_anything_blocks.py
│ │ ├── feature_volume.py
│ │ ├── layers.py
│ │ ├── networks.py
│ │ ├── networks_fast.py
│ │ ├── view_agnostic_feature_volume.py
│ │ └── vit_modules.py
│ ├── options.py
│ ├── run_demo.py
│ ├── test.py
│ ├── test_rmvd.py
│ ├── tools/
│ │ ├── fusers_helper.py
│ │ ├── keyframe_buffer.py
│ │ ├── marching_cubes/
│ │ │ ├── ext.cpp
│ │ │ ├── marching_cubes.cu
│ │ │ ├── marching_cubes.h
│ │ │ ├── marching_cubes_cpu.cpp
│ │ │ ├── marching_cubes_utils.h
│ │ │ ├── pytorch3d_cutils.h
│ │ │ └── tables.h
│ │ ├── mesh_renderer.py
│ │ ├── partial_fuser.py
│ │ ├── tsdf.py
│ │ └── tuple_generator.py
│ ├── train.py
│ └── utils/
│ ├── augmentation_utils.py
│ ├── cropping_utils.py
│ ├── dataset_utils.py
│ ├── generic_utils.py
│ ├── geometry_utils.py
│ ├── metrics_utils.py
│ ├── model_utils.py
│ ├── pytorch3d_extras.py
│ ├── rendering_utils.py
│ ├── visualization_utils.py
│ └── volume_utils.py
└── regsplatfacto/
├── pyproject.toml
└── regsplatfacto/
├── __init__.py
├── data/
│ ├── __init__.py
│ ├── mvsanywhere_dataset.py
│ ├── py.typed
│ └── regsplatfacto_datamanager.py
├── meshing.py
├── regsplatfacto_config.py
├── regsplatfacto_model.py
├── render_for_meshing.py
└── utils.py
================================================
FILE CONTENTS
================================================
================================================
FILE: .gitignore
================================================
*.pyc
.vscode/
debug_scripts/
debug_dump
logs/
logs
models/*.ckpt
weights/*.ckpt
**__pycache__**
logs
results
.mypy_cache
*.egg-info/
*.egg
weights
outputs
================================================
FILE: LICENSE
================================================
Copyright © Niantic, Inc. 2025. Patent Pending.
All rights reserved.
================================================================================
This Software is licensed under the terms of the following MVSAnywhere license
which allows for non-commercial use only. For any other use of the software not
covered by the terms of this license, please contact partnerships@nianticlabs.com
================================================================================
DoubleTake License
This Agreement is made by and between the Licensor and the Licensee as
defined and identified below.
1. Definitions.
In this Agreement (“the Agreement”) the following words shall have the
following meanings:
"Authors" shall mean S. Izquierdo, M. Sayed, M. Firman, G. Garcia-Hernando,
D. Turmukhambetov, J. Civera, O. Mac Aodha, G. Brostow, and J. Watson
"Licensee" Shall mean the person or organization agreeing to use the
Software in accordance with these terms and conditions.
"Licensor" shall mean Niantic Inc., a company organized and existing under
the laws of Delaware, whose principal place of business is at 1 Ferry Building,
Suite 200, San Francisco, 94111.
"Software" shall mean the MVSAnywhere Software uploaded by Licensor to the
GitHub repository at https://github.com/nianticlabs/mvsanywhere
on April 25th 2025 in source code or object code form and any
accompanying documentation as well as any modifications or additions uploaded
to the same GitHub repository by Licensor.
2. License.
2.1 The Licensor has all necessary rights to grant a license under: (i)
copyright and rights in the nature of copyright subsisting in the Software; and
(ii) certain patent rights resulting from a patent application(s) filed by the
Licensor in the United States and/or other jurisdictions in connection with the
Software. The Licensor grants the Licensee for the duration of this Agreement,
a free of charge, non-sublicenseable, non-exclusive, non-transferable copyright
and patent license (in consequence of said patent application(s)) to use the
Software for non-commercial purpose only, including teaching and research at
educational institutions and research at not-for-profit research institutions
in accordance with the provisions of this Agreement. Non-commercial use
expressly excludes any profit-making or commercial activities, including without
limitation sale, license, manufacture or development of commercial products, use in
commercially-sponsored research, use at a laboratory or other facility owned or
controlled (whether in whole or in part) by a commercial entity, provision of
consulting service, use for or on behalf of any commercial entity, use in
research where a commercial party obtains rights to research results or any
other benefit, and use of the code in any models, model weights or code
resulting from such procedure in any commercial product. Notwithstanding the
foregoing restrictions, you can use this code for publishing comparison results
for academic papers, including retraining on your own data. Any use of the
Software for any purpose other than pursuant to the license grant set forth
above shall automatically terminate this License.
2.2 The Licensee is permitted to make modifications to the Software
provided that any distribution of such modifications is in accordance with
Clause 3.
2.3 Except as expressly permitted by this Agreement and save to the
extent and in the circumstances expressly required to be permitted by law, the
Licensee is not permitted to rent, lease, sell, offer to sell, or loan the
Software or its associated documentation.
3. Redistribution and modifications
3.1 The Licensee may reproduce and distribute copies of the Software, with
or without modifications, in source format only and only to this same GitHub
repository , and provided that any and every distribution is accompanied by an
unmodified copy of this License and that the following copyright notice is
always displayed in an obvious manner: Copyright © Niantic, Inc. 2018. All
rights reserved.
3.2 In the case where the Software has been modified, any distribution must
include prominent notices indicating which files have been changed.
3.3 The Licensee shall cause any work that it distributes or publishes,
that in whole or in part contains or is derived from the Software or any part
thereof (“Work based on the Software”), to be licensed as a whole at no charge
to all third parties entitled to a license to the Software under the terms of
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4. Duration.
This Agreement is effective until the Licensee terminates it by destroying
the Software, any Work based on the Software, and its documentation together
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5. Disclaimer of Warranties.
The Software is provided as is. To the maximum extent permitted by law,
Licensor provides no warranties or conditions of any kind, either express or
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6. LIMITATION OF LIABILITY.
IN NO EVENT SHALL THE LICENSOR AND/OR AUTHORS BE LIABLE FOR ANY DIRECT,
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The Licensee shall indemnify the Licensor and/or Authors against all third
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8.3 The Licensee shall promptly notify the Licensor of any improvement or
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8.4 The Licensee grants an exclusive first option to the Licensor to be
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9. Acknowledgements.
The Licensee shall acknowledge the Authors and use of the Software in the
publication of any work that uses, or results that are achieved through, the
use of the Software. The following citation shall be included in the
acknowledgement: “MVSAnywhere: Zero Shot Multi-View Stereo",
by S. Izquierdo, M. Sayed, M. Firman, G. Garcia-Hernando,
D. Turmukhambetov, J. Civera, O. Mac Aodha, G. Brostow, and J. Watson
Proceedings of the Computer Vision and Pattern Recognition (CVPR), 2025”.
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This Agreement shall be governed by, construed and interpreted in
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of this Agreement.
================================================
FILE: Makefile
================================================
SHELL = /bin/bash
SYSTEM_NAME := $(shell uname)
SYSTEM_ARCHITECTURE := $(shell uname -m)
MAMBA_INSTALL_SCRIPT := Miniforge3-24.11.2-1-$(SYSTEM_NAME)-$(SYSTEM_ARCHITECTURE).sh
MAMBA_ENV_NAME := mvsanywhere
PACKAGE_FOLDER := src/mvsanywhere
# HELP: install-mamba: Install Mamba
.PHONY: install-mamba
install-mamba:
@echo "Installing Mamba..."
@curl -L -O "https://github.com/conda-forge/miniforge/releases/download/24.11.2-1/$(MAMBA_INSTALL_SCRIPT)"
@chmod +x "$(MAMBA_INSTALL_SCRIPT)"
@./$(MAMBA_INSTALL_SCRIPT)
@rm "$(MAMBA_INSTALL_SCRIPT)"
# HELP: create-mamba-env: Create a new Mamba environment
.PHONY: create-mamba-env
create-mamba-env:
@mamba env create -f environment.yml -n "$(MAMBA_ENV_NAME)"
@echo -e " Mamba env created!"
@echo "Installing pip dependencies..."
@echo -e "🎉🎉 Your new $(MAMBA_ENV_NAME) mamba environment is ready to be used 🎉🎉"
# HELP: black: Run Black
.PHONY: black
black:
@echo "Running Black..."
black --check --diff --config pyproject.toml .
# HELP: isort: Run isort
.PHONY: isort
isort:
@echo "Running isort..."
isort ${PACKAGE_FOLDER} tests -c --settings-path pyproject.toml
# HELP: format-code: Format code using
.PHONY: format-code
format-code:
@echo "Formatting code..."
isort ${PACKAGE_FOLDER} tests --settings-path pyproject.toml
black --config pyproject.toml .
@echo -e "✅✅ Code formatted ✅✅"
================================================
FILE: README.md
================================================
# MVSAnywhere: Zero Shot Multi-View Stereo
A multi-view stereo depth estimation model which works anywhere, in any scene, with any range of depths
> **MVSAnywhere: Zero Shot Multi-View Stereo**
>
> [Sergio Izquierdo](https://serizba.github.io/), [Mohamed Sayed](https://masayed.com), [Michael Firman](http://www.michaelfirman.co.uk), [Guillermo Garcia-Hernando](https://guiggh.github.io/), [Daniyar Turmukhambetov](https://dantkz.github.io/about/), [Javier Civera](http://webdiis.unizar.es/~jcivera/), [Oisin Mac Aodha](https://homepages.inf.ed.ac.uk/omacaod/), [Gabriel Brostow](http://www0.cs.ucl.ac.uk/staff/g.brostow/) and [Jamie Watson](https://www.linkedin.com/in/jamie-watson-544825127/).
>
> [Paper, CVPR 2025 (arXiv pdf)](https://arxiv.org/abs/2503.22430), [Project Page](https://nianticlabs.github.io/mvsanywhere/)
https://github.com/user-attachments/assets/d35b93f7-5f0e-4fbd-b991-bc4e7a45f2b6
This code is for non-commercial use; please see the [license file](LICENSE) for terms. If you do find any part of this codebase helpful, please cite our paper using the BibTex below and link this repo. Thanks!
## Table of Contents
- [MVSAnywhere: Zero Shot Multi-View Stereo](#mvsanywhere-zero-shot-multi-view-stereo)
- [Table of Contents](#table-of-contents)
- [⚙️ Setup](#️-setup)
- [📦 Pretrained Models](#-pretrained-models)
- [🏃 Running out of the box!](#-running-out-of-the-box)
- [Running on recordings from your own device!](#running-on-recordings-from-your-own-device)
- [🍏 iOS](#-ios)
- [📱 Android](#-android)
- [📷 Custom data](#-custom-data)
- [Running Gaussian splatting with MVSAnywhere regularisation!](#running-gaussian-splatting-with-mvsanywhere-regularisation)
- [📊 Testing and Evaluation](#-testing-and-evaluation)
- [Robust Multi-View Depth Benchmark (RMVD)](#robust-multi-view-depth-benchmark-rmvd)
- [🔨 Training](#-training)
- [📝🧮👩💻 Notation for Transformation Matrices](#-notation-for-transformation-matrices)
- [🗺️ World Coordinate System](#️-world-coordinate-system)
- [🙏 Acknowledgements](#-acknowledgements)
- [📜 BibTeX](#-bibtex)
- [👩⚖️ License](#️-license)
## ⚙️ Setup
We are going to create a new Mamba environment called `mvsanywhere`. If you don't have Mamba, you can install it with:
```shell
make install-mamba
```
```shell
make create-mamba-env
mamba activate mvsanywhere
```
In the code directory, install the repo as a pip package:
```shell
pip install -e .
```
To use our Gaussian splatting regularization also install that module:
```shell
pip install -e src/regsplatfacto/
```
## 📦 Pretrained Models
We provide 2 variants of our models: [mvsanywhere_hero.ckpt](https://storage.googleapis.com/niantic-lon-static/research/mvsanywhere/mvsanywhere_hero.ckpt) and [mvsanywhere_dot.ckpt](https://storage.googleapis.com/niantic-lon-static/research/mvsanywhere/mvsanywhere_dot.ckpt). `mvsanywhere_hero` is "Ours" from the main paper, and `mvsanywhere_dot` is ours with no metadata MLP.
## 🏃 Running out of the box!
We've now included two scans for people to try out immediately with the code. You can download these scans [from here](https://drive.google.com/file/d/1x-auV7vGCMdu5yZUMPcoP83p77QOuasT/view?usp=sharing).
Steps:
1. Download weights for the `hero_model` into the weights directory.
2. Download the scans and unzip them to a directory of your choosing.
3. You should be able to run it! Something like this will work:
```shell
CUDA_VISIBLE_DEVICES=0 python src/mvsanywhere/run_demo.py \
--name mvsanywhere \
--output_base_path OUTPUT_PATH \
--config_file configs/models/mvsanywhere_model.yaml \
--load_weights_from_checkpoint weights/mvsanywhere_hero.ckpt \
--data_config_file configs/data/vdr/vdr_dense.yaml \
--scan_parent_directory /path/to/vdr/ \
--scan_name house \ # Scan name (house or living_room)
--num_workers 8 \
--batch_size 2 \
--fast_cost_volume \
--run_fusion \
--depth_fuser custom_open3d \
--fuse_color \
--fusion_max_depth 3.5 \
--fusion_resolution 0.02 \
--extended_neg_truncation \
--dump_depth_visualization
```
This will output meshes, quick depth viz, and socres when benchmarked against LiDAR depth under `OUTPUT_PATH`.
If you run out of GPU memory, you can try removing the `--fast_cost_colume` flag.
## Running on recordings from your own device!
### 🍏 iOS
<details>
<summary>How to use NeRF Capture to record videos</summary>
1. Download the [NeRF Capture](https://github.com/jc211/NeRFCapture) app from the [App Store](https://apps.apple.com/us/app/nerfcapture/id6446518379). Capture a recording of your favourite environment and save it.
2. Place your recordings in a directory with the following structure:
```
/path/to/recordings/
│-- recording_0/
│ │-- images/
| | |-- image_0.png
| | |-- image_1.png
| | ...
│ │-- transforms.json
│-- recording_1/
| ...
```
3. And run the model 🚀🚀🚀
```shell
python src/mvsanywhere/run_demo.py \
--name mvsanywhere \
--output_base_path OUTPUT_PATH \
--config_file configs/models/mvsanywhere_model.yaml \
--load_weights_from_checkpoint weights/mvsanywhere_hero.ckpt \
--data_config_file configs/data/nerfstudio/nerfstudio_empty.yaml \
--scan_parent_directory /path/to/recordings/ \
--scan_name recording_0 \
--fast_cost_volume \
--num_workers 8 \
--batch_size 2 \
--image_height 480 \
--image_width 640 \
--dump_depth_visualization \
--rotate_images # Only if you recorded in portrait
```
</details>
### 📱 Android
<details>
<summary>Use ARCorder to get a video in Android with camera poses</summary>
1. Download the [ARCorder](https://github.com/serizba/arcorder) app from [releases](https://github.com/serizba/arcorder/releases/download/v1.0.0/arcorder_release.apk). This very simple app relies on Android AR Core system, accuracy of the computed poses might be limited. Capture a recording of your favourite environment and save it.
2. Place your recordings in a directory with the following structure:
```
/path/to/recordings/
│-- recording_0/
│ │-- images/
| | |-- image_0.png
| | |-- image_1.png
| | ...
│ │-- transforms.json
│-- recording_1/
| ...
```
3. And run the model 🚀🚀🚀
```shell
python src/mvsanywhere/run_demo.py \
--name mvsanywhere \
--output_base_path OUTPUT_PATH \
--config_file configs/models/mvsanywhere_model.yaml \
--load_weights_from_checkpoint weights/mvsanywhere_hero.ckpt \
--data_config_file configs/data/nerfstudio/nerfstudio_empty.yaml \
--scan_parent_directory /path/to/recordings/ \
--scan_name recording_0 \
--fast_cost_volume \
--num_workers 8 \
--batch_size 2 \
--image_height 480 \
--image_width 640 \
--dump_depth_visualization \
--rotate_images # Only if you recorded in portrait
```
</details>
### 📷 Custom data
<details>
<summary>Use COLMAP to obtain a sparse reconstruction</summary>
If you already have a COLMAP reconstruction skip to 4.
1. Install [nerfstudio](https://docs.nerf.studio/quickstart/installation.html)
2. Install COLMAP using `conda install -c conda-forge colmap`.
3. Process your video/sequence using
```shell
ns-process-data {images, video} --data {DATA_PATH} --output-dir {PROCESSED_DATA_DIR}
```
4. Your reconstructions should have the following structure:
```
/path/to/reconstruction/
│-- reconstruction_0/
│ │-- images/
| | |-- image_0.png
| | |-- image_1.png
| | ...
│ │-- colmap/
| | |-- database.db
| | |-- sparse/
| | | |-- 0/
| | | | |-- cameras.bin
| | | | |-- images.bin
| | | | ...
| | | |-- 1/
| | | | ...
│-- reconstruction_1/
| ...
```
5. And run the model 🚀🚀🚀
```shell
python src/mvsanywhere/run_demo.py \
--name mvsanywhere \
--output_base_path OUTPUT_PATH \
--config_file configs/models/mvsanywhere_model.yaml \
--load_weights_from_checkpoint weights/mvsanywhere_hero.ckpt \
--data_config_file configs/data/colmap/colmap_empty.yaml \
--scan_parent_directory /path/to/reconstruction \
--scan_name reconstruction_0:0 \ # reconstruction_name:n where n is the colmap sparse model
--fast_cost_volume \
--num_workers 8 \
--batch_size 2 \
--image_height 480 \
--image_width 640 \
--dump_depth_visualization
```
</details>
## Running Gaussian splatting with MVSAnywhere regularisation!
https://github.com/user-attachments/assets/12a6bb3f-fe9c-48ed-8982-e55c59dfd14d
We release code `regsplatfacto` to run splatting using MVSAnywhere depths as regularisation. This is heavily inspired by techniques such as [DN-Splatter](https://maturk.github.io/dn-splatter/) and [VCR-Gauss](https://hlinchen.github.io/projects/VCR-GauS/).
You can use any data in the nerfstudio format - e.g. existing nerfstudio data, or data from the 3 sources listed above.
If you are using data which has camera distortion, you will need to run our script `scripts/data_scripts/undistort_nerfstudio_data.py`:
```shell
python3 scripts/data_scripts/undistort_nerfstudio_data.py \
--data-dir /path/to/input/scene \
--output-dir /path/to/output/scene
```
Additionally, the [NeRF Capture](https://github.com/jc211/NeRFCapture) app saves frame metadata without file extension. To run splatting you will need to run our script `scripts/data_scripts/fix_nerfcapture_filenames.py`.
To train a splat, you can use
```shell
ns-train regsplatfacto \
--data path/to/data \
--experiment-name mvsanywhere-splatting \
--pipeline.datamanager.load_weights_from_checkpoint path/to/model \
--pipeline.model.use-skybox False
```
This will first run mvsanywhere inference and save outputs to disk, and then start training your splat.
> Tips:
> * If your data was captured with a phone in portrait mode, you can append the flag `--pipeline.datamanager.rotate_images True`.
> * If your data contains a lot of sky, you can try adding a background skybox using `--pipeline.model.use-skybox True`.
Once you have a splat, you can extract a mesh using TSDF fusion, using
```shell
ns-render-for-meshing \
--load-config /path/to/splat/config \
--rescale_to_world True \
--output_path /path/to/render/outputs
ns-meshing \
--renders-path /path/to/render/outputs \
--max_depth 20.0 \
--save-name mvsanywhere_mesh \
--voxel_size 0.04
```
If you are running on a scene reconstructed without metric scale (e.g. COLMAP), then you will need to adjust the `max_depth` and `voxel_size` to be something sensible for your scale.
Congratulations - you now have a splat and a mesh!
## 📊 Testing and Evaluation
### Robust Multi-View Depth Benchmark (RMVD)
We used the [Robust Multi-View Depth Benchmark](https://github.com/lmb-freiburg/robustmvd/) to evaluate MVSAnywhere depth estimation on a zero-shot environment with multiple datasets.
To evaluate MVSAnywhere on this benchmark, first, download the benchmark code in your system:
```shell
git clone https://github.com/lmb-freiburg/robustmvd.git
```
Now, download and preprocess the evaluation datasets following [this guide](https://github.com/lmb-freiburg/robustmvd/blob/master/rmvd/data/README.md). You should download:
- KITTI
- Scannet
- ETH3D
- DTU
- Tanks and Temples
Don't forget to set the path to these datasets in `rmvd/data/paths.toml`. Now you are ready to evaluate MVSAnywhere by just running:
```shell
export PYTHONPATH="/path/to/robustmvd/:$PYTHONPATH"
python src/mvsanywhere/test_rmvd.py \
--name mvsanywhere \
--output_base_path OUTPUT_PATH \
--config_file configs/models/mvsanywhere_model.yaml \
--load_weights_from_checkpoint weights/mvsanywhere_hero.ckpt
```
## 🔨 Training
To train MVSAnywhere:
1. Download all the required synthetic datasets (and val dataset):
<details>
<summary>Hypersim</summary>
* Download following instructions from [here](https://github.com/apple/ml-hypersim):
```shell
python code/python/tools/dataset_download_images.py \
--downloads_dir path/to/download \
--decompress_dir /path/to/hypersim/raw
```
* Update `configs/data/hypersim/hypersim_default_train.yaml` to point to the correct location.
* Convert distances into planar depth using the provided script in this repo:
```shell
python ./data_scripts/generate_hypersim_planar_depths.py \
--data_config configs/data/hypersim_default_train.yaml \
--num_workers 8
```
</details>
<details>
<summary>TartanAir</summary>
* Download following instructions from [here](https://github.com/apple/ml-hypersim):
```shell
python download_training.py \
--output-dir /path/to/tartan \
--rgb \
--depth \
--seg \
--only-left \
--unzip
```
* Update `configs/data/tartanair/tartanair_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>BlendedMVG</summary>
* Download following instructions from [here](https://github.com/YoYo000/BlendedMVS).
* You should download BlendedMVS, BlendedMVS+ and BlendedMVS++, all low-res. Place all on the same folder.
* Update `configs/data/blendedmvg/blendedmvg_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>MatrixCity</summary>
* Download following instructions from [here](https://github.com/city-super/MatrixCity).
* You should download big_city, big_city_depth, big_city_depth_float32.
* Update `configs/data/matrix_city/matrix_city_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>VKITTI2</summary>
* Download following instructions from [here](https://europe.naverlabs.com/proxy-virtual-worlds-vkitti-2/).
* You should download rgb, depth, classSegmentation and textgt.
* Update `configs/data/vkitti/vkitti_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>Dynamic Replica</summary>
* Download following instructions from [here](https://github.com/facebookresearch/dynamic_stereo).
* After download you can remove unused stuff to save disk space (segmentation, optical flow and pixel trajectories.)
* Update `configs/data/dynamic_replica/dynamic_replica_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>MVSSynth</summary>
* Download following instructions from [here](https://phuang17.github.io/DeepMVS/mvs-synth.html).
* You should download the 960x540 version.
* Update `configs/data/mvssynth/mvssynth_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>SAIL-VOS 3D</summary>
* Download following instructions from [here](https://sailvos.web.illinois.edu/_site/_site/index.html).
* You will need to contact the authors to download the data.
* Buy Grand Theft Auto V.
* (optional, recommended) Play Grand Theft Auto V and relax a little bit.
* Update `configs/data/sailvos3d/sailvos3d_default_train.yaml` to point to the correct location.
</details>
<details>
<summary>ScanNet v2 (Optional, val only)</summary>
* Follow the instructions from [here](https://github.com/nianticlabs/mvsanywhere/tree/main/scripts/data_scripts/scannet_wrangling_scripts).
</details>
2. Download Depth Anything v2 base weights from [here](https://github.com/DepthAnything/Depth-Anything-V2).
3. Now you can train the model using:
```shell
python src/mvsanywhere/train.py \
--log_dir logs/ \
--name mvsanywhere_training \
--config_file configs/models/mvsanywhere_model.yaml \
--data_config configs/data/hypersim/hypersim_default_train.yaml:configs/data/tartanair/tartanair_default_train.yaml:configs/data/blendedmvg/blendedmvg_default_train.yaml:configs/data/matrix_city/matrix_city_default_train.yaml:configs/data/vkitti/vkitti_default_train.yaml:configs/data/dynamic_replica/dynamic_replica_default_train.yaml:configs/data/mvssynth/mvssynth_default_train.yaml:configs/data/sailvos3d/sailvos3d_default_train.yaml \
--val_data_config configs/data/scannet/scannet_default_val.yaml \
--batch_size 6 \
--val_batch_size 6 \
--da_weights_path /path/to/depth_anything_v2_vitb.pth \
--gpus 2
```
## 📝🧮👩💻 Notation for Transformation Matrices
__TL;DR:__ `world_T_cam == world_from_cam`
This repo uses the notation "cam_T_world" to denote a transformation from world to camera points (extrinsics). The intention is to make it so that the coordinate frame names would match on either side of the variable when used in multiplication from *right to left*:
cam_points = cam_T_world @ world_points
`world_T_cam` denotes camera pose (from cam to world coords). `ref_T_src` denotes a transformation from a source to a reference view.
Finally this notation allows for representing both rotations and translations such as: `world_R_cam` and `world_t_cam`
## 🗺️ World Coordinate System
This repo is geared towards ScanNet, so while its functionality should allow for any coordinate system (signaled via input flags), the model weights we provide assume a ScanNet coordinate system. This is important since we include ray information as part of metadata. Other datasets used with these weights should be transformed to the ScanNet system. The dataset classes we include will perform the appropriate transforms.
## 🙏 Acknowledgements
The tuple generation scripts make heavy use of a modified version of DeepVideoMVS's [Keyframe buffer](https://github.com/ardaduz/deep-video-mvs/blob/master/dvmvs/keyframe_buffer.py) (thanks Arda and co!).
We'd like to thank the Niantic Raptor R\&D infrastructure team - Saki Shinoda, Jakub Powierza, and Stanimir Vichev - for their valuable infrastructure support.
## 📜 BibTeX
If you find our work useful in your research please consider citing our paper:
```
@inproceedings{izquierdo2025mvsanywhere,
title={{MVSAnywhere}: Zero Shot Multi-View Stereo},
author={Izquierdo, Sergio and Sayed, Mohamed and Firman, Michael and Garcia-Hernando, Guillermo and Turmukhambetov, Daniyar and Civera, Javier and Mac Aodha, Oisin and Brostow, Gabriel J. and Watson, Jamie},
booktitle={CVPR},
year={2025}
}
```
## 👩⚖️ License
Copyright © Niantic, Inc. 2024. Patent Pending.
All rights reserved.
Please see the [license file](LICENSE) for terms.
================================================
FILE: configs/data/blendedmvg/blendedmvg_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/blendedmvs/
tuple_info_file_location: data_splits/blendedmvg/
dataset_scan_split_file: data_splits/blendedmvg/blendedmvg_train.txt
dataset: blendedmvg
mv_tuple_file_suffix: _pair.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
================================================
FILE: configs/data/blendedmvg/blendedmvg_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/blendedmvs/
tuple_info_file_location: data_splits/blendedmvg/
dataset_scan_split_file: data_splits/blendedmvg/blendedmvg_val.txt
dataset: blendedmvg
mv_tuple_file_suffix: _pair.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
================================================
FILE: configs/data/colmap/colmap_empty.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset: colmap
num_images_in_tuple: 8
frame_tuple_type: dense_offline
split: test
================================================
FILE: configs/data/demo/demo_colmap.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /path/to/colmap_reconstructions/
tuple_info_file_location: /path/to/colmap_reconstructions/
dataset_scan_split_file: /path/to/colmap_reconstructions/scans.txt
dataset: colmap
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: test
================================================
FILE: configs/data/demo/demo_nerf_capture.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /path/to/nerf_capture/data/
tuple_info_file_location: /path/to/nerf_capture/data/
dataset_scan_split_file: /path/to/nerf_capture/data/scans.txt
dataset: nerf
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: test
================================================
FILE: configs/data/dynamic_replica/dynamic_replica_default_test.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/dynamic_replica/dynamic_stereo/dynamic_replica_data/
tuple_info_file_location: data_splits/dynamic_replica/
dataset_scan_split_file: data_splits/dynamic_replica/dynamic_replica_test.txt
dataset: dynamic_replica
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: test
train_maximum_pose_distance: 1.00
================================================
FILE: configs/data/dynamic_replica/dynamic_replica_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/dynamic_replica/dynamic_stereo/dynamic_replica_data/
tuple_info_file_location: data_splits/dynamic_replica/
dataset_scan_split_file: data_splits/dynamic_replica/dynamic_replica_train.txt
dataset: dynamic_replica
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
train_maximum_pose_distance: 1.00
================================================
FILE: configs/data/dynamic_replica/dynamic_replica_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/dynamic_replica/dynamic_stereo/dynamic_replica_data/
tuple_info_file_location: data_splits/dynamic_replica/
dataset_scan_split_file: data_splits/dynamic_replica/dynamic_replica_val.txt
dataset: dynamic_replica
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
train_maximum_pose_distance: 1.00
================================================
FILE: configs/data/hypersim/hypersim_default_test.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/hypersim/raw/
tuple_info_file_location: data_splits/hypersim/standard_split/
dataset_scan_split_file: data_splits/hypersim/standard_split/test_files_all.json
dataset: hypersim
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: test
use_min_max_depth: True
================================================
FILE: configs/data/hypersim/hypersim_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/hypersim/raw/
tuple_info_file_location: data_splits/hypersim/bd_split/
dataset_scan_split_file: data_splits/hypersim/bd_split/train_files_bd.json
dataset: hypersim
mv_tuple_file_suffix: _clean_eight_view_deepvmvs_bd.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
================================================
FILE: configs/data/hypersim/hypersim_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/hypersim/raw/
tuple_info_file_location: data_splits/hypersim/bd_split/
dataset_scan_split_file: data_splits/hypersim/bd_split/val_files_bd.json
dataset: hypersim
mv_tuple_file_suffix: _clean_eight_view_deepvmvs_bd.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
================================================
FILE: configs/data/matrix_city/matrix_city_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/matrix
tuple_info_file_location: data_splits/matrix_city/
dataset_scan_split_file: data_splits/matrix_city/matrix_city_train.json
dataset: matrix_city
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
train_maximum_pose_distance: 1.00
================================================
FILE: configs/data/matrix_city/matrix_city_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/matrix
tuple_info_file_location: data_splits/matrix_city/
dataset_scan_split_file: data_splits/matrix_city/matrix_city_val.txt
dataset: matrix_city
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
train_maximum_pose_distance: 1.00
================================================
FILE: configs/data/mvssynth/mvssynth_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/mvssynth/GTAV_540
tuple_info_file_location: data_splits/mvssynth/
dataset_scan_split_file: data_splits/mvssynth/train_scans.txt
dataset: mvssynth
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
val_interval: 100
================================================
FILE: configs/data/mvssynth/mvssynth_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/mvssynth/GTAV_540
tuple_info_file_location: data_splits/mvssynth/
dataset_scan_split_file: data_splits/mvssynth/val_scans.txt
dataset: mvssynth
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
val_interval: 100
================================================
FILE: configs/data/nerfstudio/nerfstudio_empty.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset: nerfstudio
num_images_in_tuple: 8
frame_tuple_type: dense_offline
split: test
================================================
FILE: configs/data/sailvos3d/sailvos3d_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/sailovos3d/sailvos3d
tuple_info_file_location: data_splits/sailvos3d/
dataset_scan_split_file: data_splits/sailvos3d/split_train.txt
dataset: sailvos3d
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
train_maximum_pose_distance: 1.00
================================================
FILE: configs/data/scannet/scannet_default_test.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/scannet
tuple_info_file_location: data_splits/ScanNetv2/standard_split
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_test.txt
dataset: scannet
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
# default means every keyframe defined by DVMVS.
frame_tuple_type: default
split: test
================================================
FILE: configs/data/scannet/scannet_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/scannet
tuple_info_file_location: data_splits/ScanNetv2/standard_split/
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_train.txt
dataset: scannet
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
================================================
FILE: configs/data/scannet/scannet_default_train_inference_style.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/scannet-data-png2/
tuple_info_file_location: data_splits/ScanNetv2/standard_split
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_train.txt
dataset: scannet
mv_tuple_file_suffix: _test_eight_view_deepvmvs.txt
num_images_in_tuple: 8
# default means every keyframe defined by DVMVS.
frame_tuple_type: default
split: train
================================================
FILE: configs/data/scannet/scannet_default_train_ray.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas/projects/shared/datasets/academic_use_only/scannet/
tuple_info_file_location: /mnt/nas3/shared/projects/geometryhints/data_splits/ScanNetv2/standard_split/
dataset_scan_split_file: /mnt/nas3/shared/projects/geometryhints/data_splits/ScanNetv2/standard_split/scannetv2_train.txt
dataset: scannet
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
================================================
FILE: configs/data/scannet/scannet_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/scannet
tuple_info_file_location: data_splits/ScanNetv2/standard_split/
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_val.txt
dataset: scannet
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
================================================
FILE: configs/data/scannet/scannet_default_val_inference_style.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/scannet-data-png2/
tuple_info_file_location: data_splits/ScanNetv2/standard_split
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_val.txt
dataset: scannet
mv_tuple_file_suffix: _test_eight_view_deepvmvs.txt
num_images_in_tuple: 8
# default means every keyframe defined by DVMVS.
frame_tuple_type: default
split: val
================================================
FILE: configs/data/scannet/scannet_dense_test.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/scannet
tuple_info_file_location: data_splits/ScanNetv2/standard_split/
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_test.txt
dataset: scannet
mv_tuple_file_suffix: _eight_view_deepvmvs_dense.txt
num_images_in_tuple: 8
frame_tuple_type: dense
split: test
================================================
FILE: configs/data/scannet/scannet_dense_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: datasets/scannetv2/
tuple_info_file_location: data_splits/ScanNetv2/standard_split/
dataset_scan_split_file: data_splits/ScanNetv2/standard_split/scannetv2_val.txt
dataset: scannet
mv_tuple_file_suffix: _eight_view_deepvmvs_dense.txt
num_images_in_tuple: 8
frame_tuple_type: dense
split: val
================================================
FILE: configs/data/tartanair/tartanair_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/tartanair/
tuple_info_file_location: data_splits/tartanair/
dataset_scan_split_file: data_splits/tartanair/train_scans.txt
dataset: tartanair
mv_tuple_file_suffix: _eight_view_deepvmvs_bd.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
================================================
FILE: configs/data/tartanair/tartanair_default_val.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/tartanair/
tuple_info_file_location: data_splits/tartanair/
dataset_scan_split_file: data_splits/tartanair/val_scans.txt
dataset: tartanair
mv_tuple_file_suffix: _eight_view_deepvmvs_bd.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: val
================================================
FILE: configs/data/vdr/vdr_default.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
tuple_info_file_location: data_splits/vdr/
dataset_scan_split_file: data_splits/vdr/scans.txt
dataset: vdr
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: test
================================================
FILE: configs/data/vdr/vdr_dense.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
tuple_info_file_location: data_splits/vdr/
dataset_scan_split_file: data_splits/vdr/scans.txt
dataset: vdr
mv_tuple_file_suffix: _eight_view_deepvmvs_dense.txt
num_images_in_tuple: 8
frame_tuple_type: dense
split: test
================================================
FILE: configs/data/vdr/vdr_dense_offline.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
tuple_info_file_location: data_splits/vdr/
dataset_scan_split_file: data_splits/vdr/scans.txt
dataset: vdr
mv_tuple_file_suffix: _eight_view_deepvmvs_dense_offline.txt
num_images_in_tuple: 8
frame_tuple_type: dense_offline
split: test
================================================
FILE: configs/data/vkitti/vkitti_default_train.yaml
================================================
!!python/object:mvsanywhere.options.DataOptions
dataset_path: /mnt/nas3/shared/datasets/vkitti
tuple_info_file_location: data_splits/vkitti/
dataset_scan_split_file: data_splits/vkitti/vkitti_train.txt
dataset: vkitti
mv_tuple_file_suffix: _eight_view_deepvmvs.txt
num_images_in_tuple: 8
frame_tuple_type: default
split: train
train_maximum_pose_distance: 1.00
================================================
FILE: configs/models/mvsanywhere_dot_model.yaml
================================================
!!python/object:mvsanywhere.options.Options
feature_volume_type: simple_cost_volume
batch_size: 16
val_batch_size: 4
cost_volume_aggregation: dot
cv_encoder_type: vit_encoder
depth_decoder_name: dpt
gpus: 2
image_encoder_name: dinov2_vitb14
log_interval: 100
loss_type: log_l1
lr: 0.0001
lr: 0.0001
lr_da_encoder: 0.000005
lr_da_decoder: 0.00005
wd: 0.0001
matching_encoder_type: resnet
name: simplerecon_model
num_sanity_val_steps: 0
num_workers: 12
precision: 16
random_seed: 0
image_width: 640
image_height: 480
val_image_width: 640
val_image_height: 480
matching_scale: 0.25
prediction_scale: 1.0
model_type: depth_model
================================================
FILE: configs/models/mvsanywhere_model.yaml
================================================
!!python/object:mvsanywhere.options.Options
feature_volume_type: view_agnostic_mlp_feature_volume
batch_size: 16
val_batch_size: 4
cost_volume_aggregation: dot
cv_encoder_type: vit_encoder
depth_decoder_name: dpt
gpus: 2
image_encoder_name: dinov2_vitb14
log_interval: 100
loss_type: log_l1
lr: 0.0001
lr: 0.0001
lr_da_encoder: 0.000005
lr_da_decoder: 0.00005
wd: 0.0001
matching_encoder_type: resnet
name: simplerecon_model
num_sanity_val_steps: 0
num_workers: 12
precision: 16
random_seed: 0
image_width: 640
image_height: 480
val_image_width: 640
val_image_height: 480
matching_scale: 0.25
prediction_scale: 1.0
model_type: depth_model
================================================
FILE: configs/models/simplerecon_model.yaml
================================================
!!python/object:mvsanywhere.options.Options
feature_volume_type: mlp_feature_volume
batch_size: 16
cost_volume_aggregation: dot
cv_encoder_type: multi_scale_encoder
depth_decoder_name: unet_pp
gpus: 2
image_encoder_name: efficientnet
log_interval: 100
loss_type: log_l1
lr: 0.0001
wd: 0.0001
matching_encoder_type: resnet
name: simplerecon_model
num_sanity_val_steps: 0
num_workers: 12
precision: 16
random_seed: 0
model_type: depth_model
================================================
FILE: data_splits/ScanNetv2/dvmvs_split/dvmvs_train.txt
================================================
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FILE: data_splits/ScanNetv2/dvmvs_split/dvmvs_val.txt
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FILE: data_splits/ScanNetv2/dvmvs_split/test_eight_view_deepvmvs.txt
================================================
stairs/seq-06 000018 000000 000003 000001 000016 000015 000007 000014
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================================================
FILE: data_splits/ScanNetv2/dvmvs_split/test_eight_view_deepvmvs_dense.txt
================================================
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gitextract_knu0jtpw/
├── .gitignore
├── LICENSE
├── Makefile
├── README.md
├── configs/
│ ├── data/
│ │ ├── blendedmvg/
│ │ │ ├── blendedmvg_default_train.yaml
│ │ │ └── blendedmvg_default_val.yaml
│ │ ├── colmap/
│ │ │ └── colmap_empty.yaml
│ │ ├── demo/
│ │ │ ├── demo_colmap.yaml
│ │ │ └── demo_nerf_capture.yaml
│ │ ├── dynamic_replica/
│ │ │ ├── dynamic_replica_default_test.yaml
│ │ │ ├── dynamic_replica_default_train.yaml
│ │ │ └── dynamic_replica_default_val.yaml
│ │ ├── hypersim/
│ │ │ ├── hypersim_default_test.yaml
│ │ │ ├── hypersim_default_train.yaml
│ │ │ └── hypersim_default_val.yaml
│ │ ├── matrix_city/
│ │ │ ├── matrix_city_default_train.yaml
│ │ │ └── matrix_city_default_val.yaml
│ │ ├── mvssynth/
│ │ │ ├── mvssynth_default_train.yaml
│ │ │ └── mvssynth_default_val.yaml
│ │ ├── nerfstudio/
│ │ │ └── nerfstudio_empty.yaml
│ │ ├── sailvos3d/
│ │ │ └── sailvos3d_default_train.yaml
│ │ ├── scannet/
│ │ │ ├── scannet_default_test.yaml
│ │ │ ├── scannet_default_train.yaml
│ │ │ ├── scannet_default_train_inference_style.yaml
│ │ │ ├── scannet_default_train_ray.yaml
│ │ │ ├── scannet_default_val.yaml
│ │ │ ├── scannet_default_val_inference_style.yaml
│ │ │ ├── scannet_dense_test.yaml
│ │ │ └── scannet_dense_val.yaml
│ │ ├── tartanair/
│ │ │ ├── tartanair_default_train.yaml
│ │ │ └── tartanair_default_val.yaml
│ │ ├── vdr/
│ │ │ ├── vdr_default.yaml
│ │ │ ├── vdr_dense.yaml
│ │ │ └── vdr_dense_offline.yaml
│ │ └── vkitti/
│ │ └── vkitti_default_train.yaml
│ └── models/
│ ├── mvsanywhere_dot_model.yaml
│ ├── mvsanywhere_model.yaml
│ └── simplerecon_model.yaml
├── data_splits/
│ ├── ScanNetv2/
│ │ ├── dvmvs_split/
│ │ │ ├── dvmvs_train.txt
│ │ │ ├── dvmvs_val.txt
│ │ │ ├── test_eight_view_deepvmvs.txt
│ │ │ └── test_eight_view_deepvmvs_dense.txt
│ │ └── standard_split/
│ │ ├── scannetv2_test.txt
│ │ ├── scannetv2_test_planes.txt
│ │ ├── scannetv2_train.txt
│ │ ├── scannetv2_val.txt
│ │ ├── test_eight_view_deepvmvs.txt
│ │ ├── test_eight_view_deepvmvs_dense.txt
│ │ ├── test_eight_view_deepvmvs_offline.txt
│ │ ├── test_planes_eight_view_deepvmvs.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ ├── train_test_eight_view_deepvmvs.txt
│ │ ├── val_eight_view_deepvmvs.txt
│ │ └── val_test_eight_view_deepvmvs.txt
│ ├── blendedmvg/
│ │ ├── blendedmvg_train.txt
│ │ ├── blendedmvg_val.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ └── val_eight_view_deepvmvs.txt
│ ├── dynamic_replica/
│ │ ├── dynamic_replica_test.txt
│ │ ├── dynamic_replica_train.txt
│ │ ├── dynamic_replica_val.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ └── val_eight_view_deepvmvs.txt
│ ├── hypersim/
│ │ ├── bd_split/
│ │ │ ├── train_clean_eight_view_deepvmvs_bd.txt
│ │ │ ├── train_eight_view_deepvmvs_bd.txt
│ │ │ ├── train_files_bd.json
│ │ │ ├── train_files_mean_10_m_no_bad_scenes.txt
│ │ │ ├── val_clean_eight_view_deepvmvs_bd.txt
│ │ │ ├── val_eight_view_deepvmvs_bd.txt
│ │ │ ├── val_files_bd.json
│ │ │ └── val_files_mean_10_m_no_bad_scenes.txt
│ │ └── standard_split/
│ │ ├── test_files_all.json
│ │ ├── train_files_all.json
│ │ └── val_files_all.json
│ ├── matrix_city/
│ │ ├── matrix_city_train.json
│ │ ├── matrix_city_train.txt
│ │ ├── matrix_city_val.txt
│ │ ├── train_eight_view_deepvmvs.txt
│ │ └── val_eight_view_deepvmvs.txt
│ ├── mvssynth/
│ │ ├── train_eight_view_deepvmvs.txt
│ │ ├── train_scans.txt
│ │ ├── val_eight_view_deepvmvs.txt
│ │ └── val_scans.txt
│ ├── sailvos3d/
│ │ ├── split_train.txt
│ │ └── train_eight_view_deepvmvs.txt
│ ├── tartanair/
│ │ ├── all_scans.txt
│ │ ├── train_eight_view_deepvmvs_bd.txt
│ │ ├── train_scans.txt
│ │ ├── val_eight_view_deepvmvs_bd.txt
│ │ └── val_scans.txt
│ ├── vdr/
│ │ ├── scans.txt
│ │ ├── test_eight_view_deepvmvs.txt
│ │ ├── test_eight_view_deepvmvs_dense.txt
│ │ └── test_eight_view_deepvmvs_dense_offline.txt
│ └── vkitti/
│ ├── matrix_city_train.json
│ ├── train_eight_view_deepvmvs.txt
│ └── vkitti_train.txt
├── demo_assets/
│ └── cameras.npy
├── environment.yml
├── eval.py
├── hubconf.py
├── pyproject.toml
├── scripts/
│ ├── create_visibility_volume.py
│ ├── data_scripts/
│ │ ├── filter_hypersim_scenes.py
│ │ ├── fix_nerfcapture_filenames.py
│ │ ├── generate_blendedmvg_tuples.py
│ │ ├── generate_hypersim_planar_depths.py
│ │ ├── generate_matrix_scans.py
│ │ ├── generate_test_tuples.py
│ │ ├── generate_train_tuples.py
│ │ ├── generate_train_tuples_geometry.py
│ │ ├── precompute_valid_frames.py
│ │ ├── scannet_wrangling_scripts/
│ │ │ ├── LICENSE
│ │ │ ├── README.md
│ │ │ ├── SensorData.py
│ │ │ ├── download_scannet.py
│ │ │ ├── env.yml
│ │ │ ├── reader.py
│ │ │ └── splits/
│ │ │ ├── scannetv2_test.txt
│ │ │ ├── scannetv2_train.txt
│ │ │ └── scannetv2_val.txt
│ │ └── undistort_nerfstudio_data.py
│ ├── dust3r_waymo_preprocess.py
│ ├── evals/
│ │ └── mesh_eval.py
│ ├── evaluation.py
│ ├── render_scripts/
│ │ └── render_meshes.py
│ └── strip_checkpoint.py
├── setup.py
├── simple_demo.py
└── src/
├── mvsanywhere/
│ ├── datasets/
│ │ ├── __init__.py
│ │ ├── blendedmvg.py
│ │ ├── change_of_basis.py
│ │ ├── colmap_dataset.py
│ │ ├── dynamic_replica.py
│ │ ├── generic_mvs_dataset.py
│ │ ├── hypersim.py
│ │ ├── matrix_city.py
│ │ ├── mvssynth.py
│ │ ├── nerf_dataset.py
│ │ ├── nerfstudio_dataset.py
│ │ ├── read_write_colmap_model.py
│ │ ├── sailvos3d.py
│ │ ├── scannet_dataset.py
│ │ ├── tartanair.py
│ │ ├── vdr_dataset.py
│ │ └── vkitti.py
│ ├── experiment_modules/
│ │ ├── rmvd_mvsa.py
│ │ └── sr_depth_model.py
│ ├── losses.py
│ ├── modules/
│ │ ├── cost_volume.py
│ │ ├── depth_anything_blocks.py
│ │ ├── feature_volume.py
│ │ ├── layers.py
│ │ ├── networks.py
│ │ ├── networks_fast.py
│ │ ├── view_agnostic_feature_volume.py
│ │ └── vit_modules.py
│ ├── options.py
│ ├── run_demo.py
│ ├── test.py
│ ├── test_rmvd.py
│ ├── tools/
│ │ ├── fusers_helper.py
│ │ ├── keyframe_buffer.py
│ │ ├── marching_cubes/
│ │ │ ├── ext.cpp
│ │ │ ├── marching_cubes.cu
│ │ │ ├── marching_cubes.h
│ │ │ ├── marching_cubes_cpu.cpp
│ │ │ ├── marching_cubes_utils.h
│ │ │ ├── pytorch3d_cutils.h
│ │ │ └── tables.h
│ │ ├── mesh_renderer.py
│ │ ├── partial_fuser.py
│ │ ├── tsdf.py
│ │ └── tuple_generator.py
│ ├── train.py
│ └── utils/
│ ├── augmentation_utils.py
│ ├── cropping_utils.py
│ ├── dataset_utils.py
│ ├── generic_utils.py
│ ├── geometry_utils.py
│ ├── metrics_utils.py
│ ├── model_utils.py
│ ├── pytorch3d_extras.py
│ ├── rendering_utils.py
│ ├── visualization_utils.py
│ └── volume_utils.py
└── regsplatfacto/
├── pyproject.toml
└── regsplatfacto/
├── __init__.py
├── data/
│ ├── __init__.py
│ ├── mvsanywhere_dataset.py
│ ├── py.typed
│ └── regsplatfacto_datamanager.py
├── meshing.py
├── regsplatfacto_config.py
├── regsplatfacto_model.py
├── render_for_meshing.py
└── utils.py
SYMBOL INDEX (764 symbols across 76 files)
FILE: eval.py
function eval (line 13) | def eval(args):
FILE: hubconf.py
class MVSAnywhereInference (line 17) | class MVSAnywhereInference(nn.Module):
method __init__ (line 19) | def __init__(
method forward (line 64) | def forward(
method preprocess_and_run (line 162) | def preprocess_and_run(
function mvsanywhere (line 280) | def mvsanywhere(
FILE: scripts/create_visibility_volume.py
class SimpleScanNetDataset (line 30) | class SimpleScanNetDataset(torch.utils.data.Dataset):
method __init__ (line 33) | def __init__(
method _get_available_frames (line 48) | def _get_available_frames(self, frame_interval: int):
method load_rendered_depth (line 60) | def load_rendered_depth(self, frame_ind: int) -> torch.Tensor:
method load_pose (line 73) | def load_pose(self, frame_ind) -> dict[str, torch.Tensor]:
method load_intrinsics (line 87) | def load_intrinsics(self) -> dict[str, torch.Tensor]:
method load_mesh (line 105) | def load_mesh(self) -> o3d.geometry.TriangleMesh:
method __len__ (line 112) | def __len__(self):
method __getitem__ (line 116) | def __getitem__(self, idx):
function create_all_occlusion_masks (line 131) | def create_all_occlusion_masks(
function cli (line 296) | def cli(
FILE: scripts/data_scripts/fix_nerfcapture_filenames.py
function fix_nerfcapture_filenames (line 6) | def fix_nerfcapture_filenames(
FILE: scripts/data_scripts/generate_hypersim_planar_depths.py
function crawl_subprocess (line 38) | def crawl_subprocess(opts, scan, count, progress):
function crawl (line 76) | def crawl(opts, scans):
FILE: scripts/data_scripts/generate_test_tuples.py
function compute_offline_tuple (line 63) | def compute_offline_tuple(
function default_dvmvs_tuples (line 159) | def default_dvmvs_tuples(scan, poses, dists_to_last_valid, n_measurement...
function offline_dvmvs_tuples (line 213) | def offline_dvmvs_tuples(scan, poses, n_measurement_frames):
function dense_dvmvs_tuples (line 262) | def dense_dvmvs_tuples(scan, poses, n_measurement_frames):
function offline_dense_dvmvs_tuples (line 336) | def offline_dense_dvmvs_tuples(scan, poses, n_measurement_frames):
function crawl_subprocess_long (line 374) | def crawl_subprocess_long(opts_temp_filepath, scan, count, progress):
function crawl (line 517) | def crawl(opts_temp_filepath, opts, scans):
FILE: scripts/data_scripts/generate_train_tuples.py
function gather_pairs_train (line 54) | def gather_pairs_train(
function crawl_subprocess_short (line 137) | def crawl_subprocess_short(opts_temp_filepath, scan, count, progress):
function crawl_subprocess_long (line 228) | def crawl_subprocess_long(opts_temp_filepath, scan, count, progress):
function crawl (line 392) | def crawl(opts_temp_filepath, opts, scans):
FILE: scripts/data_scripts/generate_train_tuples_geometry.py
function crawl_subprocess_long (line 54) | def crawl_subprocess_long(opts_temp_filepath, scan, count, progress):
function crawl (line 222) | def crawl(opts_temp_filepath, opts, scans):
FILE: scripts/data_scripts/precompute_valid_frames.py
function process_scan (line 44) | def process_scan(opts_temp_filepath, scan, count, progress):
function multi_process_scans (line 91) | def multi_process_scans(opts_temp_filepath, opts, scans):
FILE: scripts/data_scripts/scannet_wrangling_scripts/SensorData.py
function print_array_on_one_line (line 15) | def print_array_on_one_line():
class RGBDFrame (line 23) | class RGBDFrame:
method load (line 24) | def load(self, file_handle):
method decompress_depth (line 39) | def decompress_depth(self, compression_type):
method decompress_depth_zlib (line 45) | def decompress_depth_zlib(self):
method decompress_color (line 48) | def decompress_color(self, compression_type):
method dump_color_to_file (line 54) | def dump_color_to_file(self, compression_type, filepath):
method decompress_color_jpeg (line 63) | def decompress_color_jpeg(self):
class SensorData (line 67) | class SensorData:
method __init__ (line 68) | def __init__(self, filename):
method load (line 72) | def load(self, filename):
method export_depth_images (line 105) | def export_depth_images(self, output_path, image_size=None, frame_skip...
method export_color_images (line 130) | def export_color_images(self, output_path, image_size=None, frame_skip...
method save_mat_to_file (line 149) | def save_mat_to_file(self, matrix, filename):
method export_poses (line 154) | def export_poses(self, output_path, frame_skip=1):
method export_intrinsics (line 163) | def export_intrinsics(self, output_path, scan_name):
FILE: scripts/data_scripts/scannet_wrangling_scripts/download_scannet.py
function get_release_scans (line 53) | def get_release_scans(release_file):
function download_release (line 62) | def download_release(release_scans, out_dir, file_types, use_v1_sens):
function download_file (line 72) | def download_file(url, out_file):
function download_scan (line 87) | def download_scan(scan_id, out_dir, file_types, use_v1_sens):
function download_task_data (line 103) | def download_task_data(out_dir):
function download_tfrecords (line 122) | def download_tfrecords(in_dir, out_dir):
function download_label_map (line 141) | def download_label_map(out_dir):
function main (line 154) | def main():
FILE: scripts/data_scripts/scannet_wrangling_scripts/reader.py
function process_scan (line 38) | def process_scan(opt, scan_job, count=None, progress=None):
function main (line 65) | def main():
FILE: scripts/data_scripts/undistort_nerfstudio_data.py
function undistort_nerfstudio_data (line 11) | def undistort_nerfstudio_data(
FILE: scripts/dust3r_waymo_preprocess.py
function colmap_to_opencv_intrinsics (line 38) | def colmap_to_opencv_intrinsics(K):
function opencv_to_colmap_intrinsics (line 51) | def opencv_to_colmap_intrinsics(K):
function camera_matrix_of_crop (line 63) | def camera_matrix_of_crop(input_camera_matrix, input_resolution, output_...
function geotrf (line 78) | def geotrf(Trf, pts, ncol=None, norm=False):
function inv (line 142) | def inv(mat):
function imread_cv2 (line 153) | def imread_cv2(path, options=cv2.IMREAD_COLOR):
class ImageList (line 166) | class ImageList:
method __init__ (line 170) | def __init__(self, images):
method __len__ (line 179) | def __len__(self):
method to_pil (line 182) | def to_pil(self):
method size (line 186) | def size(self):
method resize (line 191) | def resize(self, *args, **kwargs):
method crop (line 194) | def crop(self, *args, **kwargs):
method _dispatch (line 197) | def _dispatch(self, func, *args, **kwargs):
function rescale_image_depthmap (line 201) | def rescale_image_depthmap(image, depthmap, camera_intrinsics, output_re...
function starcall (line 237) | def starcall(args):
function starstarcall (line 243) | def starstarcall(args):
function parallel_map (line 249) | def parallel_map(function, args, workers=0, star_args=False, kw_args=Fal...
function parallel_processes (line 299) | def parallel_processes(*args, **kwargs):
function show_raw_pointcloud (line 308) | def show_raw_pointcloud(pts3d, colors, point_size=2):
function main (line 317) | def main(waymo_root, output_dir, subslices, do_extract_frames, workers=1):
function _list_sequences (line 326) | def _list_sequences(db_root):
function make_subsequences (line 332) | def make_subsequences(input_list):
function get_subsliced_sequences (line 339) | def get_subsliced_sequences(db_root, subslices):
function extract_frames (line 349) | def extract_frames(db_root, output_dir, sequences, workers=8):
function process_one_seq (line 358) | def process_one_seq(db_root, output_dir, seq):
function extract_frames_one_seq (line 387) | def extract_frames_one_seq(filename):
function make_crops (line 450) | def make_crops(output_dir, sequences, workers=16, **kw):
function crop_one_seq (line 457) | def crop_one_seq(input_dir, output_dir, seq, resolution=640):
FILE: scripts/evals/mesh_eval.py
function main (line 30) | def main():
FILE: scripts/evaluation.py
function run (line 9) | def run():
function incremental (line 26) | def incremental(checkpoint: str, output_dir: Path):
FILE: scripts/render_scripts/render_meshes.py
class SimpleScanNetDataset (line 55) | class SimpleScanNetDataset(torch.utils.data.Dataset):
method __init__ (line 58) | def __init__(self, scan_name: str, scan_data_root: Path, tuple_filepat...
method _get_available_frames (line 70) | def _get_available_frames(self, tuple_filepath: str):
method load_pose (line 80) | def load_pose(self, frame_ind) -> dict[str, torch.Tensor]:
method load_intrinsics (line 94) | def load_intrinsics(self) -> dict[str, torch.Tensor]:
method load_mesh (line 112) | def load_mesh(self) -> o3d.geometry.TriangleMesh:
method __len__ (line 118) | def __len__(self):
method __getitem__ (line 122) | def __getitem__(self, idx):
function render_scene_meshes (line 136) | def render_scene_meshes(
function render_scene_meshes_partial (line 256) | def render_scene_meshes_partial(
function render_scenes (line 380) | def render_scenes(
FILE: simple_demo.py
function main (line 8) | def main():
FILE: src/mvsanywhere/datasets/blendedmvg.py
class BlendedMVGDataset (line 11) | class BlendedMVGDataset(GenericMVSDataset):
method __init__ (line 27) | def __init__(
method get_sub_folder_dir (line 125) | def get_sub_folder_dir(split):
method get_frame_id_string (line 129) | def get_frame_id_string(self, frame_id):
method get_color_filepath (line 138) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 155) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 172) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 187) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 204) | def get_pose_filepath(self, scan_id, frame_id):
method load_intrinsics (line 217) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 288) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 331) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 360) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/change_of_basis.py
class ChangeOfBasis (line 4) | class ChangeOfBasis:
method convert_matrix_to_vision_convention (line 51) | def convert_matrix_to_vision_convention(cls, pose: np.ndarray) -> np.n...
method convert_arkit_to_vision_convention (line 57) | def convert_arkit_to_vision_convention(cls, pose: np.ndarray) -> np.nd...
method convert_landscape_to_portrait (line 63) | def convert_landscape_to_portrait(cls, pose: np.ndarray) -> np.ndarray:
method convert_portrait_to_landscape (line 69) | def convert_portrait_to_landscape(cls, pose: np.ndarray) -> np.ndarray:
method convert_ned_to_vision_convention (line 75) | def convert_ned_to_vision_convention(cls, pose: np.ndarray) -> np.ndar...
FILE: src/mvsanywhere/datasets/colmap_dataset.py
class ColmapDataset (line 24) | class ColmapDataset(GenericMVSDataset):
method __init__ (line 63) | def __init__(
method get_frame_id_string (line 157) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 166) | def get_valid_frame_path(self, split, scan):
method get_valid_frame_ids (line 181) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method load_pose (line 258) | def load_pose(self, scan_id, frame_id):
method load_intrinsics (line 289) | def load_intrinsics(self, scan_id, frame_id=None, flip=None):
method load_capture_poses (line 382) | def load_capture_poses(self, scan_id):
method load_target_size_depth_and_mask (line 408) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 424) | def load_full_res_depth_and_mask(self, scan_id, frame_id, crop=None):
method get_color_filepath (line 440) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 456) | def get_high_res_color_filepath(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/dynamic_replica.py
class DynamicReplicaFrameAnnotation (line 24) | class DynamicReplicaFrameAnnotation(ImplicitronFrameAnnotation):
class DynamicReplicaDataset (line 30) | class DynamicReplicaDataset(GenericMVSDataset):
method __init__ (line 41) | def __init__(
method get_sub_folder_dir (line 149) | def get_sub_folder_dir(split):
method get_frame_id_string (line 153) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 162) | def get_valid_frame_path(self, split, scan):
method _get_frame_ids (line 177) | def _get_frame_ids(self, split, scan):
method get_valid_frame_ids (line 183) | def get_valid_frame_ids(self, split, scan, store_computed=False):
method get_color_filepath (line 270) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 297) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 314) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 331) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method _get_opencv_camera (line 349) | def _get_opencv_camera(self, frame_annotation):
method load_intrinsics (line 398) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 464) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 510) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 543) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/generic_mvs_dataset.py
class GenericMVSDataset (line 21) | class GenericMVSDataset(Dataset):
method __init__ (line 49) | def __init__(
method __len__ (line 233) | def __len__(self):
method get_sub_folder_dir (line 237) | def get_sub_folder_dir(split):
method get_valid_frame_path (line 241) | def get_valid_frame_path(self, split, scan):
method get_valid_frame_ids (line 247) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method get_color_filepath (line 269) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 285) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 302) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 317) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 333) | def get_pose_filepath(self, scan_id, frame_id):
method get_frame_id_string (line 346) | def get_frame_id_string(self, frame_id):
method get_gt_mesh_path (line 355) | def get_gt_mesh_path(dataset_path, split, scan_id):
method load_intrinsics (line 361) | def load_intrinsics(self, scan_id, frame_id=None, flip=None):
method load_target_size_depth_and_mask (line 383) | def load_target_size_depth_and_mask(self, scan_id, frame_id):
method load_full_res_depth_and_mask (line 404) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 422) | def load_pose(self, scan_id, frame_id):
method load_color (line 438) | def load_color(self, scan_id, frame_id, crop=None):
method load_high_res_color (line 469) | def load_high_res_color(self, scan_id, frame_id):
method get_frame (line 497) | def get_frame(self, scan_id, frame_id, load_depth, flip=False):
method stack_src_data (line 676) | def stack_src_data(self, src_data):
method __getitem__ (line 689) | def __getitem__(self, idx):
FILE: src/mvsanywhere/datasets/hypersim.py
class HypersimDataset (line 17) | class HypersimDataset(GenericMVSDataset):
method __init__ (line 28) | def __init__(
method get_frame_id_string (line 125) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 134) | def get_valid_frame_path(self, split, scan):
method _get_frame_ids (line 151) | def _get_frame_ids(self, split, scan):
method _check_hypersim_img_not_anomalous (line 165) | def _check_hypersim_img_not_anomalous(self, img, threshold=0.3):
method get_valid_frame_ids (line 186) | def get_valid_frame_ids(self, split, scan, store_computed=False):
method get_color_filepath (line 271) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 310) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 336) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 353) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_full_res_distance_filepath (line 380) | def get_full_res_distance_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 406) | def get_pose_filepath(self, scan_id, frame_id):
method load_intrinsics (line 426) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 533) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 583) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method _get_cam_position (line 615) | def _get_cam_position(self, pose_path, frame):
method _get_cam_orientation (line 632) | def _get_cam_orientation(self, pose_path, frame):
method load_pose (line 649) | def load_pose(self, scan_id, frame_id):
method _get_M_cam_from_uv (line 715) | def _get_M_cam_from_uv(self, scan_id):
method _get_rays_hypersim_torch (line 749) | def _get_rays_hypersim_torch(self, intrinsics_inv, H, W):
method _get_prependicular_depths (line 786) | def _get_prependicular_depths(self, scan_id, frame_id):
method _save_prependicular_depths_to_disk (line 815) | def _save_prependicular_depths_to_disk(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/matrix_city.py
class MatrixCityDataset (line 18) | class MatrixCityDataset(GenericMVSDataset):
method __init__ (line 29) | def __init__(
method get_frame_id_string (line 137) | def get_frame_id_string(self, frame_id):
method format_frame_id (line 146) | def format_frame_id(self, scan, frame_id):
method get_valid_frame_path (line 158) | def get_valid_frame_path(self, split, scan):
method _load_transforms_file (line 173) | def _load_transforms_file(self, scan):
method _get_frame_ids (line 176) | def _get_frame_ids(self, split, scan):
method get_valid_frame_ids (line 182) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method get_color_filepath (line 266) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 298) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 319) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 336) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method load_intrinsics (line 361) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method _load_depth (line 434) | def _load_depth(depth_path):
method load_target_size_depth_and_mask (line 441) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 493) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 528) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/mvssynth.py
class MVSSynthDataset (line 13) | class MVSSynthDataset(GenericMVSDataset):
method __init__ (line 24) | def __init__(
method get_valid_frame_path (line 123) | def get_valid_frame_path(self, split, scan):
method get_valid_frame_ids (line 128) | def get_valid_frame_ids(self, split, scan, store_computed=False):
method get_color_filepath (line 174) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 190) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 204) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 219) | def get_pose_filepath(self, scan_id, frame_id):
method load_intrinsics (line 233) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 311) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_pose (line 351) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/nerf_dataset.py
class NeRFDataset (line 14) | class NeRFDataset(GenericMVSDataset):
method __init__ (line 25) | def __init__(
method get_frame_id_string (line 117) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 126) | def get_valid_frame_path(self, split, scan):
method get_valid_frame_ids (line 131) | def get_valid_frame_ids(self, split, scan, store_computed=False):
method get_color_filepath (line 190) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 206) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 222) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 236) | def get_pose_filepath(self, scan_id, frame_id):
method load_intrinsics (line 250) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 328) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 358) | def load_full_res_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_pose (line 388) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/nerfstudio_dataset.py
class NerfStudioDataset (line 15) | class NerfStudioDataset(GenericMVSDataset):
method __init__ (line 26) | def __init__(
method get_frame_id_string (line 129) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 138) | def get_valid_frame_path(self, split, scan):
method _get_frame_ids (line 153) | def _get_frame_ids(self, split, scan):
method get_valid_frame_ids (line 161) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method load_pose (line 232) | def load_pose(self, scan_id, frame_id):
method load_intrinsics (line 260) | def load_intrinsics(self, scan_id, frame_id, flip=None):
method load_capture_metadata (line 343) | def load_capture_metadata(self, scan_id):
method get_cached_depth_filepath (line 376) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_cached_confidence_filepath (line 392) | def get_cached_confidence_filepath(self, scan_id, frame_id, crop=None):
method get_full_res_depth_filepath (line 408) | def get_full_res_depth_filepath(self, scan_id, frame_id, crop=None):
method get_full_res_confidence_filepath (line 425) | def get_full_res_confidence_filepath(self, scan_id, frame_id):
method load_full_res_depth_and_mask (line 441) | def load_full_res_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_target_size_depth_and_mask (line 464) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method get_color_filepath (line 485) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 509) | def get_high_res_color_filepath(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/read_write_colmap_model.py
class Image (line 52) | class Image(BaseImage):
method qvec2rotmat (line 53) | def qvec2rotmat(self):
function read_next_bytes (line 78) | def read_next_bytes(fid, num_bytes, format_char_sequence, endian_charact...
function write_next_bytes (line 90) | def write_next_bytes(fid, data, format_char_sequence, endian_character="...
function read_cameras_text (line 106) | def read_cameras_text(path):
function read_cameras_binary (line 136) | def read_cameras_binary(path_to_model_file):
function write_cameras_text (line 171) | def write_cameras_text(cameras, path):
function write_cameras_binary (line 190) | def write_cameras_binary(cameras, path_to_model_file):
function read_images_text (line 207) | def read_images_text(path):
function read_images_binary (line 247) | def read_images_binary(path_to_model_file):
function write_images_text (line 297) | def write_images_text(images, path):
function write_images_binary (line 337) | def write_images_binary(images, path_to_model_file):
function read_points3D_text (line 358) | def read_points3D_text(path):
function read_points3D_binary (line 390) | def read_points3D_binary(path_to_model_file):
function write_points3D_text (line 428) | def write_points3D_text(points3D, path):
function write_points3D_binary (line 459) | def write_points3D_binary(points3D, path_to_model_file):
function detect_model_format (line 478) | def detect_model_format(path, ext):
function read_model (line 490) | def read_model(path, ext=""):
function write_model (line 512) | def write_model(cameras, images, points3D, path, ext=".bin"):
function qvec2rotmat (line 524) | def qvec2rotmat(qvec):
function rotmat2qvec (line 546) | def rotmat2qvec(R):
FILE: src/mvsanywhere/datasets/sailvos3d.py
class SAILVOS3DDataset (line 18) | class SAILVOS3DDataset(GenericMVSDataset):
method __init__ (line 29) | def __init__(
method get_frame_id_string (line 130) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 139) | def get_valid_frame_path(self, split, scan):
method _get_frame_ids (line 149) | def _get_frame_ids(self, split, scan):
method get_valid_frame_ids (line 153) | def get_valid_frame_ids(self, split, scan, store_computed=False):
method get_color_filepath (line 239) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 267) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 283) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 300) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method load_intrinsics (line 316) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method _load_rage_matrices (line 391) | def _load_rage_matrices(self, scan_id, frame_id):
method convert_ndc_depth_to_cam (line 411) | def convert_ndc_depth_to_cam(
method load_target_size_depth_and_mask (line 466) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method pixels_to_ndcs (line 523) | def pixels_to_ndcs(
method load_full_res_depth_and_mask (line 552) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 588) | def load_pose(self, scan_id, frame_id):
method compute_intrinsics_from_P (line 625) | def compute_intrinsics_from_P(P: np.ndarray, image_width: int, image_h...
FILE: src/mvsanywhere/datasets/scannet_dataset.py
class ScannetDataset (line 11) | class ScannetDataset(GenericMVSDataset):
method __init__ (line 77) | def __init__(
method get_sub_folder_dir (line 175) | def get_sub_folder_dir(split):
method get_frame_id_string (line 182) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 191) | def get_valid_frame_path(self, split, scan):
method get_valid_frame_ids (line 199) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method get_gt_mesh_path (line 297) | def get_gt_mesh_path(dataset_path, split, scan_id):
method get_color_filepath (line 309) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 336) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 364) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 387) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 406) | def get_pose_filepath(self, scan_id, frame_id):
method load_intrinsics (line 423) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 494) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 537) | def load_full_res_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_pose (line 576) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/tartanair.py
class TartanAirDataset (line 16) | class TartanAirDataset(GenericMVSDataset):
method __init__ (line 27) | def __init__(
method get_frame_id_string (line 124) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 133) | def get_valid_frame_path(self, split, scan):
method _get_frame_ids (line 148) | def _get_frame_ids(self, split, scan):
method get_valid_frame_ids (line 155) | def get_valid_frame_ids(self, split, scan, store_computed=False):
method get_color_filepath (line 238) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 271) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 292) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 309) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_full_res_classgt_filepath (line 330) | def get_full_res_classgt_filepath(self, scan_id, frame_id):
method get_pose_filepath (line 352) | def get_pose_filepath(self, scan_id, frame_id):
method load_intrinsics (line 367) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method load_target_size_depth_and_mask (line 435) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 499) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 531) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/vdr_dataset.py
class VDRDataset (line 18) | class VDRDataset(GenericMVSDataset):
method __init__ (line 31) | def __init__(
method get_sub_folder_dir (line 89) | def get_sub_folder_dir(split):
method get_frame_id_string (line 92) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 101) | def get_valid_frame_path(self, split, scan):
method get_valid_frame_ids (line 108) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method load_pose (line 178) | def load_pose(self, scan_id, frame_id):
method load_intrinsics (line 214) | def load_intrinsics(self, scan_id, frame_id, flip=None):
method load_capture_metadata (line 294) | def load_capture_metadata(self, scan_id):
method get_cached_depth_filepath (line 322) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_cached_confidence_filepath (line 355) | def get_cached_confidence_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 388) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_full_res_confidence_filepath (line 410) | def get_full_res_confidence_filepath(self, scan_id, frame_id):
method load_full_res_depth_and_mask (line 431) | def load_full_res_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_target_size_depth_and_mask (line 474) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method get_color_filepath (line 548) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 573) | def get_high_res_color_filepath(self, scan_id, frame_id):
FILE: src/mvsanywhere/datasets/vkitti.py
class VirtualKITTIDataset (line 15) | class VirtualKITTIDataset(GenericMVSDataset):
method __init__ (line 26) | def __init__(
method get_frame_id_string (line 123) | def get_frame_id_string(self, frame_id):
method get_valid_frame_path (line 132) | def get_valid_frame_path(self, split, scan):
method _get_frame_ids (line 147) | def _get_frame_ids(self, split, scan):
method get_valid_frame_ids (line 156) | def get_valid_frame_ids(self, split, scan, store_computed=True):
method get_color_filepath (line 238) | def get_color_filepath(self, scan_id, frame_id):
method get_high_res_color_filepath (line 275) | def get_high_res_color_filepath(self, scan_id, frame_id):
method get_cached_depth_filepath (line 298) | def get_cached_depth_filepath(self, scan_id, frame_id):
method get_full_res_depth_filepath (line 315) | def get_full_res_depth_filepath(self, scan_id, frame_id):
method get_full_res_classgt_filepath (line 338) | def get_full_res_classgt_filepath(self, scan_id, frame_id):
method load_intrinsics (line 361) | def load_intrinsics(self, scan_id, frame_id=None, flip=False):
method _load_depth (line 433) | def _load_depth(depth_path, is_float16=True):
method _load_classgt (line 438) | def _load_classgt(classgt_path, is_float16=True):
method load_target_size_depth_and_mask (line 442) | def load_target_size_depth_and_mask(self, scan_id, frame_id, crop=None):
method load_full_res_depth_and_mask (line 498) | def load_full_res_depth_and_mask(self, scan_id, frame_id):
method load_pose (line 528) | def load_pose(self, scan_id, frame_id):
FILE: src/mvsanywhere/experiment_modules/rmvd_mvsa.py
class MVSA_Wrapped (line 17) | class MVSA_Wrapped(nn.Module):
method __init__ (line 18) | def __init__(self, opts, use_refinement=False, **kwargs):
method input_adapter (line 38) | def input_adapter(self, images, keyview_idx, poses=None, intrinsics=No...
method forward (line 97) | def forward(
method output_adapter (line 159) | def output_adapter(self, model_output):
FILE: src/mvsanywhere/experiment_modules/sr_depth_model.py
class DepthModel (line 44) | class DepthModel(pl.LightningModule):
method __init__ (line 92) | def __init__(self, opts):
method compute_matching_feats (line 266) | def compute_matching_feats(
method get_heuristic_depth_range (line 321) | def get_heuristic_depth_range(self, cur_data, src_data):
method refine_depth_range (line 339) | def refine_depth_range(self, cur_data, src_data, outputs):
method forward (line 370) | def forward(
method compute_losses (line 593) | def compute_losses(self, cur_data, src_data, outputs):
method step (line 702) | def step(self, phase, batch, batch_idx):
method training_step (line 888) | def training_step(self, batch, batch_idx):
method validation_step (line 892) | def validation_step(self, batch, batch_idx):
method configure_optimizers (line 896) | def configure_optimizers(self):
FILE: src/mvsanywhere/losses.py
class MSGradientLoss (line 11) | class MSGradientLoss(nn.Module):
method __init__ (line 12) | def __init__(self, num_scales: int = 4):
method forward (line 17) | def forward(self, depth_gt: Tensor, depth_pred: Tensor) -> Tensor:
class ScaleInvariantLoss (line 39) | class ScaleInvariantLoss(jit.ScriptModule):
method __init__ (line 40) | def __init__(self, si_lambda: float = 0.85):
method forward (line 46) | def forward(self, log_depth_gt: Tensor, log_depth_pred: Tensor) -> Ten...
class NormalsLoss (line 54) | class NormalsLoss(nn.Module):
method forward (line 55) | def forward(self, normals_gt_b3hw: Tensor, normals_pred_b3hw: Tensor) ...
class MVDepthLoss (line 78) | class MVDepthLoss(nn.Module):
method __init__ (line 79) | def __init__(self, height, width):
method _check_warped_image (line 88) | def _check_warped_image(
method get_valid_mask (line 134) | def get_valid_mask(
method get_error_for_pair (line 174) | def get_error_for_pair(
method forward (line 211) | def forward(
FILE: src/mvsanywhere/modules/cost_volume.py
class CostVolumeManager (line 10) | class CostVolumeManager(nn.Module):
method __init__ (line 23) | def __init__(
method initialise_for_projection (line 52) | def initialise_for_projection(self, device=None):
method get_mask (line 74) | def get_mask(self, pix_coords_bk2hw):
method generate_depth_planes (line 97) | def generate_depth_planes(
method warp_features (line 133) | def warp_features(
method build_cost_volume (line 219) | def build_cost_volume(
method indices_to_disparity (line 317) | def indices_to_disparity(self, indices, depth_planes_bdhw):
method forward (line 322) | def forward(
method to_fast (line 365) | def to_fast(self) -> "FastCostVolumeManager":
class FastCostVolumeManager (line 374) | class FastCostVolumeManager(CostVolumeManager):
method __init__ (line 375) | def __init__(self, matching_height, matching_width, num_depth_bins=64,...
method warp_features (line 380) | def warp_features(
method build_cost_volume (line 468) | def build_cost_volume(
FILE: src/mvsanywhere/modules/depth_anything_blocks.py
function _make_scratch (line 13) | def _make_scratch(in_shape, out_shape, groups=1, expand=False):
function _make_fusion_block (line 46) | def _make_fusion_block(features, use_bn, size = None):
class ResidualConvUnit (line 58) | class ResidualConvUnit(nn.Module):
method __init__ (line 62) | def __init__(self, features, activation, bn):
method forward (line 90) | def forward(self, x):
class FeatureFusionBlock (line 116) | class FeatureFusionBlock(nn.Module):
method __init__ (line 120) | def __init__(self, features, activation, deconv=False, bn=False, expan...
method forward (line 147) | def forward(self, *xs, size=None):
class DPTHead (line 177) | class DPTHead(nn.Module):
method __init__ (line 178) | def __init__(
method set_prediction_scale (line 279) | def set_prediction_scale(self, prediction_scale):
method forward (line 285) | def forward(self, out_features, patch_h, patch_w):
method load_da_weights (line 328) | def load_da_weights(self, weights_path):
FILE: src/mvsanywhere/modules/feature_volume.py
class FeatureVolumeManager (line 12) | class FeatureVolumeManager(CostVolumeManager):
method __init__ (line 26) | def __init__(
method build_cost_volume (line 81) | def build_cost_volume(
method to_fast (line 358) | def to_fast(self) -> "FastFeatureVolumeManager":
class FastFeatureVolumeManager (line 368) | class FastFeatureVolumeManager(FeatureVolumeManager):
method __init__ (line 377) | def __init__(
method warp_features (line 432) | def warp_features(
method build_cost_volume (line 586) | def build_cost_volume(
FILE: src/mvsanywhere/modules/layers.py
function conv3x3 (line 7) | def conv3x3(
function conv1x1 (line 28) | def conv1x1(in_planes: int, out_planes: int, stride: int = 1, bias: bool...
class BasicBlock (line 33) | class BasicBlock(nn.Module):
method __init__ (line 36) | def __init__(
method forward (line 77) | def forward(self, x: Tensor) -> Tensor:
class TensorFormatter (line 97) | class TensorFormatter(nn.Module):
method __init__ (line 105) | def __init__(self):
method _expand_batch_with_channels (line 111) | def _expand_batch_with_channels(self, x):
method _reduce_batch_to_channels (line 120) | def _reduce_batch_to_channels(self, x):
method forward (line 130) | def forward(self, x, apply_func):
FILE: src/mvsanywhere/modules/networks.py
function double_basic_block (line 13) | def double_basic_block(num_ch_in, num_ch_out, num_repeats=2):
class DepthDecoderPP (line 20) | class DepthDecoderPP(nn.Module):
method __init__ (line 21) | def __init__(self, num_ch_enc, scales=range(4), num_output_channels=1,...
method forward (line 65) | def forward(self, input_features):
class CVEncoder (line 88) | class CVEncoder(nn.Module):
method __init__ (line 89) | def __init__(self, num_ch_cv, num_ch_enc, num_ch_outs):
method forward (line 110) | def forward(self, x, img_feats):
class MLP (line 120) | class MLP(nn.Module):
method __init__ (line 121) | def __init__(self, channel_list, disable_final_activation=False):
method forward (line 134) | def forward(self, x):
class ResnetMatchingEncoder (line 138) | class ResnetMatchingEncoder(nn.Module):
method __init__ (line 141) | def __init__(
method forward (line 188) | def forward(self, input_image):
class UNetMatchingEncoder (line 192) | class UNetMatchingEncoder(nn.Module):
method __init__ (line 193) | def __init__(self):
method forward (line 211) | def forward(self, x):
FILE: src/mvsanywhere/modules/networks_fast.py
class ConvBlock (line 6) | class ConvBlock(nn.Module):
method __init__ (line 7) | def __init__(self, in_ch, out_ch, use_elu=True, use_bn=False):
method forward (line 17) | def forward(self, x):
class ConvUpsampleAndConcatBlock (line 27) | class ConvUpsampleAndConcatBlock(nn.Module):
method __init__ (line 28) | def __init__(self, in_ch, out_ch, skip_chns, use_elu=True, use_bn=False):
method forward (line 36) | def forward(self, x, cat_feats):
class SkipDecoder (line 45) | class SkipDecoder(nn.Module):
method __init__ (line 46) | def __init__(self, input_channels, use_bn=False):
method forward (line 79) | def forward(self, features):
class SkipDecoderRegression (line 98) | class SkipDecoderRegression(SkipDecoder):
method __init__ (line 99) | def __init__(self, input_channels, use_bn=False):
method forward (line 134) | def forward(self, features):
FILE: src/mvsanywhere/modules/view_agnostic_feature_volume.py
class ViewAgnosticFeatureVolumeManager (line 12) | class ViewAgnosticFeatureVolumeManager(CostVolumeManager):
method __init__ (line 26) | def __init__(
method build_cost_volume (line 82) | def build_cost_volume(
method to_fast (line 381) | def to_fast(self) -> "FastViewAgnosticFeatureVolumeManager":
class FastViewAgnosticFeatureVolumeManager (line 391) | class FastViewAgnosticFeatureVolumeManager(ViewAgnosticFeatureVolumeMana...
method __init__ (line 400) | def __init__(
method warp_features (line 430) | def warp_features(
method build_cost_volume (line 584) | def build_cost_volume(
FILE: src/mvsanywhere/modules/vit_modules.py
class Attention (line 18) | class Attention(nn.Module):
method __init__ (line 19) | def __init__(
method forward (line 38) | def forward(self, x: torch.Tensor) -> torch.Tensor:
class PytorchMemEffAttention (line 53) | class PytorchMemEffAttention(Attention):
method forward (line 54) | def forward(self, x: torch.Tensor, attn_bias=None) -> torch.Tensor:
function use_memeffattn_in_model (line 67) | def use_memeffattn_in_model(model):
class DINOv2 (line 87) | class DINOv2(nn.Module):
method __init__ (line 95) | def __init__(
method forward (line 108) | def forward(self, x):
method load_da_weights (line 123) | def load_da_weights(self, weights_path):
class CostVolumePatchEmbed (line 133) | class CostVolumePatchEmbed(nn.Module):
method __init__ (line 135) | def __init__(
method forward (line 189) | def forward(self, x, img_feats):
method patch_embed (line 210) | def patch_embed(self, x):
class ViTCVEncoder (line 216) | class ViTCVEncoder(nn.Module):
method __init__ (line 218) | def __init__(
method forward (line 250) | def forward(self, x, img_feats):
method prepare_tokens_with_masks (line 273) | def prepare_tokens_with_masks(self, x, img_features, masks=None):
FILE: src/mvsanywhere/options.py
class DataOptions (line 10) | class DataOptions:
class Options (line 38) | class Options:
class OptionsHandler (line 257) | class OptionsHandler:
method __init__ (line 294) | def __init__(self, required_flags=[]):
method parse_and_merge_options (line 309) | def parse_and_merge_options(self, config_filepaths=None, ignore_cl_arg...
method populate_argparse (line 376) | def populate_argparse(self):
method check_required_items (line 390) | def check_required_items(self):
method merge_config_options (line 396) | def merge_config_options(self, config_options):
method merge_cl_args (line 404) | def merge_cl_args(self, cl_args):
method pretty_print_options (line 423) | def pretty_print_options(self):
method load_options_from_yaml (line 432) | def load_options_from_yaml(config_filepath):
method save_options_as_yaml (line 437) | def save_options_as_yaml(config_filepath, options):
function handle_backwards_compat (line 442) | def handle_backwards_compat(opts):
FILE: src/mvsanywhere/run_demo.py
function prepare_scan_files (line 149) | def prepare_scan_files(opts):
function init_model (line 208) | def init_model(opts):
function main (line 216) | def main(opts):
FILE: src/mvsanywhere/test.py
function main (line 129) | def main(opts):
FILE: src/mvsanywhere/test_rmvd.py
function main (line 16) | def main(opts):
FILE: src/mvsanywhere/tools/fusers_helper.py
class DepthFuser (line 14) | class DepthFuser:
method __init__ (line 15) | def __init__(self, gt_path="", fusion_resolution=0.04, max_fusion_dept...
class OurFuser (line 20) | class OurFuser(DepthFuser):
method __init__ (line 33) | def __init__(
method fuse_frames (line 64) | def fuse_frames(self, depths_b1hw, K_b44, cam_T_world_b44, color_b3hw):
method export_mesh (line 72) | def export_mesh(self, path, export_single_mesh=True):
method save_tsdf (line 78) | def save_tsdf(self, path):
method sample_tsdf (line 81) | def sample_tsdf(self, world_points_N3, what_to_sample="tsdf", sampling...
method get_mesh (line 98) | def get_mesh(self, export_single_mesh=True, convert_to_trimesh=True):
method get_mesh_pytorch3d (line 101) | def get_mesh_pytorch3d(self, scale_to_world=True, min_bounds_3=None, m...
class Open3DFuser (line 107) | class Open3DFuser(DepthFuser):
method __init__ (line 114) | def __init__(
method fuse_frames (line 141) | def fuse_frames(
method export_mesh (line 198) | def export_mesh(self, path, use_marching_cubes_mask=None):
method get_mesh (line 201) | def get_mesh(self, export_single_mesh=None, convert_to_trimesh=False):
method save_tsdf (line 209) | def save_tsdf(self, path):
function get_fuser (line 213) | def get_fuser(opts, scan):
class CustomOpen3dFuser (line 259) | class CustomOpen3dFuser(Open3DFuser):
method __init__ (line 260) | def __init__(self, extended_neg_truncation=False, *args, **kwargs):
method fuse_frames (line 286) | def fuse_frames(
method update_tsdf_for_voxels (line 372) | def update_tsdf_for_voxels(
method export_mesh (line 452) | def export_mesh(self, path, use_marching_cubes_mask=None, trim_tsdf_us...
method get_mesh (line 458) | def get_mesh(
method get_mesh_pytorch3d (line 491) | def get_mesh_pytorch3d(self, scale_to_world=True):
FILE: src/mvsanywhere/tools/keyframe_buffer.py
class DVMVS_Config (line 12) | class DVMVS_Config:
class DVMVS_TartanAir_Config (line 24) | class DVMVS_TartanAir_Config:
class DVMVS_MatrixCity_Config (line 36) | class DVMVS_MatrixCity_Config:
function is_pose_available (line 49) | def is_pose_available(pose):
function is_valid_pair (line 59) | def is_valid_pair(
function pose_distance (line 81) | def pose_distance(reference_pose, measurement_pose):
class KeyframeBuffer (line 100) | class KeyframeBuffer:
method __init__ (line 101) | def __init__(
method calculate_penalty (line 117) | def calculate_penalty(self, t_score, R_score):
method try_new_keyframe (line 127) | def try_new_keyframe(self, pose, image, dist_to_last_valid=None, index...
method get_best_measurement_frames (line 193) | def get_best_measurement_frames(self, n_requested_measurement_frames):
class SimpleBuffer (line 220) | class SimpleBuffer:
method __init__ (line 221) | def __init__(
method try_new_keyframe (line 231) | def try_new_keyframe(self, pose, image, index=None):
method get_measurement_frames (line 274) | def get_measurement_frames(self):
class OfflineKeyframeBuffer (line 279) | class OfflineKeyframeBuffer:
method __init__ (line 280) | def __init__(
method calculate_penalty (line 297) | def calculate_penalty(self, t_score, R_score):
method try_new_keyframe (line 307) | def try_new_keyframe(self, pose, image, index=None):
method get_best_measurement_frames (line 368) | def get_best_measurement_frames(self, n_requested_measurement_frames):
method get_best_measurement_frames_for_0index (line 394) | def get_best_measurement_frames_for_0index(self, n_requested_measureme...
FILE: src/mvsanywhere/tools/marching_cubes/ext.cpp
function PYBIND11_MODULE (line 4) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
FILE: src/mvsanywhere/tools/marching_cubes/marching_cubes_cpu.cpp
function MarchingCubesCpu (line 29) | std::tuple<at::Tensor, at::Tensor, at::Tensor> MarchingCubesCpu(
FILE: src/mvsanywhere/tools/marching_cubes/marching_cubes_utils.h
type Vertex (line 21) | struct Vertex {
function operator (line 34) | bool operator==(const Vertex& xyz) const {
function operator (line 39) | bool operator!=(const Vertex& xyz) const {
type Cube (line 48) | struct Cube {
function Vertex (line 101) | Vertex VertexInterp(
function HashVpair (line 138) | int64_t HashVpair(const int edge, int W, int H, int D) {
FILE: src/mvsanywhere/tools/mesh_renderer.py
class Renderer (line 31) | class Renderer:
method __init__ (line 37) | def __init__(self, height=480, width=640, flat_render=False, ambient_l...
method render (line 42) | def render(
method __call__ (line 76) | def __call__(self, height, width, intrinsics, pose, meshes):
method fix_pose (line 79) | def fix_pose(self, pose):
method mesh_opengl (line 89) | def mesh_opengl(self, mesh, mesh_material=None):
method delete (line 95) | def delete(self):
method render_mesh (line 98) | def render_mesh(
method render_mesh_cull_composite (line 141) | def render_mesh_cull_composite(self, alpha, **kwargs):
function render_colour (line 151) | def render_colour(renderer, meshes, world_T_cam, K, height=256, width=320):
class SmoothBirdsEyeCamera (line 161) | class SmoothBirdsEyeCamera:
method __init__ (line 166) | def __init__(
method get_bird_eye_trans (line 183) | def get_bird_eye_trans(
function get_cam_pose_from_lookat_and_loc (line 255) | def get_cam_pose_from_lookat_and_loc(
function camera_marker (line 282) | def camera_marker(
function get_image_box (line 470) | def get_image_box(
function create_lights_above_mesh (line 537) | def create_lights_above_mesh(mesh: trimesh.Trimesh, light_intensity: flo...
function create_light_array (line 553) | def create_light_array(light_type, center_loc, x_length=10.0, y_length=1...
function transform_trimesh (line 576) | def transform_trimesh(mesh, transform):
FILE: src/mvsanywhere/tools/partial_fuser.py
class PartialFuser (line 11) | class PartialFuser:
method __init__ (line 12) | def __init__(
method get_mesh (line 42) | def get_mesh(self, query_frame_id: int):
method fuse_all_frames (line 85) | def fuse_all_frames(self):
FILE: src/mvsanywhere/tools/tsdf.py
function get_frustum_bounds (line 15) | def get_frustum_bounds(
class TSDF (line 53) | class TSDF:
method __init__ (line 62) | def __init__(
method from_file (line 87) | def from_file(cls, tsdf_file):
method from_mesh (line 100) | def from_mesh(cls, mesh: trimesh.Trimesh, voxel_size: float):
method from_bounds (line 123) | def from_bounds(cls, bounds: dict, voxel_size: float):
method generate_voxel_coords (line 157) | def generate_voxel_coords(
method cuda (line 168) | def cuda(self):
method cpu (line 175) | def cpu(self):
method to_mesh (line 182) | def to_mesh(self, scale_to_world=True, export_single_mesh=False):
method to_mesh_pytorch3d (line 216) | def to_mesh_pytorch3d(self, scale_to_world=True, min_bounds_3=None, ma...
method save_mesh (line 257) | def save_mesh(self, savepath, filename):
method save_tsdf (line 267) | def save_tsdf(self, filepath):
method sample_tsdf (line 277) | def sample_tsdf(self, world_points_N3, what_to_sample="tsdf", sampling...
class TSDFFuser (line 342) | class TSDFFuser:
method __init__ (line 347) | def __init__(self, tsdf, min_depth=0.5, max_depth=5.0, use_gpu=True):
method voxel_coords_3hwd (line 374) | def voxel_coords_3hwd(self):
method voxel_hashset (line 378) | def voxel_hashset(self):
method tsdf_values (line 382) | def tsdf_values(self):
method tsdf_weights (line 386) | def tsdf_weights(self):
method voxel_size (line 390) | def voxel_size(self):
method shape (line 394) | def shape(self):
method truncation (line 398) | def truncation(self):
method project_to_camera (line 401) | def project_to_camera(self, cam_T_world_T_144, K_144, valid_voxels_14N):
method integrate_depth (line 414) | def integrate_depth(
FILE: src/mvsanywhere/tools/tuple_generator.py
function compute_offline_tuple (line 63) | def compute_offline_tuple(
function default_dvmvs_tuples (line 159) | def default_dvmvs_tuples(scan, poses, dists_to_last_valid, n_measurement...
function offline_dvmvs_tuples (line 213) | def offline_dvmvs_tuples(scan, poses, n_measurement_frames):
function dense_dvmvs_tuples (line 262) | def dense_dvmvs_tuples(scan, poses, n_measurement_frames):
function offline_dense_dvmvs_tuples (line 336) | def offline_dense_dvmvs_tuples(scan, poses, n_measurement_frames):
function crawl_subprocess_long (line 374) | def crawl_subprocess_long(opts, scan, count, progress):
FILE: src/mvsanywhere/train.py
function prepare_dataloaders (line 37) | def prepare_dataloaders(opts: options.Options) -> Tuple[List[DataLoader]...
function prepare_callbacks (line 114) | def prepare_callbacks(
function prepare_model (line 143) | def prepare_model(opts: options.Options) -> torch.nn.Module:
function prepare_ddp_strategy (line 185) | def prepare_ddp_strategy(opts: options.Options) -> Strategy:
function prepare_trainer (line 199) | def prepare_trainer(
function main (line 241) | def main(opts):
FILE: src/mvsanywhere/utils/augmentation_utils.py
class CustomColorJitter (line 13) | class CustomColorJitter(torch.nn.Module):
method __init__ (line 16) | def __init__(
method forward (line 33) | def forward(self, x: torch.Tensor, denormalize_first=False) -> torch.T...
FILE: src/mvsanywhere/utils/cropping_utils.py
function find_image_bounding_box (line 4) | def find_image_bounding_box(image: np.ndarray) -> tuple[int, int, int, i...
function find_image_collection_bounding_box (line 47) | def find_image_collection_bounding_box(images: list[np.ndarray]) -> tupl...
function tightly_crop_images (line 68) | def tightly_crop_images(images: list[np.ndarray]):
FILE: src/mvsanywhere/utils/dataset_utils.py
function get_dataset (line 20) | def get_dataset(dataset_name, split_filepath, single_debug_scan_id=None,...
FILE: src/mvsanywhere/utils/generic_utils.py
function copy_code_state (line 18) | def copy_code_state(path):
function readlines (line 40) | def readlines(filepath):
function normalize_depth_single (line 47) | def normalize_depth_single(depth_11hw, mask_11hw, robust=False):
function normalize_depth (line 77) | def normalize_depth(depth_b1hw: torch.Tensor, mask_b1hw: torch.Tensor = ...
function pyrdown (line 89) | def pyrdown(input_tensor: torch.Tensor, num_scales: int = 4):
function upsample (line 98) | def upsample(x):
function batched_trace (line 110) | def batched_trace(mat_bNN):
function tensor_B_to_bM (line 114) | def tensor_B_to_bM(tensor_BS, batch_size, num_views):
function tensor_bM_to_B (line 125) | def tensor_bM_to_B(tensor_bMS):
function combine_dims (line 137) | def combine_dims(x, dim_begin, dim_end):
function to_gpu (line 143) | def to_gpu(input_dict, key_ignores=[]):
function imagenet_normalize (line 153) | def imagenet_normalize(image):
function reverse_imagenet_normalize (line 159) | def reverse_imagenet_normalize(image):
function fov_to_image_dimension (line 170) | def fov_to_image_dimension(fov_degrees: float, focal_length: float) -> f...
function crop_or_pad (line 177) | def crop_or_pad(image_bchw, new_height, new_width, pad_mode="constant"):
function read_image_file (line 224) | def read_image_file(
function read_pfm_file (line 280) | def read_pfm_file(
function crop_image_to_target_ratio (line 348) | def crop_image_to_target_ratio(image, target_aspect_ratio=4.0 / 3.0):
function cache_model_outputs (line 380) | def cache_model_outputs(
function get_generic_eps (line 431) | def get_generic_eps(tensor: Optional[Any] = None):
FILE: src/mvsanywhere/utils/geometry_utils.py
function to_homogeneous (line 12) | def to_homogeneous(input_tensor: Tensor, dim: int = 0) -> Tensor:
class BackprojectDepth (line 22) | class BackprojectDepth(jit.ScriptModule):
method __init__ (line 28) | def __init__(self, height: int, width: int):
method forward (line 55) | def forward(self, depth_b1hw: Tensor, invK_b44: Tensor) -> Tensor:
class Project3D (line 66) | class Project3D(jit.ScriptModule):
method __init__ (line 71) | def __init__(self, eps: float = 1e-8):
method forward (line 77) | def forward(self, points_b4N: Tensor, K_b44: Tensor, cam_T_world_b44: ...
class NormalGenerator (line 96) | class NormalGenerator(jit.ScriptModule):
method __init__ (line 97) | def __init__(
method forward (line 117) | def forward(self, depth_b1hw: Tensor, invK_b44: Tensor) -> Tensor:
function get_angle_dif (line 149) | def get_angle_dif(matA_b33, matB_b33):
function get_camera_rays (line 157) | def get_camera_rays(
function pose_distance (line 191) | def pose_distance(pose_b44):
function qvec2rotmat (line 206) | def qvec2rotmat(qvec):
function rotx (line 231) | def rotx(t):
function roty (line 240) | def roty(t):
function rotz (line 249) | def rotz(t):
FILE: src/mvsanywhere/utils/metrics_utils.py
function compute_depth_metrics (line 7) | def compute_depth_metrics(gt, pred, mult_a=False):
function compute_depth_metrics_batched (line 51) | def compute_depth_metrics_batched(gt_bN, pred_bN, valid_masks_bN, mult_a...
class ResultsAverager (line 122) | class ResultsAverager:
method __init__ (line 127) | def __init__(self, exp_name, metrics_name):
method update_results (line 142) | def update_results(self, elem_metrics):
method print_sheets_friendly (line 162) | def print_sheets_friendly(
method output_json (line 200) | def output_json(self, filepath, print_running_metrics=False):
method load_scores (line 236) | def load_scores(self, filepath, print_running_metrics=False):
method pretty_print_results (line 252) | def pretty_print_results(self, print_exp_name=True, print_running_metr...
method compute_final_average (line 275) | def compute_final_average(self, ignore_nans=False):
FILE: src/mvsanywhere/utils/model_utils.py
function get_model_class (line 10) | def get_model_class(opts):
function load_model_inference (line 18) | def load_model_inference(opts, model_class_to_use):
function load_model_training (line 62) | def load_model_training(opts, model_class_to_use):
FILE: src/mvsanywhere/utils/pytorch3d_extras.py
class _marching_cubes (line 20) | class _marching_cubes(Function):
method forward (line 28) | def forward(ctx, vol, isolevel, active_voxels, min_bounds, max_bounds):
method backward (line 35) | def backward(ctx, grad_verts, grad_faces):
function marching_cubes (line 39) | def marching_cubes(
FILE: src/mvsanywhere/utils/rendering_utils.py
class PyTorch3DMeshDepthRenderer (line 9) | class PyTorch3DMeshDepthRenderer:
method __init__ (line 10) | def __init__(self, height=192, width=256) -> None:
method render (line 25) | def render(self, mesh, cam_T_world_b44, K_b44):
function load_and_preprocess_mesh_for_rendering (line 50) | def load_and_preprocess_mesh_for_rendering(
FILE: src/mvsanywhere/utils/visualization_utils.py
function colormap_image (line 15) | def colormap_image(
function image_tensor3hw_to_numpyhw3 (line 75) | def image_tensor3hw_to_numpyhw3(
function tile_images (line 93) | def tile_images(
function save_viz_video_frames (line 200) | def save_viz_video_frames(frame_list, path, fps=30):
function quick_viz_export (line 210) | def quick_viz_export(
function load_and_merge_images (line 323) | def load_and_merge_images(frame_ids, quick_viz_directory, fps=30):
FILE: src/mvsanywhere/utils/volume_utils.py
class SimpleVolume (line 10) | class SimpleVolume:
method __init__ (line 18) | def __init__(
method from_bounds (line 46) | def from_bounds(cls, bounds: dict, voxel_size: float):
method generate_voxel_coords_3hwd (line 96) | def generate_voxel_coords_3hwd(
method load (line 116) | def load(cls, filepath) -> Any:
method save (line 127) | def save(self, filepath):
method cuda (line 137) | def cuda(self):
method cpu (line 144) | def cpu(self):
method to_point_cloud (line 151) | def to_point_cloud(self, threshold: Optional[float] = None, num_points...
method sample_volume (line 185) | def sample_volume(self, world_points_N3):
method project_volume_to_camera (line 239) | def project_volume_to_camera(self, cam_T_world_b44: torch.Tensor, K_b4...
class VisibilityAggregator (line 253) | class VisibilityAggregator:
method __init__ (line 254) | def __init__(self, volume: SimpleVolume, additional_extent: float = 0.3):
method integrate_into_volume (line 264) | def integrate_into_volume(
FILE: src/regsplatfacto/regsplatfacto/data/mvsanywhere_dataset.py
class MVSAnywhereDataset (line 20) | class MVSAnywhereDataset(InputDataset):
method __init__ (line 30) | def __init__(
method _predict_all_depths_and_normals (line 56) | def _predict_all_depths_and_normals(self, depth_path: Path) -> tuple[n...
method _get_depth_and_normal_estimate (line 185) | def _get_depth_and_normal_estimate(self, image_idx: int) -> dict[str, ...
method get_data (line 227) | def get_data(self, image_idx: int, image_type: Literal["uint8", "float...
FILE: src/regsplatfacto/regsplatfacto/data/regsplatfacto_datamanager.py
class RegSplatfactoDatamanagerConfig (line 13) | class RegSplatfactoDatamanagerConfig(FullImageDatamanagerConfig):
class RegSplatfactoDatamanager (line 25) | class RegSplatfactoDatamanager(FullImageDatamanager):
method __init__ (line 34) | def __init__(self, config: RegSplatfactoDatamanagerConfig, **kwargs):
method _depth_model_to_dataset (line 38) | def _depth_model_to_dataset(self, depth_model: str):
method dataset_type (line 45) | def dataset_type(self):
method create_train_dataset (line 48) | def create_train_dataset(self):
method create_eval_dataset (line 63) | def create_eval_dataset(self):
FILE: src/regsplatfacto/regsplatfacto/meshing.py
function fuse_npz_folder (line 14) | def fuse_npz_folder(renders_path: Path, fuser: Open3DFuser, key_to_fuse_...
function main (line 54) | def main(
function entrypoint (line 129) | def entrypoint() -> None:
FILE: src/regsplatfacto/regsplatfacto/regsplatfacto_model.py
function get_points_on_sphere (line 25) | def get_points_on_sphere(N: int, radius: float = 250.0) -> torch.Tensor:
class RegSplatfactoModelConfig (line 49) | class RegSplatfactoModelConfig(SplatfactoModelConfig):
method __post_init__ (line 101) | def __post_init__(self) -> None:
class RegSplatfactoModel (line 127) | class RegSplatfactoModel(SplatfactoModel):
method populate_modules (line 140) | def populate_modules(self):
method get_skybox_param_groups (line 174) | def get_skybox_param_groups(self) -> Dict[str, List[Parameter]]:
method get_param_groups (line 180) | def get_param_groups(self) -> Dict[str, List[Parameter]]:
method skybox_means (line 193) | def skybox_means(self):
method skybox_scales (line 197) | def skybox_scales(self):
method skybox_quats (line 201) | def skybox_quats(self):
method skybox_features_dc (line 205) | def skybox_features_dc(self):
method skybox_opacities (line 209) | def skybox_opacities(self):
method split_gaussians (line 212) | def split_gaussians(self, split_mask, samps) -> dict[str, torch.Tensor]:
method get_rasterized_outputs (line 267) | def get_rasterized_outputs(self, camera: Cameras) -> dict[str, torch.T...
method get_outputs (line 401) | def get_outputs(self, camera: Cameras) -> dict[str, torch.Tensor | lis...
method get_loss_dict (line 434) | def get_loss_dict(
method _get_normal_generator (line 526) | def _get_normal_generator(self, height: int, width: int) -> NormalGene...
method _get_intrinsics (line 542) | def _get_intrinsics(self, camera: Cameras) -> torch.Tensor:
method _get_implied_normal_from_depth (line 560) | def _get_implied_normal_from_depth(
method compute_scale_regularisation_loss_median (line 590) | def compute_scale_regularisation_loss_median(self) -> torch.Tensor:
method compute_flat_loss (line 628) | def compute_flat_loss(self) -> torch.Tensor:
method compute_depth_loss (line 642) | def compute_depth_loss(self, pred_depth: torch.Tensor, gt_depth: torch...
method compute_metric_depth_loss (line 659) | def compute_metric_depth_loss(
method compute_scale_invariant_depth_loss (line 682) | def compute_scale_invariant_depth_loss(
method compute_normal_loss (line 697) | def compute_normal_loss(
method _get_gt_depth_and_normal (line 721) | def _get_gt_depth_and_normal(
FILE: src/regsplatfacto/regsplatfacto/render_for_meshing.py
function compute_mapping_from_nerfstudio_to_world (line 57) | def compute_mapping_from_nerfstudio_to_world(
class DatasetRenderMeshing (line 74) | class DatasetRenderMeshing(BaseRender):
method main (line 94) | def main(self) -> None:
function entrypoint (line 245) | def entrypoint():
function get_parser_fn (line 255) | def get_parser_fn():
FILE: src/regsplatfacto/regsplatfacto/utils.py
function to_homogeneous (line 18) | def to_homogeneous(input_tensor: torch.Tensor, dim: int = 0) -> torch.Te...
class BackprojectDepth (line 28) | class BackprojectDepth(nn.Module):
method __init__ (line 34) | def __init__(self, height: int, width: int) -> None:
method forward (line 53) | def forward(self, depth_b1hw: torch.Tensor, invK_b44: torch.Tensor) ->...
class Project3D (line 65) | class Project3D(nn.Module):
method __init__ (line 70) | def __init__(self, eps: float = 1e-8):
method forward (line 75) | def forward(
class NormalGenerator (line 96) | class NormalGenerator(nn.Module):
method __init__ (line 97) | def __init__(
method forward (line 111) | def forward(self, depth_b1hw: torch.Tensor, invK_b44: torch.Tensor) ->...
function force_to_hw3 (line 127) | def force_to_hw3(array: np.ndarray) -> np.ndarray:
Copy disabled (too large)
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Condensed preview — 197 files, each showing path, character count, and a content snippet. Download the .json file for the full structured content (52,195K chars).
[
{
"path": ".gitignore",
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"preview": "*.pyc\n.vscode/\ndebug_scripts/\ndebug_dump\nlogs/\nlogs\nmodels/*.ckpt\nweights/*.ckpt\n**__pycache__**\n\nlogs\nresults\n\n.mypy_ca"
},
{
"path": "LICENSE",
"chars": 8614,
"preview": "Copyright © Niantic, Inc. 2025. Patent Pending.\n\nAll rights reserved.\n\n\n\n==============================================="
},
{
"path": "Makefile",
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"preview": "SHELL = /bin/bash\n\nSYSTEM_NAME := $(shell uname)\nSYSTEM_ARCHITECTURE := $(shell uname -m)\nMAMBA_INSTALL_SCRIPT := Minifo"
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"chars": 18310,
"preview": "# MVSAnywhere: Zero Shot Multi-View Stereo\n\nA multi-view stereo depth estimation model which works anywhere, in any scen"
},
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{
"path": "data_splits/mvssynth/train_scans.txt",
"chars": 584,
"preview": "0000\n0001\n0002\n0003\n0004\n0005\n0006\n0007\n0008\n0009\n0010\n0011\n0012\n0013\n0014\n0015\n0016\n0017\n0018\n0019\n0020\n0021\n0022\n0023\n"
},
{
"path": "data_splits/mvssynth/val_eight_view_deepvmvs.txt",
"chars": 107999,
"preview": "0000 0000 0001 0002 0003 0004 0005 0006 0007\n0000 0000 0001 0002 0003 0004 0005 0006 0007\n0000 0000 0001 0002 0003 0004 "
},
{
"path": "data_splits/mvssynth/val_scans.txt",
"chars": 14,
"preview": "0117\n0118\n0119"
},
{
"path": "data_splits/sailvos3d/split_train.txt",
"chars": 2192,
"preview": "ah_1_mcs_1\nah_3a_mcs_3\nah_3a_mcs_6\narm_2_mcs_4\narmenian_1_mcs_1\narmenian_2_mcs_6\narmenian_3_int\narmenian_3_mcs_3\narmenia"
},
{
"path": "data_splits/sailvos3d/train_eight_view_deepvmvs.txt",
"chars": 1439052,
"preview": "franklin_1_int 000518 000490 000459 000467 000527 000505 000492 000534\nexile_2_int 000227 000600 000606 000184 000564 00"
},
{
"path": "data_splits/tartanair/all_scans.txt",
"chars": 8141,
"preview": "seasidetown/Hard/P002\nseasidetown/Hard/P000\nseasidetown/Hard/P001\nseasidetown/Hard/P004\nseasidetown/Hard/P003\nseasidetow"
},
{
"path": "data_splits/tartanair/train_scans.txt",
"chars": 7579,
"preview": "seasidetown/Hard/P002\nseasidetown/Hard/P000\nseasidetown/Hard/P001\nseasidetown/Hard/P004\nseasidetown/Hard/P003\nseasidetow"
},
{
"path": "data_splits/tartanair/val_eight_view_deepvmvs_bd.txt",
"chars": 168480,
"preview": "carwelding/Hard/P001 000546_left 000548_left 000550_left 000552_left 000553_left 000554_left 000555_left 000556_left\ncar"
},
{
"path": "data_splits/tartanair/val_scans.txt",
"chars": 209,
"preview": "carwelding/Hard/P002\ncarwelding/Hard/P000\ncarwelding/Hard/P001\ncarwelding/Hard/P003\ncarwelding/Easy/P006\ncarwelding/Easy"
},
{
"path": "data_splits/vdr/scans.txt",
"chars": 17,
"preview": "living_room\nhouse"
},
{
"path": "data_splits/vdr/test_eight_view_deepvmvs.txt",
"chars": 33208,
"preview": "house 12 0 3 6 7 5 2 11\nhouse 17 0 12 10 3 13 11 1\nhouse 21 12 17 0 16 4 11 3\nhouse 25 21 12 17 0 1 16 3\nhouse 29 25 12 "
},
{
"path": "data_splits/vdr/test_eight_view_deepvmvs_dense.txt",
"chars": 93727,
"preview": "living_room 1 0 0 0 0 0 0 0\nliving_room 2 1 0 0 1 1 0 1\nliving_room 3 1 2 0 2 0 0 0\nliving_room 4 1 0 2 3 2 3 1\nliving_r"
},
{
"path": "data_splits/vdr/test_eight_view_deepvmvs_dense_offline.txt",
"chars": 94398,
"preview": "living_room 0 20 17 23 26 30 33 35\nliving_room 1 20 17 23 26 30 33 35\nliving_room 2 20 17 23 26 30 33 35\nliving_room 3 2"
},
{
"path": "data_splits/vkitti/matrix_city_train.json",
"chars": 2,
"preview": "{}"
},
{
"path": "data_splits/vkitti/train_eight_view_deepvmvs.txt",
"chars": 1862125,
"preview": "Scene01/15-deg-left 321 311 229 312 313 311 320 303\nScene20/30-deg-left 726 708 707 716 722 707 709 704\nScene06/30-deg-l"
},
{
"path": "data_splits/vkitti/vkitti_train.txt",
"chars": 845,
"preview": "Scene18/morning\nScene18/30-deg-right\nScene18/rain\nScene18/sunset\nScene18/fog\nScene18/15-deg-right\nScene18/15-deg-left\nSc"
},
{
"path": "environment.yml",
"chars": 937,
"preview": "name: mvsanywhere\nchannels:\n - default\n - pytorch\n - nvidia/label/cuda-11.8.0\n - conda-forge\n - pytorch3d\ndependenc"
},
{
"path": "eval.py",
"chars": 7427,
"preview": "#!/usr/bin/env python3\n\nimport argparse\nimport sys\nimport os.path as osp\n\nimport torch\n\nfrom rmvd import create_model, l"
},
{
"path": "hubconf.py",
"chars": 11014,
"preview": "dependencies = ['torch']\n\nfrom pathlib import Path\nfrom typing import Optional, Union\n\nfrom PIL import Image\nimport nump"
},
{
"path": "pyproject.toml",
"chars": 432,
"preview": "[tool.black]\nline-length = 100\n\n[tool.isort]\nprofile = \"black\"\n\n[tool.mypy]\nwarn_unused_configs = true\nignore_missing_im"
},
{
"path": "scripts/create_visibility_volume.py",
"chars": 10419,
"preview": "import os\nfrom pathlib import Path\n\nimport click\nimport numpy as np\nimport open3d as o3d\nimport torch\nimport torchvision"
},
{
"path": "scripts/data_scripts/filter_hypersim_scenes.py",
"chars": 825,
"preview": "import numpy as np\n\nTUPLES_FILE = \"data_splits/hypersim/bd_split/{}_eight_view_deepvmvs_bd.txt\"\nFILTER_FILE = \"data_spli"
},
{
"path": "scripts/data_scripts/fix_nerfcapture_filenames.py",
"chars": 1004,
"preview": "import json\nimport tyro\nfrom pathlib import Path\n\n\ndef fix_nerfcapture_filenames(\n data_path: Path,\n):\n \"\"\"\n Lo"
},
{
"path": "scripts/data_scripts/generate_blendedmvg_tuples.py",
"chars": 2109,
"preview": "import sys\nimport random\nimport numpy as np\nfrom pathlib import Path\nfrom mvsanywhere import options\nfrom mvsanywhere.ut"
},
{
"path": "scripts/data_scripts/generate_hypersim_planar_depths.py",
"chars": 3566,
"preview": "\"\"\"Script for generating planar depth maps for the Hypersim Dataset\n\n Run like so for generating/saving depth maps to"
},
{
"path": "scripts/data_scripts/generate_matrix_scans.py",
"chars": 1702,
"preview": "import glob\nimport json\nfrom pathlib import Path\nfrom collections import defaultdict\n\nimport numpy as np\n\nfrom mvsanywhe"
},
{
"path": "scripts/data_scripts/generate_test_tuples.py",
"chars": 21022,
"preview": "\"\"\"Script for generating DeeoVideoMVS multiview lists in the split folder \n indicated. It will export these frame tup"
},
{
"path": "scripts/data_scripts/generate_train_tuples.py",
"chars": 16496,
"preview": "\"\"\"Script for generating DeeoVideoMVS multiview lists in the split folder\n indicated. It will export these frame tupl"
},
{
"path": "scripts/data_scripts/generate_train_tuples_geometry.py",
"chars": 10648,
"preview": "\"\"\"Script for generating geometry-based multiview lists in the split folder\n indicated. It will export these frame tu"
},
{
"path": "scripts/data_scripts/precompute_valid_frames.py",
"chars": 4897,
"preview": "\"\"\"Script for precomputing and storing a list of valid frames per scan. A valid \n frame is defined as one that has an"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/LICENSE",
"chars": 1192,
"preview": "The LICENSE applies only to reader.py and SensorData.py.\n\nCopyright 2017 \nAngela Dai, Angel X. Chang, Manolis Savva, Mac"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/README.md",
"chars": 4352,
"preview": "# Downloading and Extracting ScanNetv2\n\n\nDeveloped and tested with python 3.9.\n\nThe included license at LICENSE applies "
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/SensorData.py",
"chars": 7549,
"preview": "import os, struct\nimport numpy as np\nimport zlib\nimport imageio\nimport cv2\nimport png\nfrom PIL import Image\nfrom context"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/download_scannet.py",
"chars": 13620,
"preview": "#!/usr/bin/env python\n# Downloads ScanNet public data release\n# Run with ./download-scannet.py (or python download-scann"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/env.yml",
"chars": 147,
"preview": "name: scannet_extraction\ndependencies:\n - python=3.9.7\n - numpy\n - imageio\n - pillow\n - tqdm\n - pip\n - pip:\n -"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/reader.py",
"chars": 3273,
"preview": "import argparse\nfrom concurrent.futures import process\nimport os, sys\nfrom tqdm import tqdm\nfrom multiprocessing.pool im"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/splits/scannetv2_test.txt",
"chars": 1300,
"preview": "scene0707_00\nscene0708_00\nscene0709_00\nscene0710_00\nscene0711_00\nscene0712_00\nscene0713_00\nscene0714_00\nscene0715_00\nsce"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/splits/scannetv2_train.txt",
"chars": 15613,
"preview": "scene0191_00\nscene0191_01\nscene0191_02\nscene0119_00\nscene0230_00\nscene0528_00\nscene0528_01\nscene0705_00\nscene0705_01\nsce"
},
{
"path": "scripts/data_scripts/scannet_wrangling_scripts/splits/scannetv2_val.txt",
"chars": 4056,
"preview": "scene0568_00\nscene0568_01\nscene0568_02\nscene0304_00\nscene0488_00\nscene0488_01\nscene0412_00\nscene0412_01\nscene0217_00\nsce"
},
{
"path": "scripts/data_scripts/undistort_nerfstudio_data.py",
"chars": 4385,
"preview": "import numpy as np\nimport cv2\nfrom pathlib import Path\nfrom PIL import Image\nimport tyro\nimport json\nimport tqdm\nimport "
},
{
"path": "scripts/dust3r_waymo_preprocess.py",
"chars": 19339,
"preview": "#!/usr/bin/env python3\n# Copyright (C) 2024-present Naver Corporation. All rights reserved.\n# Licensed under CC BY-NC-SA"
},
{
"path": "scripts/evals/mesh_eval.py",
"chars": 10530,
"preview": "from collections import OrderedDict\nfrom pathlib import Path\nimport sys, os\n\nimport time\nimport argparse\nimport torch\nim"
},
{
"path": "scripts/evaluation.py",
"chars": 1598,
"preview": "import subprocess\nfrom pathlib import Path\n\nimport click\nfrom loguru import logger\n\n\n@click.group()\ndef run():\n pass\n"
},
{
"path": "scripts/render_scripts/render_meshes.py",
"chars": 16742,
"preview": "import torch\n\nfrom pathlib import Path\n\nfrom mvsanywhere.datasets.scannet_dataset import ScannetDataset\nfrom mvsanywhere"
},
{
"path": "scripts/strip_checkpoint.py",
"chars": 783,
"preview": "# for importing options on checkpoint load.\nimport sys\n\nsys.path.append(\"/\".join(sys.path[0].split(\"/\")[:-1]))\n\nimport t"
},
{
"path": "setup.py",
"chars": 321,
"preview": "import setuptools\n\n__version__ = \"0.1.0\"\n\nsetuptools.setup(\n name=\"mvsanywhere\",\n version=__version__,\n descrip"
},
{
"path": "simple_demo.py",
"chars": 1662,
"preview": "# Simple demo showing how to use the model using torch.hub\n\nimport torch\nimport numpy as np\nfrom PIL import Image\nimport"
},
{
"path": "src/mvsanywhere/datasets/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "src/mvsanywhere/datasets/blendedmvg.py",
"chars": 14710,
"preview": "import os\n\nimport numpy as np\nimport PIL.Image as pil\nimport torch\n\nfrom mvsanywhere.datasets.generic_mvs_dataset import"
},
{
"path": "src/mvsanywhere/datasets/change_of_basis.py",
"chars": 2494,
"preview": "import numpy as np\n\n\nclass ChangeOfBasis:\n LANDSCAPE_TO_PORTRAIT = np.array(\n [\n [0.0, -1.0, 0.0, 0"
},
{
"path": "src/mvsanywhere/datasets/colmap_dataset.py",
"chars": 17490,
"preview": "import functools\nimport logging\nimport os\nfrom pathlib import Path\n\nimport numpy as np\nimport PIL.Image as pil\nimport to"
},
{
"path": "src/mvsanywhere/datasets/dynamic_replica.py",
"chars": 21758,
"preview": "from collections import defaultdict\nimport os\nfrom pathlib import Path\n\nfrom dataclasses import dataclass\nimport gzip\nfr"
},
{
"path": "src/mvsanywhere/datasets/generic_mvs_dataset.py",
"chars": 28592,
"preview": "import logging\nimport os\nimport random\n\nimport numpy as np\nimport PIL.Image as pil\nimport torch\nfrom torch.utils.data im"
},
{
"path": "src/mvsanywhere/datasets/hypersim.py",
"chars": 28972,
"preview": "import os\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nimport torch\nimport h5p"
},
{
"path": "src/mvsanywhere/datasets/matrix_city.py",
"chars": 20534,
"preview": "import os\nfrom pathlib import Path\nimport glob\nimport json\n\nfrom mvsanywhere.datasets.change_of_basis import ChangeOfBas"
},
{
"path": "src/mvsanywhere/datasets/mvssynth.py",
"chars": 15519,
"preview": "import os\n\nos.environ[\"OPENCV_IO_ENABLE_OPENEXR\"] = \"1\"\nimport json\nfrom pathlib import Path\n\nimport numpy as np\nimport "
},
{
"path": "src/mvsanywhere/datasets/nerf_dataset.py",
"chars": 15994,
"preview": "import os\n\nimport json\nfrom pathlib import Path\n\nimport numpy as np\nimport torch\n\nfrom mvsanywhere.datasets.generic_mvs_"
},
{
"path": "src/mvsanywhere/datasets/nerfstudio_dataset.py",
"chars": 19658,
"preview": "import os\nfrom pathlib import Path\n\nimport numpy as np\nimport torch\nfrom scipy.spatial.transform import Rotation as R\nim"
},
{
"path": "src/mvsanywhere/datasets/read_write_colmap_model.py",
"chars": 21457,
"preview": "# Copyright (c), ETH Zurich and UNC Chapel Hill.\n# All rights reserved.\n#\n# Redistribution and use in source and binary "
},
{
"path": "src/mvsanywhere/datasets/sailvos3d.py",
"chars": 23735,
"preview": "import os\nfrom pathlib import Path\n\nfrom mvsanywhere.datasets.change_of_basis import ChangeOfBasis\n\nos.environ[\"OPENCV_I"
},
{
"path": "src/mvsanywhere/datasets/scannet_dataset.py",
"chars": 22621,
"preview": "import os\n\nimport numpy as np\nimport PIL.Image as pil\nimport torch\n\nfrom mvsanywhere.datasets.generic_mvs_dataset import"
},
{
"path": "src/mvsanywhere/datasets/tartanair.py",
"chars": 19480,
"preview": "import os\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image\nimport torch\nimport cv2"
},
{
"path": "src/mvsanywhere/datasets/vdr_dataset.py",
"chars": 21655,
"preview": "import functools\nimport json\nimport logging\nimport os\n\nimport numpy as np\nimport PIL.Image as pil\nimport torch\nimport to"
},
{
"path": "src/mvsanywhere/datasets/vkitti.py",
"chars": 19702,
"preview": "import os\nfrom pathlib import Path\nimport json\n\nos.environ[\"OPENCV_IO_ENABLE_OPENEXR\"]=\"1\"\n\nimport numpy as np\nfrom PIL "
},
{
"path": "src/mvsanywhere/experiment_modules/rmvd_mvsa.py",
"chars": 5347,
"preview": "import sys\nfrom pathlib import Path\nfrom dataclasses import dataclass\n\nimport torch\nimport torch.nn as nn\nfrom torchvisi"
},
{
"path": "src/mvsanywhere/experiment_modules/sr_depth_model.py",
"chars": 42046,
"preview": "import logging\n\nimport lightning as pl\nimport timm\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\nimp"
},
{
"path": "src/mvsanywhere/losses.py",
"chars": 8225,
"preview": "import kornia\nimport torch\nimport torch.jit as jit\nimport torch.nn.functional as F\nfrom torch import Tensor, nn\n\nfrom mv"
},
{
"path": "src/mvsanywhere/modules/cost_volume.py",
"chars": 19724,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch import Tensor\nimport einops\n\nfrom mvsanywh"
},
{
"path": "src/mvsanywhere/modules/depth_anything_blocks.py",
"chars": 11010,
"preview": "from loguru import logger\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nmodel_configs = {\n 'din"
},
{
"path": "src/mvsanywhere/modules/feature_volume.py",
"chars": 29111,
"preview": "import einops\nimport torch\nimport torch.nn.functional as F\nfrom torch import Tensor\n\nfrom mvsanywhere.modules.cost_volum"
},
{
"path": "src/mvsanywhere/modules/layers.py",
"chars": 4178,
"preview": "from typing import Callable, Optional\n\nimport torch.nn as nn\nfrom torch import Tensor\n\n\ndef conv3x3(\n in_planes: int,"
},
{
"path": "src/mvsanywhere/modules/networks.py",
"chars": 6917,
"preview": "import antialiased_cnns\nimport numpy as np\nimport timm\nimport torch\nfrom torch import nn\nfrom torchvision import models\n"
},
{
"path": "src/mvsanywhere/modules/networks_fast.py",
"chars": 4828,
"preview": "import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass ConvBlock(nn.Module):\n def __init__(self, "
},
{
"path": "src/mvsanywhere/modules/view_agnostic_feature_volume.py",
"chars": 30611,
"preview": "import einops\nimport torch\nimport torch.nn.functional as F\nfrom torch import Tensor\n\nfrom mvsanywhere.modules.cost_volum"
},
{
"path": "src/mvsanywhere/modules/vit_modules.py",
"chars": 9234,
"preview": "from loguru import logger\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom mvsanywhere.modules.d"
},
{
"path": "src/mvsanywhere/options.py",
"chars": 16552,
"preview": "import argparse\nimport dataclasses\nimport os\nfrom dataclasses import dataclass\nfrom typing import List\nimport yaml\n\n\n@da"
},
{
"path": "src/mvsanywhere/run_demo.py",
"chars": 25059,
"preview": "\"\"\"\n Predicts depth maps using a DepthModel model. Uses an MVS dataset from\n datasets.\n\n All results will be st"
},
{
"path": "src/mvsanywhere/test.py",
"chars": 20179,
"preview": "\"\"\"\n Predicts depth maps using a DepthModel model. Uses an MVS dataset from\n datasets.\n\n All results will be st"
},
{
"path": "src/mvsanywhere/test_rmvd.py",
"chars": 1970,
"preview": "\"\"\"\n Test script for evaluating MVSAnywhere on the Robust Multi-View Depth Benchmark\n\n\"\"\"\n\n\nimport os\nimport torch\n\ni"
},
{
"path": "src/mvsanywhere/tools/fusers_helper.py",
"chars": 18701,
"preview": "import numpy as np\nfrom open3d import core as o3c\nimport open3d as o3d\nimport torch\nimport trimesh\nfrom pytorch3d.render"
},
{
"path": "src/mvsanywhere/tools/keyframe_buffer.py",
"chars": 15472,
"preview": "\"\"\"\nMost of this is a modified version of code from the DeepVideoMVS repository\nat https://github.com/ardaduz/deep-video"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/ext.cpp",
"chars": 147,
"preview": "#include <torch/extension.h>\n#include \"marching_cubes.h\"\n\nPYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {\n m.def(\"marching_c"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/marching_cubes.cu",
"chars": 23016,
"preview": "/*\n * Copyright (c) Meta Platforms, Inc. and affiliates.\n * All rights reserved.\n *\n * This source code is licensed unde"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/marching_cubes.h",
"chars": 2279,
"preview": "/*\n * Copyright (c) Meta Platforms, Inc. and affiliates.\n * All rights reserved.\n *\n * This source code is licensed unde"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/marching_cubes_cpu.cpp",
"chars": 4029,
"preview": "/*\n * Copyright (c) Meta Platforms, Inc. and affiliates.\n * All rights reserved.\n *\n * This source code is licensed unde"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/marching_cubes_utils.h",
"chars": 4622,
"preview": "/*\n * Copyright (c) Meta Platforms, Inc. and affiliates.\n * All rights reserved.\n *\n * This source code is licensed unde"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/pytorch3d_cutils.h",
"chars": 523,
"preview": "/*\n * Copyright (c) Meta Platforms, Inc. and affiliates.\n * All rights reserved.\n *\n * This source code is licensed unde"
},
{
"path": "src/mvsanywhere/tools/marching_cubes/tables.h",
"chars": 15153,
"preview": "/*\n * Copyright (c) Meta Platforms, Inc. and affiliates.\n * All rights reserved.\n *\n * This source code is licensed unde"
},
{
"path": "src/mvsanywhere/tools/mesh_renderer.py",
"chars": 18401,
"preview": "import os\n\nos.environ[\"PYOPENGL_PLATFORM\"] = \"egl\"\n\nimport sys\n\nimport numpy as np\nimport pyrender\nimport trimesh\nimport"
},
{
"path": "src/mvsanywhere/tools/partial_fuser.py",
"chars": 3789,
"preview": "import os\nimport pickle\nfrom collections import OrderedDict\nfrom pathlib import Path\n\nimport torch\n\nfrom mvsanywhere.too"
},
{
"path": "src/mvsanywhere/tools/tsdf.py",
"chars": 20069,
"preview": "import os\nfrom typing import Tuple\n\nimport numpy as np\nimport open3d as o3d\nimport torch\nimport torch.nn.functional as T"
},
{
"path": "src/mvsanywhere/tools/tuple_generator.py",
"chars": 18086,
"preview": "\"\"\"Script for generating DeeoVideoMVS multiview lists in the split folder \n indicated. It will export these frame tup"
},
{
"path": "src/mvsanywhere/train.py",
"chars": 10358,
"preview": "\"\"\" \n Trains a DepthModel model. Uses an MVS dataset from datasets.\n\n - Outputs logs and checkpoints to opts.log_d"
},
{
"path": "src/mvsanywhere/utils/augmentation_utils.py",
"chars": 1636,
"preview": "from typing import List, Tuple, Union\n\nimport kornia\nimport torch\nfrom torch import Tensor\n\nfrom mvsanywhere.utils.gener"
},
{
"path": "src/mvsanywhere/utils/cropping_utils.py",
"chars": 2157,
"preview": "import numpy as np\n\n\ndef find_image_bounding_box(image: np.ndarray) -> tuple[int, int, int, int]:\n \"\"\"Finds the bound"
},
{
"path": "src/mvsanywhere/utils/dataset_utils.py",
"chars": 8795,
"preview": "import json\nimport os\nfrom pathlib import Path\n\nfrom mvsanywhere.datasets.blendedmvg import BlendedMVGDataset\nfrom mvsan"
},
{
"path": "src/mvsanywhere/utils/generic_utils.py",
"chars": 14544,
"preview": "import logging\nimport re\nimport os\nimport pickle\nfrom pathlib import Path\nfrom typing import Any, Optional\n\nimport korni"
},
{
"path": "src/mvsanywhere/utils/geometry_utils.py",
"chars": 7547,
"preview": "import kornia\nimport numpy as np\nimport torch\nimport torch.jit as jit\nimport torch.nn.functional as F\nfrom torch import "
},
{
"path": "src/mvsanywhere/utils/metrics_utils.py",
"chars": 9415,
"preview": "import json\n\nimport numpy as np\nimport torch\n\n\ndef compute_depth_metrics(gt, pred, mult_a=False):\n \"\"\"\n Computes e"
},
{
"path": "src/mvsanywhere/utils/model_utils.py",
"chars": 3855,
"preview": "import torch\nfrom loguru import logger\n\nfrom mvsanywhere.modules.cost_volume import CostVolumeManager\nfrom mvsanywhere.m"
},
{
"path": "src/mvsanywhere/utils/pytorch3d_extras.py",
"chars": 4158,
"preview": "from typing import List, Optional, Tuple\n\nimport torch\nfrom pytorch3d.transforms import Translate\nfrom torch.autograd im"
},
{
"path": "src/mvsanywhere/utils/rendering_utils.py",
"chars": 2121,
"preview": "from pathlib import Path\n\nimport torch\nimport trimesh\nfrom pytorch3d.renderer import MeshRasterizer, RasterizationSettin"
},
{
"path": "src/mvsanywhere/utils/visualization_utils.py",
"chars": 13490,
"preview": "import math\nimport os\nfrom typing import Union\n\nimport cv2\nimport matplotlib.pyplot as plt\nimport moviepy.editor as mpy\n"
},
{
"path": "src/mvsanywhere/utils/volume_utils.py",
"chars": 12055,
"preview": "from typing import Any, Optional\n\nimport numpy as np\nimport open3d as o3d\nimport torch\n\nfrom mvsanywhere.utils.geometry_"
},
{
"path": "src/regsplatfacto/pyproject.toml",
"chars": 440,
"preview": "[project]\nname = \"regsplatfacto\"\nversion = \"0.0.1\"\n\n[tool.setuptools.packages.find]\ninclude = [\"regsplatfacto*\"]\n\n[tool."
},
{
"path": "src/regsplatfacto/regsplatfacto/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "src/regsplatfacto/regsplatfacto/data/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "src/regsplatfacto/regsplatfacto/data/mvsanywhere_dataset.py",
"chars": 9563,
"preview": "import warnings\nfrom pathlib import Path\nfrom typing import Literal\n\nimport numpy as np\nimport torch\nfrom nerfstudio.dat"
},
{
"path": "src/regsplatfacto/regsplatfacto/data/py.typed",
"chars": 0,
"preview": ""
},
{
"path": "src/regsplatfacto/regsplatfacto/data/regsplatfacto_datamanager.py",
"chars": 2936,
"preview": "from dataclasses import dataclass, field\nfrom typing import Generic, Type\n\nfrom nerfstudio.data.datamanagers.full_images"
},
{
"path": "src/regsplatfacto/regsplatfacto/meshing.py",
"chars": 5455,
"preview": "from pathlib import Path\n\nimport numpy as np\nimport open3d as o3d\nimport torch\nimport tqdm\nimport tyro\nfrom nerfstudio.u"
},
{
"path": "src/regsplatfacto/regsplatfacto/regsplatfacto_config.py",
"chars": 3785,
"preview": "\"\"\"\nRegSplatfacto configuration file.\n\"\"\"\n\nfrom nerfstudio.configs.base_config import ViewerConfig\nfrom nerfstudio.data."
},
{
"path": "src/regsplatfacto/regsplatfacto/regsplatfacto_model.py",
"chars": 32327,
"preview": "\"\"\"\nRegularised Splatfacto Model\n\"\"\"\n\nfrom __future__ import annotations\n\nfrom dataclasses import dataclass, field\nfrom "
},
{
"path": "src/regsplatfacto/regsplatfacto/render_for_meshing.py",
"chars": 10679,
"preview": "# Copyright 2022 the Regents of the University of California, Nerfstudio Team and contributors. All rights reserved.\n#\n#"
},
{
"path": "src/regsplatfacto/regsplatfacto/utils.py",
"chars": 4417,
"preview": "\"\"\" Taken from SimpleRecon\"\"\"\nimport kornia\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\nfrom torch i"
}
]
// ... and 5 more files (download for full content)
About this extraction
This page contains the full source code of the nianticlabs/mvsanywhere GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 197 files (112.7 MB), approximately 12.7M tokens, and a symbol index with 764 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.