Metadata-Version: 2.1
Name: mitransient
Version: 1.0.3
Summary: Transient rendering extensions for Mitsuba 3
Home-page: https://github.com/diegoroyo/mitsuba3-transient-nlos
Author: Diego Royo, Miguel Crespo, Jorge García
Author-email: droyo@unizar.es
License: BSD
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: mitsuba >=3.5.0

<div align="center">
<img align="center" src="https://github.com/mitsuba-renderer/mitsuba2/raw/master/docs/images/logo_plain.png" width="90" height="90"/>
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<!-- PROJECT LOGO -->
<p align="center">
  <h1 align="center">Transient Mitsuba 3</h1>

  <p align="center">
    <a href="https://diego.contact"><strong>Diego Royo</strong></a>
    &nbsp;&nbsp;&nbsp;&nbsp;
    <a href="https://mcrespo.me"><strong>Miguel Crespo</strong></a>
    &nbsp;&nbsp;&nbsp;&nbsp;
    <a href="https://jgarciapueyo.github.io/"><strong>Jorge García</strong></a>
  </p>
</p>

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  <img src="https://raw.githubusercontent.com/diegoroyo/mitsuba3-transient-nlos/main/.images/cornell-box.png" width="200" height="200"/>
  <img src="https://raw.githubusercontent.com/diegoroyo/mitsuba3-transient-nlos/main/.images/cornell-box.gif" width="200" height="200"/>
  <img src="https://raw.githubusercontent.com/diegoroyo/mitsuba3-transient-nlos/main/.images/nlos-Z.png" width="200" height="200"/>
  <img src="https://raw.githubusercontent.com/diegoroyo/mitsuba3-transient-nlos/main/.images/nlos-Z.gif" width="200" height="200"/>
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# Overview

This library adds support to [Mitsuba 3](https://github.com/mitsuba-renderer/mitsuba3) for doing transient simulations, with amazing support for non-line-of-sight (NLOS) data capture simulations.

### Main features
* **Cross-platform:** Mitsuba 3 has been tested on Linux (x86_64), macOS (aarch64, x86_64), and Windows (x86_64).
* **Easy interface** to convert your algorithms for the transient domain.
* **Temporal domain** filtering.
* **Python-only** library for doing transient rendering in both CPU and GPU.
* **Several integrators have already been implemented** including path tracing (also adapted for NLOS scenes) and volumetric path-tracing.

<br>

> **ℹ️ Check out our examples about how to use our library!** <br>
> Featuring [General Usage](https://github.com/diegoroyo/mitsuba3-transient-nlos/tree/main/examples), [Line-of-sight transient rendering](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/examples/transient/render_cbox_diffuse.ipynb), and [Non-line-of-sight transient rendering](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/examples/transient-nlos/mitsuba3-transient-nlos.ipynb)

<br>

# License and citation

This project was created by [Miguel Crespo](https://mcrespo.me) and expanded by [Diego Royo](https://diego.contact) and [Jorge García](https://jgarciapueyo.github.io/).

If you use our code in your project, please consider citing us using the following:

```bibtex
@misc{mitsuba3transient,
	title        = {Transient Mitsuba 3},
	author       = {Royo, Diego and Crespo, Miguel and Garcia, Jorge},
	year         = 2023,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/diegoroyo/mitsuba3-transient-nlos}}
}
```

Additionally, the NLOS features were re-implemented from our publication [Non-line-of-sight transient rendering](https://doi.org/10.1016/j.cag.2022.07.003). Please also consider citing us if you use them:

```bibtex
@article{royo2022non,
	title        = {Non-line-of-sight transient rendering},
	author       = {Diego Royo and Jorge García and Adolfo Muñoz and Adrian Jarabo},
	year         = 2022,
	journal      = {Computers & Graphics},
	doi          = {https://doi.org/10.1016/j.cag.2022.07.003},
	issn         = {0097-8493},
	url          = {https://www.sciencedirect.com/science/article/pii/S0097849322001200}
}
```

# What is transient rendering?

Conventional rendering is referred to as steady state, where the light propagation speed is assumed to be infinite. In contrast, transient rendering breaks this assumption allowing us to simulate light in motion (see the teaser image for a visual example).

For example, path tracing algorithms integrate over multiple paths that connect a light source with the camera. For a known path, transient path tracing uses the *very complex* formula of `time = distance / speed` (see [[Two New Sciences by Galileo]](https://en.wikipedia.org/wiki/Two_New_Sciences)) to compute the `time` when each photon arrives at the camera from the path's `distance` and light's `speed`. This adds a new `time` dimension to the captured images (i.e. it's a video now). The simulations now take new parameters as input: when to start recording the video, how long is each time step (framerate), and how many frames to record.

*Note: note that the `time` values we need to compute are very small (e.g. light takes only ~3.33 * 10^-9 seconds to travel 1 meter), `time` is usually measured in optical path distance. See [Wikipedia](https://en.wikipedia.org/wiki/Optical_path_length) for more information. TL;DR `opl = distance * refractive_index`*

# Roadmap

**Last update: Apr. 2024*

- [ ] Importance sampling of the temporal domain
- [ ] Differentiable transient rendering
- [ ] Fluorescence BRDF
- [X] Non-line-of-sight support (NLOS)
  - [X] `max_depth`
  - [X] `filter_depth`
  - [X] `discard_direct_paths`
  - [ ] `auto_detect_bins`
  - [ ] Faster implementation of exhaustive scanning


# Installation

We provide the package via PyPI. To install `mitsuba3-transient-nlos` you need to run:

```bash
pip install mitransient
```

If you have installed Mitsuba 3 via `pip` you will only have access to the `llvm_ad_rgb` and `cuda_ad_rgb` variants. If you want to use other variants (e.g. NLOS simulations can greatly benefit from the `llvm_mono` variant which only propagates one wavelength), then we recommend that you compile Mitsuba 3 yourself [following this tutorial](https://mitsuba.readthedocs.io/en/latest/src/developer_guide/compiling.html) and enable the following variants: `["scalar_mono", "llvm_mono", "llvm_ad_mono", "cuda_mono", "cuda_ad_mono", "scalar_rgb", "llvm_rgb", "llvm_ad_rgb", "cuda_rgb", "cuda_ad_rgb"]`.

## Requirements

- `Python >= 3.8`
- `Mitsuba3 >= 3.5.0`
- (optional) For computation on the GPU: `Nvidia driver >= 495.89`
- (optional) For vectorized / parallel computation on the CPU: `LLVM >= 11.1`

## After installation

At this point, you should be able to `import mitsuba` and `import mitransient` in your Python code (careful about setting the correct `PATH` environment variable if you have compiled Mitsuba 3 yourself, see the section below).

For NLOS data capture simulations, see https://github.com/diegoroyo/tal. `tal` is a toolkit that allows you to create and simulate NLOS scenes with an easier shell interface instead of directly from Python.

### If you use your own Mitsuba 3

If you have opted for using a custom (non-default installation through `pip`) Mitsuba 3, you have several options for it. The idea here is to be able to control which version of Mitsuba will be loaded on demand.

* One solution is to directly execute `setpath.sh` provided after the compilation of the Mitsuba 3 repo [(More info)](https://mitsuba.readthedocs.io/en/latest/src/developer_guide/compiling.html). This shell script will modify the `PATH` and `PYTHONPATH` variables to load first this version of Mitsuba.
* Another solution following the previous one is to directly set yourself the `PYTHONPATH` environment variable as you wish.
* Another solution for having a custom version globally available is by using `pip install . --editable`. This will create a symlink copy of the package files inside the corresponding `site-packages` folder and will be listed as a package installed of `pip` and will be available as other packages installed. If you recompile them, you will still have the newest version directly to use. Please follow these instructions:
  * Go to `<mitsuba-path>/mitsuba3/build/python/drjit` and execute `pip install . --editable`.
  * Go to `<mitsuba-path>/mitsuba3/build/python/mitsuba` and execute `pip install . --editable`.
* If you are a user of Jupyter Notebooks, the easiest solution will be to add the following snippet of code to modify the notebook's `PYTHONPATH`:
```python
import sys
sys.path.insert(0, '<mitsuba-path>/mitsuba3/build/python')
import mitsuba as mi
```

# Usage

> **ℹ️ Check out the `examples` folder for practical usage!** <br>

As of November 2023, `mitsuba3-transient-nlos` implements the following plugins which can be used in scene XML files. To view a description of their parameters, click on the name of your desired plugin.
* `film`:
  * [`transient_hdr_film`](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/mitransient/films/transient_hdr_film.py): Transient equivalent of Mitsuba 3's `hdrfilm` plugin.
* `integrators`:
  * [`transient_path`](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/mitransient/integrators/transientpath.py): Transient path tracing for line-of-sight scenes. If you want to do NLOS simulations, use `transientnlospath` instead.
  * [`transient_nlos_path`](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/mitransient/integrators/transientnlospath.py): Transient path tracing with specific sampling routines for NLOS scenes (e.g. laser sampling and hidden geometry sampling of the ["Non-Line-of-Sight Transient Rendering" paper](https://diego.contact/publications/nlos-render)).
  * [`transient_prbvolpath`](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/mitransient/integrators/transient_prb_volpath.py): Path Replay Backpropagation for volumetric path tracing. Implemented by Miguel Crespo, untested.
* `sensor`:
  * [`nlos_capture_meter`](https://github.com/diegoroyo/mitsuba3-transient-nlos/blob/main/mitransient/sensors/nloscapturemeter.py): Can be attached to one of the scene's geometries, and measures uniformly-spaced points on such geometry (e.g. relay wall).

## Testing

Our test suite can be run using `pytest` on the root folder of the repo.
