About
Nori 2 is a minimalistic ray tracer written in C++. It runs
on Windows, Linux, and Mac OS and provides a foundation for
the homework assignments in the course
Computer Graphics taught at ETH Zürich.
While Nori provides much support code to simplify your development
work as much as possible, the code that you will initially receive
from us does very little: it loads a scene and saves a rendered image
as an OpenEXR image—but
the actual rendering code is missing, hence the output image just
consists of black pixels.
Your task will be to extend this system to a full-fledged physically-based
renderer as part of programming assignments and your final project.
Core features
The Nori base code provides many features that would be tedious
to implement from scratch. The following are included:
- A simple GUI to watch images as they render
- An XML-based scene file loader
- Basic point/vector/normal/ray/bounding box classes
- A pseudorandom number generator (PCG32)
- Support for saving output as OpenEXR files
- A loader for Wavefront OBJ files
- An optimized bounding volume hierarchy builder
- Ray-triangle intersection
- Code for multi-threaded rendering
- Image reconstruction filters
- Statistical \(\chi^2\)- and \(t\)-tests to verify sampling code
Guidelines
Permissible sources of information
Feel free to consult additional references
when completing projects, but remember cite them in your writeup.
When asked to implement feature \(X\), we request that you don't
go and read the source code of the implementation of \(X\) in some other renderer,
because you will likely not learn much in the process. The PBRT book
is excluded from this rule.
If in doubt, get in touch with the course staff.
References
You may find the following general references useful:
- "Physically Based Rendering, Third Edition: From Theory To Implementation" by Matt Pharr, Wenzel Jakob and Greg Humphreys. Available Online, October 2018.
- "Advanced Global Illumination" by Philip Dutré, Philippe Bekaert, and Kavita Bala. AK Peters, 2nd edition, August 2006.
- "Robust Monte Carlo Methods for Light Transport Simulation ", PhD Thesis by Eric Veach, Stanford University, December 1997.
Instructions
The assignments have to be solved and submitted individually. The final project can be done in groups of two.
More information about the final project and the rendering competition will come later in the semester.
The deadlines are specified for each assignment. These are the dates to submit your exercises (code and
report).
To get graded you need to submit on time according to the late policy.
We aim to complete grading until one week after the deadline.
The goal of these exercises is to help you create the foundation of a good renderer for subsequent
assignments and the final projects. It is your job to convince us that you have implemented
the assignments correctly, through the information provided in your reports and the quality/readability
of your code. We will deduct points for poorly written code or inconclusive comparisons/validations in
your report. Make sure to start working on the homework as early as possible. Building your own
advanced renderer is a lot of fun. Use this great opportunity, and don’t forget to have fun!
Note: Undeclared copying of code or images (either
from other students or from external sources) is strictly prohibited! Any violation of this rule
will lead to expulsion from the class. If you're ever in doubt, just include a citation in your
code or report indicating where some idea came from, whether it be a web site, another piece of
software, or anything—this always maintains your honesty, whether the source was used in a good
way or not. When you turn your assignment in, you are claiming that everything in it is your
original idea unless you cite a source for it.
Submissions
We will be using GitLab with a commit hash submission on Moodle to gather your submissions.
Every time there is something to submit, you will be provided a link to the assignment submission.
Continuous Integration (CI) testing
Your GitLab repositories are CI-enabled and, once triggered, a
Pipeline will be created
that first compiles your code and then optionally runs the tests for the selected assignment.
The pipeline can be triggered in one of these ways:
-
By pushing a commit with a message that contains "[PA#]",
e.g. "[PA1] Implementing average visibility". A tag
of [PA{1,2,3,4}] will run the respective tests, while
[PA0] will only compile the code.
-
Manually through the web interface (Build > Pipelines > Run Pipeline) to
run the compile job. You can also choose to run assignment tests from there.
We will run the pipeline on your submission commit after every assignment.
While we do not strictly require that you run and pass the pipeline,
failed CI pipeline
is most likely caused by other problems with your code or repository that can be grounds for point reduction!
The jobs are run by shared runners hosted by
D-INFK ISG.
They are a shared resource so please use them responsibly,
e.g. do not use the CI as a replacement for
local testing. There is a possibility that other users slow down or even block the whole build process,
especially near the assignment deadlines.
Late policy
Please submit your work on time and follow the respective instructions.
Late submissions can be accepted and graded without penalties only for valid reasons (e.g. military service or hospitalization) with written proof prior to the deadline.
Otherwise, the submission will be graded with penalties. More specifically, we multiply the grades with a scale factor that depends on the submission time.
The submission time is defined as the time point when the last submission is made on Moodle (not the time of the commit!).
The scale factor is defined as follows, depending on how long the submission is overdue.
- under 6h*: 90%
- 6h - 12h: 80%
- 12h - 24h: 60%
- 24h - 36h: 40%
- 36h - 48h: 20%
- More than 48h: 0% (the submission is likely not graded)
* if the submission is made within 1 hour of the deadline, the penalty will be waived once (only the first occurrence in the semester)
In case of technical issues with GitLab or Moodle near the deadline, you may submit the local commit hash by e-mail.
But be aware that you will be required to provide a repository that contains this hash.