Introduction
FFmpeg is the universal multimedia toolkit: a complete, cross-platform solution to record, convert, filter, and stream audio and video. It is used by a number of media players (including VLC and MPlayer), video websites (including YouTube and Vimeo), web browsers (including Google Chrome/Chromium and Firefox), social media (including Facebook and Twitter) and countless other software projects in the multimedia field and beyond.
This is our ideas page for Google Summer of Code 2017. See the GSoC Timeline for important dates.
Information for Students
Getting Started
- Get to know FFmpeg. If you are a student interested in contributing to FFmpeg, it is recommended to start by subscribing to the ffmpeg-devel mailing-list, visiting our FreeNode IRC channels (#ffmpeg-devel and #ffmpeg although you will find most developers on the first one), and exploring both the codebase and the development workflow. Feel free to contact us if you have any questions. Also do not hesitate to answer questions from other students on our IRC channel if you know the answer to something.
- Find a project. Listed on this page are mentored and un-mentored projects. Mentored projects are well-defined and mentor(s) have already volunteered. Un-mentored projects are additional ideas you may want to consider, but you will have to contact us to find a mentor. You can also propose your own project, if you can think of one that better fits your interest and skill level. If a project description is unclear or you have any questions, please get in touch with its mentor and/or join our IRC channel at #ffmpeg-devel.
- Contact us. If you decide on a project, get in touch with the community and let us know. If you want to work on a qualification task, let the respective mentor know so we can avoid duplicated efforts.
- Apply. Students should apply by April 3 at the very latest. The "work" period begins on May 30 and ends in August. Take a look at GSoC timeline for additional information. Note, make sure you apply to Google before the 3rd even if you have not yet finished your qualification task. And please apply as soon as possible: Applications can be improved until the 3rd but not afterwards!
Note: A friendly reminder that while the application to GSoC is important for you and GSoC, FFmpeg mentors will not base their decision solely on the GSoC application. We will judge the applicant based on their abilities in coding, learning the tools, communication skills etc. So please do not worry about your application being perfect for us. Although it is very important to follow GSoC's application rules so they can pay you.
Qualification Tasks
In order to get accepted you normally have to complete a small qualification task. FFmpeg development can be quite challenging and the qualification task helps us figure out whether you are motivated enough and have the potential to deliver successfully.
The qualification tasks are usually shown in the project description. Contact the respective mentor(s) for assistance on getting a related qualification task or if you want to propose your own. You can also browse the FFmpeg Bug Tracker for qualification task ideas. In general qualification tasks should include submitting a patch to the ffmpeg-devel mailing list which passes review and is accepted into the FFmpeg codebase. It will be common for such patches to need multiple iterations of submissions and reviews, so don't wait too long with the first submission! Note, please avoid picking a qualification task which another student is already working on, each student should work on a different qualification task.
Contacting FFmpeg
If you have questions or comments feel free to contact us via our mailing list, IRC channel, or e-mail one of the FFmpeg GSoC admins:
- Mailing-list: ffmpeg-devel
- IRC: #ffmpeg-devel on Freenode
- FFmpeg GSoC Admins: Michael Niedermayer (michaelni in #ffmpeg-devel on Freenode IRC, michaelni@gmx.at), Reynaldo Verdejo (reynaldo in #ffmpeg-devel on Freenode IRC, R Verdejo on g mail), Carl Eugen Hoyos (cehoyos in #ffmpeg-devel on Freenode IRC, cehoyos at ag dot or dot at)
You may also contact a mentor directly if you have questions specifically related to one of the projects listed on this page.
Mentored Projects
This section lists well-defined projects that have one or more available mentors. If you are new to FFmpeg, and have relatively little experience with multimedia, you should favor a mentored project rather than propose your own. Contact the respective mentor(s) to get more information about the project and the requested qualification task.
FITS image decoder and encoder
Description: Flexible Image Transport System (FITS) is an open standard defining a digital file format useful for storage, transmission and processing of scientific and other images. FITS is the most commonly used digital file format in astronomy.
Expected results: Fully working decoder and encoder.
Prerequisites: C coding skills, basic familiarity with git.
Qualification Task: XPM decoder implemented in libavcodec
Alternative Qualification Task: add native DWA/DWB decompression in libavcodec OpenEXR implementation
Mentor: Paul B Mahol (durandal_1707 in #ffmpeg-devel on Freenode IRC, onemda@gmail.com)
Backup mentor: Rostislav Pehlivanov (atomnuker in #ffmpeg-devel on Freenode IRC, atomnuker@gmail.com)
VMAF video filter
Description: Video Multi-Method Assessment Fusion (VMAF) is an video quality metric developed (https://github.com/Netflix/vmaf) by Netflix. The metric provides an indication of how closely a video resembles a source/reference. This is semantically similar to PSNR/SSIM, but VMAF is supposed to more closely reflect human visual perception. FFmpeg currently has video filters that measure PSNR/SSIM of any input video file compared to a reference, but it currently has no support for VMAF. In this task, you will add support for VMAF to FFmpeg.
Expected results: Fully functional video filter that measures the VMAF of any input video compared to a reference, and that does not depend on Netflix' code. You should be able to run a command like "ffmpeg -i file -i ref -lavfi vmaf -f null -" and it should give identical results to Netflix' run_vmaf.py tool. If there is time, you will also write x86 SIMD optimizations.
Prerequisites: C coding skills, basic familiarity with git.
Qualification Task: Create a vmaf video filter based on (and linking to) Netflix' codebase.
Mentor: Ronald S. Bultje (BBB in #ffmpeg-devel on Freenode IRC, rsbultje@gmail.com)
Backup mentor: Thilo Borgmann (thilo.borgmann AT mail de)
VP9 decoder improvements
Description: VP9 is a video codec developed by Google. It yields significantly better quality per bit compared to H.264, which is why many websites - e.g. Youtube - use VP9 (if the client supports it) to stream video over internet. FFmpeg has a native VP9 decoder that is significantly faster than Google's reference implementation. In this task, you will make this decoder even better.
Expected results: Improve FFmpeg's VP9 native decoder by implementing one or more of the following subtasks:
- AVX2 implementations for all 10/12bpc DSP functions
- AVX2 implementation for 8bpc loopfilter function
- native alpha channel (transparency) support for VP8/9 decoders
- tile threading support
Prerequisites: C coding skills, x86 assembly skills (or the will to learn), basic familiarity with git. The AVX2 tasks require access to a Haswell or better x86 machine. (ask kierank on irc if you need access to one)
Qualification Task: Finish one task from the list in expected results.
Mentor: Ronald S. Bultje (BBB in #ffmpeg-devel on Freenode IRC, rsbultje@gmail.com)
Backup mentor: Rostislav Pehlivanov (atomnuker in #ffmpeg-devel on Freenode IRC, atomnuker@gmail.com)
Ambisonic decoder
Description: Ambisonics is a full-sphere surround sound technique: in addition to the horizontal plane, it covers sound sources above and below the listener.
Expected results: Fully featured decoder implemented as filter in libavfilter.
Prerequisites: C coding skills, basic familiarity with git.
Qualification Task: Implement simple square decoder.
Alternative Qualification Task: Implement one of shelf filters as required by ambisonic decoding.
Mentor: Paul B Mahol (durandal_1707 in #ffmpeg-devel on Freenode IRC, onemda@gmail.com)
Backup mentor: Rostislav Pehlivanov (atomnuker in #ffmpeg-devel on Freenode IRC, atomnuker@gmail.com)
DICOM support
Description: FFmpeg currently does not support DICOM files although this is a widely used image format that is often passed to patients who have no access to DICOM equipment.
Expected results: Support reading as many features of the format as possible.
Prerequisites: Good C coding skills, basic familiarity with git
Qualification Task: Write a simple demuxer for a format currently unsupported by FFmpeg. The following tickets contain possible tasks, not all of them are equally simple / difficult, some may turn out to be less useful: #5154, #4748, #4519, #3986 (this may be too difficult or impossible), #3720, #2956, #2662 and #2176. Not all possible features of a demuxer have to be implemented (the more the better) but at least auto-detection and video decoding (and remuxing) should be possible to implement for all of them.
Mentor: Carl Eugen Hoyos (cehoyos in #ffmpeg-devel on Freenode IRC, ce AT hoyos.ws)
Backup Mentor: Thilo Borgmann (thilo.borgmann AT mail de)
MPEG-4 ALS codec improvements
Description: The implementation for MPEG-4 ALS is still missing some features and known bugs exist. This project aims to add missing features to the decoder and possibly the encoder as well as raising compatibility with the reference encoders.
Expected results: Improve FFmpeg's ALS native decoder by implementing one or more of the following subtasks:
- Add RLS-LMS prediction to the decoder / encoder
- Add FATE regression tests for RLS-LMS if appropriate
- Add floating-point support to the encoder
- Validate comptibility with reference codecs RM22/RM23
- Fix system dependent bugs to make FATE "green"
- Optimize FATE test samples in size and test coverage
- Solve known bugs in the codec
Prerequisites: C coding skills, basic familiarity with git.
Qualification Task: Fix one of the known bugs of ALS listed in our bugtracker.
Mentor: Thilo Borgmann (thilo.borgmann AT mail de)
Backup mentor: Mohammad Umair (omerjerk in #ffmpeg-devel on Freenode IRC, omerjerk@gmail.com)
Minterpolate improvements
Description: Improve the quality of the minterpolate filter by researching and implementing better algorithms.
Expected results: Significant reduction of subjective artifacts and significantly improved objective quality of videos created with minterpolate. Subtasks:
- Comparission of the existing minterpolate implementation against other implementations (which are freely accessible/testable)
- Finding the best state of the art algorithms in the academic literature
- Finding the best competing implementations
- Implementing and testing the best solutions found in FFmpegs minterpolate
Prerequisites: C coding skills, knowledge of motion estimation, motion compensation and optical flow algorithms. basic familiarity with git.
Qualification Task: Demonstrate that you are able to improve the quality of minterpolate.
Mentor: Michael Niedermayer (michaelni in #ffmpeg-devel on Freenode IRC, michael@niedermayer.cc)
Vorbis encoder improvements
Description: FFmpeg has a native Vorbis encoder which is known to have quality issues ever since it was implemented.
Expected results: Improve FFmpeg's Vorbis encoder:
- Add transient detection
- Switch transform sizes based on lambda
- Improve the rate control system
- Use the existing AAC psychoacoustic system to improve the quality
- Write FATE tests to improve test coverage
Prerequisites: C coding skills, basic familiarity with git.
Qualification Task: Use the existing AAC psychoacoustic system to detect transients
Mentor: Rostislav Pehlivanov (atomnuker in #ffmpeg-devel on Freenode IRC, atomnuker@gmail.com)
Backup mentor: TBA
Unmentored Projects
This is a list of projects that students are encouraged to consider if a mentored project is unavailable or not within the students skill or interests. The student will have to find a mentor for the project. A student can also propose their own project.
VC-1 interlaced
Description: The FFmpeg VC-1 decoder has improved over the years, but many samples are still not decoded bit-exact and some real-world interlaced streams show artefacts. This task is difficult.
Expected results:
- Implement missing parts of interlacing
- Make more reference samples bit-exact
Prerequisites: C coding skills, basic familiarity with git, ability to read and understand the vc1 specification and align that knowledge with the existing code
Qualification Task: Find a bug in the current decoder implementation and fix it.
JPEG 2000
Description: FFmpeg contains a native JPEG 2000 encoder and decoder. Both are missing many features, see also the FFmpeg bug tracker for some unsupported samples. This task is difficult
Expected results: A jpeg 2000 decoder which can decode more samples and / or an encoder that achieves higher compression.
Qualification Task: Fix an issue (for example from the bug tracker) to show that you are capable of improving the codec implementation.
Prerequisites: C coding skills, basic familiarity with git, good knowledge of Jpeg-2000
Your Own Project Idea
A student can propose a project. Ideas can also be found by browsing bugs and feature requests on our bug tracker. The work should last the majority of the GSoC internship duration, the task must be approved by the developers, and a mentor must be assigned.
Students can discuss an idea in the ffmpeg-devel mailing-list, the #ffmpeg-devel IRC channel, or contact the FFmpeg GSoC admins for more information.
