GSoC/2022/Ideas: Difference between revisions

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==== Project: Porting the KDE Connect iOS codebase to macOS ====
==== Project: Porting the KDE Connect iOS app to macOS ====
'''Brief explanation''': TBA.
'''Brief explanation''': TBA.



Revision as of 01:11, 13 February 2022

Konqi is giving a lesson!

See also: GSoC Instructions, Last year ideas

Guidelines

Information for Students

These ideas were contributed by our developers and users. They are sometimes vague or incomplete. If you wish to submit a proposal based on these ideas, you are urged to contact the developers and find out more about the particular suggestion you're looking at.

Becoming accepted as a Google Summer of Code student is quite competitive. Accepted students typically have thoroughly researched the technologies of their proposed project and have been in frequent contact with potential mentors. Simply copying and pasting an idea here will not work. On the other hand, creating a completely new idea without first consulting potential mentors rarely works.

When writing your proposal or asking for help from the general KDE community don't assume people are familiar with the ideas here. KDE is really big!

If there is no specific contact given you can ask questions on the general KDE development list [email protected]. See the KDE mailing lists page for information on available mailing lists and how to subscribe.

Note

These are all proposals! We are open to new ideas you might have!! Do you have an awesome idea you want to work on with KDE but that is not among the ideas below? That's cool. We love that! But please do us a favor: Get in touch with a mentor early on and make sure your project is realistic and within the scope of KDE.


Adding a Proposal

Note

Follow the template of other proposals!


Project:

If appropriate, screenshot or another image

Brief explanation:

Expected results:

Knowledge Prerequisite:

Duration: ~175 hr or ~350 hour (use only one)

Mentor:

When adding an idea to this section, please try to include the following data:

  • if the application is not widely known, a description of what it does and where its code lives
  • a brief explanation
  • the expected results
  • pre-requisites for working on your project
  • if applicable, links to more information or discussions
  • mailing list or IRC channel for your application/library/module
  • expected effort to finish the project (either ~175 or ~350 hrs)
  • your name and email address for contact (if you're willing to be a mentor)

**Ideas with no mentors listed and their contact info will be removed**

If you are not a developer but have a good idea for a proposal, get in contact with relevant developers first.

Ideas

Your Own Idea

Project: Something that you're totally excited about

Brief explanation: Do you have an awesome idea you want to work on with KDE but that is not among the ideas below? That's cool. We love that! But please do us a favor: Get in touch with a mentor early on and make sure your project is realistic and within the scope of KDE. That will spare you and us a lot of frustration.

Expected results: Something you and KDE loves

Knowledge Prerequisite: Probably C++ and Qt but depends on your project

Duration: Mention one of ~175 or ~350 hours of effort necessary to finish the project. Use only one of these two project classes and don't come up with other numbers here.

Mentor: Try to see who in KDE is interested in what you want to work on and approach them. If you are unsure you can always ask in #kde-soc:kde.org on matrix.

digiKam

digiKam is an advanced open-source digital photo management application that runs on Linux, Windows, and MacOS. The application provides a comprehensive set of tools for importing, managing, editing, and sharing photos and raw files.

Project: New plugin to process OCR

Brief Explanation: the goal of this project is to implement a new generic DPlugin to process images in batch with Tesseract. It's a C++ framework to make Optical Characters Recognition. This plugin must be able to run over images automatically and record detected text in image metadata for post-processing, as described in this bugzilla file:

https://bugs.kde.org/show_bug.cgi?id=117629

Expected Results:

Provide a new optional Generic Tesseract based DPlugin available in digiKam and Showfoto to run OCR automatically. Write unit-tests, and documentation.

Knowledge Prerequisite:

  • C++, Qt5 and Qt6 API, Tesseract, CMake, OCR Image Processing

Mentors: Thanh Trung Dinh ([email protected]), Minh Nghĩa Dương ([email protected]), Maik Qualmann ([email protected]), and Gilles Caulier ([email protected])

Project: Improve Image Quality Sorter with Neural Network

Brief Explanation: digiKam has powerful feature to sort images by quality and register items with flags in database for future post processing. Analyzed image qualities are noise, focus, exposure, and compression. Algorithms used in background are revised in 2021 and give good enough result but we can add new criteria of quality based on Neural Network analysis, as for ex to detect the composition of image.

Expected Results:

Provide an update of Image Quality processing using OpenCV DNN engine. Write unit-tests, and documentation.

Knowledge Prerequisite:

  • C++, Qt5 and Qt6, DNN, OpenCV, Image Processing

Mentors: Thanh Trung Dinh ([email protected]), Minh Nghĩa Dương ([email protected]), Maik Qualmann ([email protected]), and Gilles Caulier ([email protected])

Project: Port Continuous Integration/Deployment to Gitlab/Craft DevOp Infrastructure and Notarize Bundles for Stores

Brief Explanation: digiKam use KDE/Jenkins to process Continuous Integration for Linux/BSD target. Windows and MacOS target do not work. With the recent migration to Gitlab, DevOps gain simplicity and become more powerful. The goal of this project is:

- Prepare Craft infrastructure to handle digiKam and all required dependencies (this is more and less already done as other application as Krita already build with Craft). - Setup Continuous Integration and Continuous Deployment authorizations with Gitlab/Craft. - Compile digiKam from MacOS and Windows using CI. - Fix compilation with XCode and VisualC++ if necessary using CI. - Configure the signature of bundles. - Configure the application rights under MacOS and Windows (access to camera device, access to disks). - Construct the bundles. - Test if all is fine at run time on target computers. - Deploy the bundles to the Windows and MacOS stores (Kate editor do it already).

Relevant bugzilla entries are listed below:

https://bugs.kde.org/show_bug.cgi?id=398582 https://bugs.kde.org/show_bug.cgi?id=120192

Link to Craft DevOps toolkit:

https://community.kde.org/Craft

Expected Results:

Using modern Gitlab/Craft DevOps infrastructure to compile digiKam. Provide notarized bundles for Apple and Microsoft stores.

Knowledge Prerequisite:

  • C++, CMake, Qt5 and Qt6, Gitlab, DevOps, Craft.

Mentors: Thanh Trung Dinh ([email protected]), Minh Nghĩa Dương ([email protected]), Maik Qualmann ([email protected]), and Gilles Caulier ([email protected])

Okular

Okular is a universal document viewer developed by KDE. Okular works on multiple platforms, including but not limited to Linux, Windows, Mac OS X, *BSD. Contact the Okular developers.

Project: Okular user interface for e-ink tables (PineNote)

Brief explanation: e-ink tables are special given their "low" refresh rate.

We would need to create a new Okular user interface (based either in the mobile or the dekstop one) to accommodate for the unique features of those kind of displays.

We will probably arrange to get a device loaned if someone gets selected for this project.

Expected results: A new Okular user interface that works well with e-ink tablets.

Knowledge prerequisite: C++, probably QML.

Duration: 350 hours.

Mentor: Albert Astals Cid [email protected]

KStars

KStars is free, open source, cross-platform Astronomy Software. It provides an accurate graphical simulation of the night sky, from any location on Earth, at any date and time.

Project: Observation Wizard Improvements

Brief explanation: The Observation Wizard enables users to select and filter objects of interest to them . Currently, the selection is done by object type, location, and magnitude in the sky. Further, the user can filter objects based on altitude and time-range when they are available. This tool can be further improved by providing the following features:

  1. INDI Integration: Filter and sort by object size for Deep Sky Objects that have a physical width and height, unlike point-like sources like stars. Limit objects to fall within a particular percentage of the sensor. For example, M31 galaxy is very large and spans almost 3 degrees in the night sky. It would not fit inside the camera's 1x1 degree field of view (as calculated from INDI). Similarly, an object spanning on 5'x5' arcmins is too small in the camera.
  2. Image Integration: The way the final list of objects are displayed should be modernized. Each object should have an image and also an Altitude-vs-Time plot next to it so that the user can quick identify what is the best time to observe this object. For large lists, this can be very CPU intensive and should be optimized accordingly.
  3. Save/Load: Ability to save and load the wizard search parameters for future use so that the user does not always have to start from scratch every time they need to search for objects.
  4. Export: Export the list of object to an external file or source in CSV and JSON formats.

Expected results:

  • Improved Observation Wizard Tool.
  • Proper integration with INDI & Ekos.

Knowledge Prerequisite: C++, Qt, Data Structures

Mentor: Jasem Mutlaq (KDE Web Chat: Jasem)

Project: FITSViewer & Photometry Improvements

Brief explanation: The FITSViewer is used to display FITS images as captured by cameras or opened by the user. It supports 8, 16, 32, and 64bit formats with either a single channel (Mono or Bayer) or RGB cube. The goal for this project is to provide efficient and intuitive controls for:

  1. Noise Calculation: Calculate the overall Signal-to-Noise (SNR) radio for the overall image, or a specific subframe of the image.
  2. Sky Glow Computation: Estimation of Sky Glow component in image of various exposures. Each captured image is affected by multiple sources of noise, only of which is the sky glow which in turn is affected by the atmosphere, pollution, and artificial sources (e.g. light). The objective is to propose to the user the optimum exposure time given the sky glow contribution to the image.
  3. Mask Overlay: Ability to select custom mask over stars to aid in focusing and photometry.
  4. Photometry: KStars includes SEP which can be used to extract sources from stellar images and also performs aperture photometry. A new tool should be developed to aid the users to perform photometric work with the images including reduction of images (darks & flats) with various optimization/algorithmic settings. Additionally, the tool provides means for aperture photometry calculations as well.

Since FITSViews typically deals with very high-resolution images, such calculations can be very computationally expensive. It is expected that a very efficient multi-threaded code to be developed to take advantage of all the available cores on the system and any hardware or instruction set optimizations to achieve the smoothest user experience. Expected results:

  • Improved Histogram Tool.
  • SNR, Sky Glow, and Photometry calculations.
  • Photometric reductions. Aperture photometry.

Knowledge Prerequisite: C++, Qt, Threading, Data Structures

Mentor: Jasem Mutlaq (KDE Web Chat: Jasem)

Project: Implement Qt3D backend for KStars

Brief explanation: The Skymap in KStars desktop version is currently built using QPainter and 2D drawing primitives. In order to take advantage of advances in modern GPU hardware and to present a stunning visual view of the night sky, a 3D backend is desired. Qt 3D provides functionality for near-realtime simulation systems with support for 2D and 3D rendering in both Qt C++ and Qt Quick applications. Within KStars, SkyPainter provides a backend-agnostic class for drawing object unto the skymap regardless of the backend. Previously, an experimental OpenGL backend was developed but was later deprecated due to drawing issues. Since Qt3D provides an abstraction to the backend framework (OpenGL/Vulkan/DirectX), it presents a very flexible framework for building future-proof 3D applications.

Expected results:

  • Create Qt3D based backend to draw all objects currently implemented by QPainter backend.
  • Create realistic colors, shares, textures, meshes, lighting for all stars, solar system, and deep sky objects.
  • Create animations for meteor shows, comet tails, stars twinkle..etc

Knowledge Prerequisite: C++, Qt, Prior experience working with 3D applications/games.

Mentor: Jasem Mutlaq (KDE Web Chat: Jasem)


Project: KStars Testing

Brief explanation: KStars is built on a relatively large number of C++ classes, grouped in the following categories: sky objects and components, projection algorithms, graphics, timekeeping, widgets, Ekos automation, INDI client, FITS viewing, accessories and several library interfaces. Most of these constituting classes remain untested in terms of systematic and automatic verification. The objective of this project is to verify the code written in those classes at three levels: API, functionality and UI-based use case. In order to achieve this, the existing test code will have to extend its code coverage, report validation results and integrate seamlessly to the build recipe of the project.

The difficulty of this project is the requirement to create tests on legacy code and consolidate a test plan that reflects how the software is working instead of how we expect it to work.

Expected results:

  • Verify APIs: call each public class member using arbitrary test fixtures, control side effects by stubbing interfaces. This verifies code is executing in the data domain we expect, or fails for known reasons. As an example, the report will reveal how classes managing coordinates accept or reject numerical input.
  • Verify functionalities: ensure specific class interfaces return an expected result given a controlled set of input parameters. This verifies code is behaving as expected, or isolates known issues. As an example, the report will reveal which value of the Julian time classes managing timekeeping produce given different input objects embedding the same UTC time.
  • Verify use cases: ensure specific scenarios can be executed in the interface as presented in their documentation. This verifies procedures achieving useful results for the end-user remain stable, and controls how they evolve and improve during development.
  • Consolidate test reports and code coverage, and automate the execution of the test plan when building.

Bonus: generate videos of use cases for end-users automatically.

Level: beginner to intermediate

Knowledge prerequisites: C++, Qt, software testing and verification fundamentals

Mentor: Jasem Mutlaq (KDE Web Chat: Jasem)

Plasma Mobile Dialer

Plasma Mobile Dialer is a part of the Plasma Mobile project developed by KDE. Additional details could also be found in the developer documentation.

Project: Visual voicemail support

Brief explanation: KDE Gitlab issue

As described in the KDE GitLab, it is possible to reuse the so-called vvmd daemon that retrieves Visual voicemail. It provides environment-agnostic D-Bus interfaces. The draft for the Qt wrappers is also there. The integration could be implemented as part of the org.kde.telephony QML plugin or as a separate QML plugin. After that, the user interface could be written in QML with Kirigami components library for the plasma-dialer side. The task is mostly to propose and implement an appropriate graphical user interface.

Expected results: An additional tab/page for the dialer where you could listen to voicemail messages

Knowledge prerequisites: QML, Kirigami (mostly), C++, Qt, D-Bus IPC (to interact with the existing daemon), CMake (project build system)

Duration: 175 hours

Mentor: Alexey (KDE Web Chat: aa13q)


Plasma

Plasma form factor integration of system dialogs

Brief explanation: On this project you will be improving the integration of different Plasma components into different form factors. By adopting the SystemDialog component, we will be able to integrate them visually on mobile, Big Screen and others.

Expected results: The SIM PIN, PolKit (i.e. admin password prompt), KWallet and Netork Manager will appear native on Plasma Mobile. As a stretch goal we could work out how to also benefit from this work on Plasma Big Screen which targets TV UXs.

Knowledge Prerequisite: QML and C++. Knowledge of Kirigami will come in handy.

Duration: 175 hours

Mentor: Aleix Pol Gonzalez, @apol:kde.org


Hardware based navigation of Maliit On-screen keyboard

Brief explanation: On this project you will be improving the Maliit on-screen keyboard to allow selection of keys and other keyboard elements, via hardware input such as gamepads, analog joysticks, or arrow keys, for use in Bigscreen and similar situations.

Expected results: Keys, word completion, and other core features of the keyboard should be controllable from hardware input. There should be clear visual indication of what key is currently selected, selection of word suggestions, and what action pressing hardware buttons (x, y, b, a, triggers, etc…) will result in. The OSK should detect what hardware configurations are currently in use, and display or not display hints as appropriate.

Knowledge Prerequisite: QML and C++

Duration: 175 hours

Mentor: Rodney Dawes KDE Web Chat: dobey)

NeoChat

Spaces Support in NeoChat

Brief explanation: Spaces are used to group matrix rooms together, for example all rooms belonging to the KDE Community. The project's goal is to enable NeoChat to support spaces.

Expected results: NeoChat can show spaces and ideally also create and edit them

Knowledge Prerequisite: QML and C++

Duration: 350 Hours

Mentor: Tobias Fella and Carl Schwan, https://matrix.to/#/#neochat:kde.org

Krita

Krita is a digital painting application, used by millions of people all over the world. For Google Summer of Code, we expect students to already have contributed to Krita by building the application and submitting merge requests for some bug fixes. Note that some projects also demand a good knowledge of algorithms and skill in doing research.

Project: Export an Image to SVG

Brief explanation: Right now, Krita can only save to SVG one layer at a time. It would be good if Krita was able to save the whole document to SVG: vector layers as groups, and raster layers as bitmaps. To be determined what should happen to other types of layers. Link: https://bugs.kde.org/show_bug.cgi?id=404834

Expected results: File -> Save, File -> Save As, File -> Export should have an option to save to SVG. A file saved into SVG should have all raster and vector content from the document, but not the filter/fill layers.

Knowledge Prerequisite: C++. Qt. CMake

Duration: ~175 hr

Mentor: Wolthera van Hövell

Project: Add Benchmarks to the Krita executable

Brief explanation: currently, to run benchmarks, people have to have a build from source. To see whether particular hardware gives a problem, we should add a function that generates a benchmark file complete with all hardware and OS info as well as what is being done. This should be separate both from the debug output and the krita log.


Expected results: integration of all benchmarks that currently run standalone from the command line into Krita. A dialog to select which benchmarks to run, and the output available after running the benchmark as a file and shown inside the benchmark dialog.


Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr or ~350 hour (use only one)

Mentor: Dmitry Kazakov


Project: Implement Support for JPEG-XL

Brief explanation: JPEG-XL (https://jpeg.org/jpegxl/) is becoming the preferred output format for HDR content. This project should select an existing jpeg-xl library and integrate it into Krita as an import/export plugin.


Expected results: the ability to import and export files in this format

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr

Mentor: Halla Rempt


Project: Texture Each Dab instead of the whole Stroke

Brief explanation: Implementing texturing brush dabs instead of texturing whole stroke. (Just like Opacity is about the whole stroke and Flow is about the opacity of just one brush dab) Link: https://bugs.kde.org/show_bug.cgi?id=375155


Expected results: Texture is applied only on brush dabs. See https://bugsfiles.kde.org/attachment.cgi?id=135342


Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr or ~350 hour (use only one)

Mentor: Dmitry Kazakov


Project: Add film-like adjustment

Brief explanation: Film-like is a name of a special adjustment curve that allows the user to control the contrast without having hue shifts that often happen when using standard HSV Adjustment curves. Note: you will need to do quite a bit of research first. Link: https://bugs.kde.org/show_bug.cgi?id=385845


Expected results: A new filter with Film-like adjustment.

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr

Mentor: Wolthera van Hövell

Project: Pixel-perfect ellipses

Brief explanation: In Krita, there is no way to draw a pixel-perfect ellipse using the Ellipse Tool. Most probably the appropriate solution would be to create a new type of Brush Engine that would behave in a pixel-perfect way. Note: this is more complicated than you might think at first. Link: https://bugs.kde.org/show_bug.cgi?id=387242


Expected results: A way to draw a pixel-perfect ellipse using the Ellipse Tool. The new Brush Engine must also behave in a pixel-perfect way creating lines and other shapes.

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr

Mentor: Ivan Yossi

Project: Adding support for high-channel depth brush tips

Brief explanation: Currently, brush tips are 8 bits and based on QImage objects. With the advent of 16 bit/channel and 32 bit/channel support in QImage, we can start supporting higher bit depth brush tips. The 16 bit/channel GBR format from Cinepaint is not so relevant: we should support EXR and PNG for predefined brush tips and extend the autogenerated brush tips to support higher channel depths as well.

Expected results: A gui to select the channel depth when creating brush tips, Loading of high-channel depth brush tips, Support for high-channel depth brush tips when painting


Knowledge Prerequisite: C++, Qt, CMake

Duration: ~350 hour

Mentor: Halla rempt

Project: Extend Arrange Docker to support alignment and distribution of Layers

Brief explanation: Currently, the arrange docker only supports aligning and distributing vector objects of a singlet vector layer. This project aims to extend the arrange docker support for layers and masks too.


Expected results: All the current operations available in Arrange docker could be done with the layers.


Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr or ~350 hour (use only one)

Mentor: Agata Cacko

Project: "Enter Group" and "Vector Pattern" GUI functionality for Krita vectors

Brief explanation: Currently, to modify grouped shapes the user have to always ungroup them. The goal of the project is to implement a UIX for modifying the shapes inside the group without ungrouping them (see Inkscape). The user should be able to "enter" a group, which would limit his actions only to the shapes inside a selected group (perhaps, shapes outside the group should also be grayed-out?).

The feature is tightly related to the "SVG Vector Patterns" functionality. Krita can already render vector patterns perfectly fine, but there is no GUI for creating/modifying them. Pattern fills should be editable from the shape editor tool option widget.


Expected results:

  • The user can Enter/Leave group and modify shapes inside it without ungrouping
  • Shapes outside the currently entered group are grayed-out (disputable?)
  • The user can create/modify vector patterns using Tool Options docker of DefaultTool (see KoFillConfigWidget)


Knowledge Prerequisite: C++, Qt, CMake

Duration: ~350 hour

Mentor: Dmitry Kazakov

Project: Improve texture editing pipeline and add DDS file format

Brief explanation: It would be nice to have support for DDS textures file format, which is rather popular among game developers. There are also a lot of nice small features which could improve texture creator's workflow a lot: https://phabricator.kde.org/T12767

Expected results:

  • Krita can load and save DDS textures
  • Mipmap generation GUI
  • cubemaps, 3D-textures, texture arrays editing GUI


Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr

Mentor: Wolthera van Hövell

Project: A Comic Book Frame Layer Type

Brief explanation: This project is about adding a new layer type geared towards creating comic book frames. For this proposal, please first check how comic book frames work in other applications (Clip Studio, Medibang...) and propose a user interface.

Expected results: a usable system to place frames and gutters on an image and modify them.

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~350 hour

Mentor: Halla Rempt

Project: Per-document resources docker

Brief explanation: Since Krita 5, Krita files can contain resources (brushes, gradients, palettes, etc.) that are specific for a certain document. This project entails creating a new docker that shows those resources and that allows adding and removing those resources from a document. If time permits, the document information dialog should also show the per-document resources.

Expected results: A new docker that shows the document's resources

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~175 hr

Mentor: Halla Rempt

Project: Clipping Masks

Brief explanation: Users are asking for clipping mask functionality that is compatible with Photoshop. This project entails implementing loading and saving clipping masks to and from PSD files and KRA files, adding a tool to create and edit clipping masks and writing documentation for the manual. See https://www.adobe.com/devnet-apps/photoshop/fileformatashtml/

Expected results: Photoshop-compatible clipping masks

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~350 hour

Mentor: Dmitry Kazakov

Project: Steam Integration

Brief explanation: Krita has been available in the Steam store for a long time. This project means you will integrate the Steam library within Krita and making it possible to support badges and achievements in Krita, as well as support for Steam's cloud storage.

Expected results: Full steam integration

Knowledge Prerequisite: C++, Qt, CMake

Duration:~350 hour

Mentor: Ivan Yossi

Project: Action Recorder

Brief explanation: Krita used to have an action recorder: a system that would record all the user's actions, like painting, applying a filter and so on into a macro file that could be replayed. This system was disabled many years ago. You would need to design a generic system that integrates with Krita's 'strokes' framework and that would save all the user's actions to such a macro file, and then be able to replay this, both at native speed and at slowed-down speed. Note that this is different from the existing recorder which writes frames from the image's state to to an animation file.

Expected results: a working recorder and playback functionality

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~350 hour

Mentor: Dmitry Kazakov

Project: Generic Layer Tagging

Brief explanation: The layer properties dialog and layer docker should be extended with support for tagging. There should be a number of default tags, but the set of tags should be extensible. There should also be defined a number of default operational meanings for tags, like "do not render this layer to an exported image" for a "Draft" tag.

Expected results: A tagging system for layers

Knowledge Prerequisite: C++, Qt, CMake

Duration: ~350 hour

Mentor: Halla Rempt

KDE Connect

KDE Connect is a series of apps for a wide range of platforms that provides inter-device integration such file and clipboard sharing, remote control, and more. Though the specific knowledge and workflow depends on the KDE Connect client (At, Android, iOS, etc.), development of all clients touches closely on concepts such as networking (socket

Project: Porting the KDE Connect iOS app to macOS

Brief explanation: TBA.

Expected results: An optimized macOS application, based on the KDE Connect iOS codebase

Knowledge Prerequisite: Swift, Objective-C, SwiftUI, Xcode, iOS, macOS

Duration: ~TBA hour

Mentor: