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The project involves integrating pixel size support into ilastik, an image-processing and classification tool. Pixel size is a metadata item enabling conversion of image pixels into real-world measurements. Whilst pixel size is not currently processed in ilastik image sets, the program is used extensively in scientific applications, and introducing real-world measurements would enable development of several key features that would allow more in-depth quantitative analysis of image data, such as object displacement and velocity in video tracking, and real-world area calculation of segmentations/ volume calculation of carvings. Once the metadata is extracted at the image input end, it is possible to feed it directly into the data pipeline, so it can be picked back up within any relevant workflow. This facilitates feature development, as it then becomes possible to work directly with the metadata values within the workflow. Once the backends of these features have been developed, they will be implemented on the front-end via Qt. The key deliverables of this project are: Implement pixel size metadata into workflows, such that the metadata remains present in project files, output images, and exported datasets; Enable calculating areas of image segmentations; Enable calculating volumes of image carvings; Enable recording of object displacement in video tracking; Enable measurement of object velocity in video tracking; Produce detailed and well-written documentation, and ensure relevant test scripts for each feature are made available. An initial pull request for this proposal can be found at https://github.com/ilastik/ilastik/pull/2995

<p>Machine learning datasets are often continuously modified yet there is no efficient way to determine if two datasets are the same. This challenge becomes problematic when the datasets are large (20 GB+) and cannot be easily loaded into memory.</p> <p>This project intends to use Locality Sensitive Hashing (LSH) with the MapReduce paradigm to compare large scale, out of core machine learning datasets.</p>

<p>Smart HTTP/2-based protocol for Infinispan.</p> <p>The Infinispan Server distribution contains a server module that implements Infinispan’s custom binary protocol called Hot Rod. The protocol was designed to enable faster client/server interactions compared to other existing text based protocols and to allow clients to make more intelligent decisions with regards to load balancing, failover and even data location operations.</p> <p>In 2015 the 2nd version of HTTP protocol (simply HTTP/2) was finally introduced. HTTP/2 provides a lot of features that are also implemented in Hot Rod protocol. For example, using the HTTP/2 will be more preferable than Hot Rod because the size of the requests and responses will be smaller.</p> <p>Expected results of this project are:</p> <ol> <li>Modify current REST Server endpoint for Infinispan to handle HTTP/2 protocol. Modification will be based on implementing features from Hot Rod protocol to HTTP/2.</li> <li>Create HTTP client on Java.</li> </ol>

The project aims to extend GCC’s static analyzer to support reporting warnings for “misuse” of POSIX FD APIs such as double-close, leakage, access mode mismatch etc. by implementing the state machine that checks such misuse. Also, the project aims to add three attributes for use on functions that work with file descriptors.

<p>The Rust Project empowers developers to build reliable and efficient systems software with memory safety guarantees.</p><p>This project aims to build automated advisory database resolution and cargo audit warning highlights directly into the Cargo CLI toolchain.</p><p><br></p><p><strong>Deliverables:</strong></p><ul><li>Cargo audit subcommand plugin in Rust.</li><li>Integration test suite targeting RustSec database.</li></ul><p><br></p><p><strong>Applications closing date: 25-Apr-2026</strong></p><p><strong>Mentee confirmation: 10-May-2026</strong></p>

<p><strong>Neural source reconstruction</strong> of MEG/EEG data requires subject specific geometrical data (i.e. electrode locations and anatomical brain data). For many reconstruction techniques, results are volumetric rather than surface-based. A group level analysis for volumetric data has not yet been implemented in MNE Python. The proposed project aims to fill this gap, by implementing necessary tools for group level analyses based on <strong>volumetric data</strong>, among which are: non-linear warping of one volumetric (grid) space to another; creating pseudo-individual anatomical MR images, based on a subject’s head shape; and output preparation, such that it can be used with already built in statistical functions. The results will be a set of Python functions that enable the user to prepare individual volumetric subject data for <strong>group level analyses</strong>. Furthermore the respective visualization will be targeted as well.</p>

This project aims to enhance gprMax's user support capabilities by integrating advanced Language Model (LLM) technologies. The core goal is developing an AI-driven chatbot capable of interpreting natural language user instructions and generating accurate, ready-to-run gprMax input files. The project is scheduled for completion within a 12-week timeframe, divided into clear milestones ensuring systematic progression and iterative refinements. The final deliverables will great improve the user experience of gprMax and laying foundation for future AI integration.

FreeCAD is a powerful CAD software with vast capabilities supporting complete technical design pipelines beginning from modelling to FEM analysis to 3D printing. By enabling FreeCAD users to perform multibody dynamic (MbD) calculations, convert the results to FEM loads and visualise the stress and strain of an assembly in motion in a single coherent workflow, FreeCAD will be better positioned to rival commercial CAD software used by the industry today. The goal of this project is to help build that workflow by improving the combined Motion workbench so that motion-derived loads can be transferred into FEM analyses in a structured and user-friendly way. This project will focus on three main objectives. The first objective is to organise the current code into a clearer object-oriented framework. The second objective is to convert idealised MbD joint forces and torques into realistic distributed FEM loads on selected contact surfaces of real parts. The third objective is to design a user interface (UI) that allows the selection of the contact regions in FreeCAD.

<p>I would like to complete the QtSharp project which aims to provide Mono/.NET bindings for Qt.</p>

I will be adding new UI elements and improving the existing UI system to easily visualize and transform various geometric shapes and UI elements interactively without affecting the existing performance.

The Mission Support System (MSS) client currently lacks the ability to save and restore view configurations, requiring users to manually recreate complex window layouts each time they reopen the application. Additionally, collaborative operations do not support sharing view configurations among participants, hindering real-time coordination. To enhance the user experience and collaboration in the Mission Support System (MSS), this project will introduce two major improvements. First, it will implement a local and server-side view restoration system, allowing users to save and reload their window layouts automatically. This will be achieved through JSON-based storage for local configurations and database integration for server-side persistence. Users will have the option to enable or disable view restoration via a new setting, ensuring flexibility. Second, the project will introduce a collaborative view-sharing feature through a dedicated "Manage View" widget. This will enable participants in an operation to share, browse, and load predefined layouts, ensuring consistency during joint missions. The widget will integrate with MSS’s existing operation system, allowing real-time updates via WebSocket notifications. Backend APIs will handle secure storage and retrieval of shared views, while the frontend will provide an intuitive interface for managing layouts. Together, these enhancements will eliminate the need for manual reconfiguration and streamline teamwork in mission planning and analysis.

This project aims to implement some new language features introduced in Fortran 2018 and Fortran 202x, enhancing gfortran's compatibility with newer Fortran standards.

<p>Mission Support System is a flight planning software which a researcher can use to analyze predicted atmospheric data, and plan a flight-path with 3D way-points. The software in the present state allows editing by a single user per flight-path. To share this work, one has to export the work as a <code>$name.ftml</code> file and send it to other researchers for further planning. This back and forth communication not only consumes a lot of human efforts and time, but also can be frustrating when the number of researchers involved in a project is bigger, say &gt;=3.</p> <p>I propose a solution to this problem, the development of <code>Mscollab</code> which stands for "Mission Support Collaboration". <code>Mscollab</code> server would facilitate <em>real-time</em>, <em>collaborated</em> editing of flight-paths by <em>authorized</em> users. By design, it will also provide a chat facility for the users who are collaborating on the project. Its UI would be a part of <code>msui</code>, the core User Interface module of <code>mss</code>. It would additionally provide insights about temporal changes related to waypoints and the users who created them, for analytics purpose. <code>Mscollab-server</code> will be a standalone server built with Python, Flask, and python-socketio.</p>

<p>In the above proposal we are showing the idea of implementing JPEG Encoder(backend) in python using existing MyHDL Library. A working module and its corresponding testbench is desired.</p>

pocketpy is a lightweight Python interpreter primarily designed for game scripting, boasting a vast feature set encompassing various Python modules. It's competitive performance and elegant syntax have made it a user choice for scientific computations. To enhance its capabilities, this project focuses on adding the core feature set from the NumPy library to pocketpy. There are two primary objectives: 1. Implementing core classes from NumPy: This subtask aims to implement key classes such as ndarray and random, along with their respective methods and functionalities. The code will be written in C++ for performance benefits. Existing C++ libraries like NumCpp (or Xtensor), which offer NumPy-like functionalities, will be leveraged for the implementation. 2. Exposing the C++ implementation to Python through bindings: To achieve this goal, we will use a library named pybind11, a popular header only library used to generate bindings for C++ classes automatically. This step will allow users to work on a pythonic frontend and access the NumPy functionalities implemented in C++. By the end of this summer, pocketpy seeks to offer robust array operations and random number generation capabilities, positioning it as a versatile tool for various computational tasks beyond game scripting.

<p>This project aims to fix the issues regarding the Android platform that includes fixing the shader, adding a new audio system and the addition of tilt for a smooth gaming experience on Android Devices.</p>

<p>The proposed project is to create a set of Python based tools for easier and efficient creation of Hypermedia driven REST-APIs.</p> <p>The other part is an application that simulates the movements of a flock of drones that have as objective to detect the presence of fires or abnormal heat spots in a given geographical area using an infrared sensors to demonstrate the capabilities of Hydrus and the Hydra Draft.</p>

As of march 2025 FreeCAD cannot have more than one active document. If a task is going on in a file, another file cannot be edited until that operation is resolved. The project's aim is to instantiate an editor per tab (document) and therefore allow parallel editing of multiple files. This would not only make the software more powerful for advanced users, but also friendlier for beginners.

The Open World Holidays Framework is an essential open-source tool that provides accurate holiday data for over 160 countries. However, it currently lacks comprehensive support for several underrepresented countries, which limits its utility for users seeking to understand global holiday practices. This proposal aims to enhance the framework by integrating holiday data for 12 additional countries: Fiji, Antigua and Barbuda, Benin, Bhutan, Cabo Verde, Central African Republic, Comoros, Ivory Coast, Democratic People's Republic of Korea, Democratic Republic of the Congo, Equatorial Guinea, and Eritrea. To achieve this, I will conduct thorough research to gather accurate holiday data from authoritative governmental sources, ensuring linguistic accuracy through credible translations. The integration process will involve developing a structured approach to accommodate both fixed and floating holidays, as well as regional variations. I will leverage my previous contributions to the framework, particularly my work on Fiji, as a foundation for this project. The deliverables for this project will include: - Integrated holiday data for the 12 new countries within the Open World Holidays Framework. - Comprehensive unit and integration tests to ensure the accuracy and compatibility of the newly added data. - Updated documentation that reflects the new country support and provides clear usage instructions for users. By expanding the framework's coverage, this project will not only enhance its functionality but also promote cultural awareness and inclusivity, making it a valuable resource for users worldwide.

<p>Expand the PFS GSoC blogging platform to include a top level overview of student status grouped by suborg and extend student activity monitoring to include code checkins, chat and mailing list activity.</p>

<p>SECCOMP_RET_TRACE seccomp API could be used to implement a more efficient syscall filtering. Using this technique, tracees will be stopped on entering filtered syscalls only instead of all syscalls.</p>

The objective of this proposal is to enhance the user experience of Mailman 3 by introducing two new features - systemwide user defaults and an improved UI for subscription management. These features will enable site admins to manage mailing lists more effectively and improve the subscription management UI for users.

cargo-semver-checks is a development tool that allows rust libraries to check whether a release breaks semver by running lints on the API. For example, it can detect whether an enum not marked #[non_exhaustive] has additional members added, and warn that this is a major breaking change. However, cargo-semver-checks can take a long time to run, and for many users, is the longest step in their CI. On top of that, the number of lints implemented is nearly doubling each year. The core of this project's work is: (1) Constructing a performance tracing tool that is capable of identifying bottlenecks and hotspots in trustfall’s execution model, and (2) Using this tool to implement performance improvements, most likely in the database adapter level in trustfall-rustdoc-adapter, with the goal of reducing runtime by 50-80%.