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Contents
Airavata
Local user interaface for Airavata MFT
NOte: This is an issue in github - https://github.com/apache/airavata-mft/issues/114 cross posting in Jira for GSoC purposes.
Currently, Airavata MFT can be accessed through its command line interface and the gRPC API. However, it is really easy if a Docker desktop-like user interface is provided for a locally running Airavata MFT. The functionalities of such an interface can be summarized as follows
- Start / Stop MFT Instance
- Register/ List/ Remove Storage endpoints
- Access data (list, download, delete, upload) in configured storage endpoints
- Move data between storage endpoints
- Search data across multiple storage endpoints
- Analytics - Performance numbers (data transfer rates in each agent)
We can use ElectonJS to develop this cross-platform user interface. The node.js backend of ElectronJS can use gRPC to connect to Airavata MFT to perform management operations
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Add blur background filter options on video sharing - AI-ML
OpenMeetings uses webRTC and HTML5 video to share audio video. Purely browser based.
One feature missing is the ability to blur your webcam's camera background.
There are multiple ways to achieve it, Google Meet seems to use: https://www.tensorflow.org/
Tensorflow are AI/ML models, they provide precompiled models into JS, for detection of face/body it seems: https://github.com/tensorflow/tfjs-models/tree/master/body-segmentation is the best model.
Since Chrome 14 there is also a Background Blur API (relying on operating system APIs): https://developer.chrome.com/blog/background-blur - but that doesn't seem to be widely or reliable supported by operating systems yet.
The project would be about adding the background blur into a simple demo and then integrate into the OpenMeetings project. Additionally other types of backgrounds can be added.
Tensorflow TFJS is under the Apache 2.0 License (See LICENSE) and should be possible to redistribute with Apache OpenMeetings.
Other live demos and examples:
https://blog.francium.tech/edit-live-video-background-with-webrtc-and-tensorflow-js-c67f92307ac5
UIMA
Support Aggregate Engines in Apache UIMACPP
UIMA is a framework for unstructured information management, built around the idea of heavy annotators interoperating using a common exchange format.
It has been in production use for about two decades.
The framework is mostly written in Java. It has a C++ counterpart that implements a subset of the framework.
The challenge for this GSOC is to work together with the mentor to implement the full framework.
More details on GitHub: https://github.com/apache/uima-uimacpp/issues/6
Benefits to the community
This has been discussed as one of the main roadblocks in using the C++ version of the framework by its users: https://lists.apache.org/thread/f1r3sghgn2oqhvzz27y26zg6j3olv8qq
About the mentor
Dr. Duboue has more than 25 years of experience in AI. He has a Ph.D. in Computer Science from Columbia University. and was a member of the IBM Watson team that beat the Jeopardy! Champions.
Aside from his consulting work, he he has taught in three different countries and done joint research with more than fifty co-authors.
He has years of experience mentoring both students and employees.