LabGraph is a Python framework for rapidly prototyping experimental systems for real-time streaming applications. It is particularly well-suited to real-time neuroscience, physiology and psychology experiments.
EGO4D is the world's largest egocentric (first person) video ML dataset and benchmark suite, with 3,600 hrs (and counting) of densely narrated video and a wide range of annotations across five new benchmark tasks. It covers hundreds of scenarios (household, outdoor, workplace, leisure, etc.) of daily life activity captured in-the-wild by 926 unique camera wearers from 74 worldwide locations and 9 different countries. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event.
This project focuses on the following use cases:
Audio-visual speaker diarization: Given an egocentric video clip, identify which person spoke and when they spoke.
Speech transcription: Given an egocentric video clip, transcribe the speech of each person.
Use Ego4D video clip
🚀 Feature
EGO4D is the world's largest egocentric (first person) video ML dataset and benchmark suite, with 3,600 hrs (and counting) of densely narrated video and a wide range of annotations across five new benchmark tasks. It covers hundreds of scenarios (household, outdoor, workplace, leisure, etc.) of daily life activity captured in-the-wild by 926 unique camera wearers from 74 worldwide locations and 9 different countries. Portions of the video are accompanied by audio, 3D meshes of the environment, eye gaze, stereo, and/or synchronized videos from multiple egocentric cameras at the same event.
This project focuses on the following use cases: Audio-visual speaker diarization: Given an egocentric video clip, identify which person spoke and when they spoke. Speech transcription: Given an egocentric video clip, transcribe the speech of each person. Use Ego4D video clip
Additional context
Example application can be found here The code should be added at folder is https://github.com/facebookresearch/labgraph/tree/main/extensions/labgraph_diarization Create setup.py and README.md, where example can be found at: https://github.com/facebookresearch/labgraph/tree/main/extensions/labgraph_viz Add github action support, reference: https://github.com/facebookresearch/labgraph/actions/workflows/main.yml Add proper license header.