This service is designed to process and manage uploaded lecture material (video recordings, documents, slides) to facilitate some advanced features in the MEITREX platform.
- Splitting of lecture videos into sections based on detected slide changes via computer vision
- OCR of lecture video on screen text
- Transcript & Closed Captions generation for lecture videos
- Generating of text embeddings on a per-section-basis for videos and per-page-basis for documents
- Semantic search/fetching of semantically similar sections of lecture material
- Automatic generation of section titles for the video sections generated
This service requires pytorch to function. As pytorch GPU-support is required for some features of this service, the pip-distributed version of pytorch cannot be used and instead a
platform-specific version has to be used.
By default, pytorch for NVIDIA CUDA 12.4 is used, as this should provide the most capability for widespread GPUs. If you need to use a different version of pytorch, you can change
the install script located in the Dockerfile.
Caution
Note that GPU features require a supported GPU and OS to function, especially in conjunction with Docker, as the service runs in a Docker container.
Docker does not provide GPU-support for MacOS at this point in time, thus GPU-features of the service do not function on MacOS.
GPU features can be disabled using the config.yaml.
The service uses the config.yaml file located in the root directory for configuration.
For further information about configuration check out this file, all configuration properties are explained using in-file comments.