Music_Gen_Streamlit

"Music Generation using Neural Networks" Streamlit App

Make a run_app.sh
Introduction [~5 min] (Sohaib)
- Team Member names/intro (WS 2019/2020, course name)
- Outline
  - Introduction
  - Data
  - Phase 1
  - Phase 2
  - Neural DJ
- Literature review
  - Refer to the literature slides
Data Analysis [~10 min] (Shivaani)
- General Info about data
  - Add charts and sources about data (Lakh and RedditPop)
- DataProcessing Pipeline Graph (streamlit graph docs/ Abdallah's choice)
- Raw MIDI data
  - Music21 intro and applications
  - show raw midi (without explanation, button to visualize raw midi (Sohaib))
- Tokenized MIDI
  - Show Tokenized with variable length
  - Expand Tokens (musicautobot, go through section and see if its too explained)
- Play MIDI (Sohaib)
  - Phase 1
    - Play original
    - Play extracted
  - Phase 2
    - Play sample (Lakh)
Add Model() (Abdallah)
- Phase 1
  - Modeling (Hugging Face OpenAI GPT2)
  - Data
    - Only Piano (extracction process)
  - Tokenization problem
- Phase 2
  - Modeling (Architecture, Transformer XL)
  - Data
    - Used piano, but then ran into problems
    - handle big files problem
  - musicautobot API for data
Add Prediction() (Code: Sohaib)
- Overview of pred process
- Play
  - Play original
  - Play predicted
- Visualize
  - Note sheet original
  - Note sheet predicted
- [?] Metrics
Technical Service/Deployment Pipeline (Code: Sohaib)
- make a requirements.txt
- Docker and heroku deployment
  - Make container
  - Check functionalities for each functional part of interface

Use Docker to run

make sure you have docker installed ./run_app.sh (this will take around 7-10 mins) then go to : localost:8501