https://github.com/ornl/vivaldi
Vivaldi is a ML pipeline which generates 3D (height) at a building-by-building level from 2D morphology features
https://github.com/ornl/vivaldi
Last synced: 3 months ago
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Vivaldi is a ML pipeline which generates 3D (height) at a building-by-building level from 2D morphology features
- Host: GitHub
- URL: https://github.com/ornl/vivaldi
- Owner: ORNL
- License: other
- Created: 2024-04-19T14:28:42.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-19T15:00:09.000Z (about 1 year ago)
- Last Synced: 2025-01-24T17:14:55.845Z (4 months ago)
- Language: Python
- Size: 48.8 KB
- Stars: 0
- Watchers: 3
- Forks: 1
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# vivaldi_bh - Model Name: Vivaldi
POC: Clinton Stipek - [email protected]
## Getting started
This project's goal is to ingest morphology features (2D) and infer height (3D) for individual buildings:
1. The following breaks the vivald process into the respective steps
- Identify 2D buildings from AOI
- Generate morphology features using the Gauntlet feature morphology process
- Please see Taylor Hauser ([email protected]) for availability of Gauntlet features
- Run a recursive feature eliminator to streamline modelling process
- Hyper-tune parameters via bayesian optimization
- Infer building heights at a building-by-building level leveraging a XGBoost algorithm
## Docker
- There is a docker image for this project, to use the image please clone the repo and then go to vivaldi_bh/src for the docker files
- once cloned and in the right file trajectory, run the following lines in order in cmd line:
1. docker-compose build vivaldi_bh
2. docker-compose up -d vivaldi_by
3. docker-compose exec vivaldi_bh python /files/vivaldi.py
- please note that for command 3, the 'vivaldi.py' is the vivaldi process outlined in Getting Started
- Please message Clinton Stipek ([email protected]) for assistance
## Script run order
1. Run rfe.py (docker-compose exec vivaldi_by python /files/rfe.py - if using linux)
2. Run vivaldi_bh.py (docker-compose exec vivaldi_bh python /files/vivaldi_bh.py - if using linux)
## Data
- The data that vivaldi works with is built off the Gauntlet process
- Gauntlet v2 generates 65 morphological features that is in a tabular form at a building-by-building level
- The Gauntlet features are stored in PostGresQL
- Please see Taylor Hauser ([email protected]) for access to the data
- Please see Clinton Stipek ([email protected]) for gauntlet features necessary to run rfe and vivaldi_bh