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dvpi_app

Application for determining DVPI and plant species identification

The application is described in further detail in two blog posts (part 1 and part 2).

Web application build using FastAPI containing 3 endpoints:

  • Landing page with simple interface for uploading '.csv' file for determining DVPI score (Danish stream plant index, link to report in Danish) or images for species identification
  • Species identification using deep learning model trained to identify 100 plant species included in DVPI
  • Determine DVPI score by calling an external SOAP API endpoint using a '.csv' file with plant species and cover (example file)

Repository contains all necessary file to run the application. To install packages for runtime environment:

pip install -r requirements.txt

To run the application locally run:

uvicorn main:app --reload

The repository also contains additionally files for serving the application on Heroku.

Landing page

Landing page interface