Skip to article frontmatterSkip to article content

Detecting floating objects using deep learning and Sentinel-2 imagery

Authors
Affiliations
ESA Phi-Lab
ESA Phi-Lab

Continuous integration badge Binder doi notebook review

thumbnail

How to run

Running on Binder

The notebook is designed to be launched from Binder.

Click the Launch Binder button at the top level of the repository

Running locally

You may also download the notebook from GitHub to run it locally:

  1. Open your terminal

  2. Check your conda install with conda --version. If you don’t have conda, install it by following these instructions (see here)

  3. Clone the repository

    git clone https://github.com/eds-book-gallery/b34facfa-cea8-48f5-89f6-f11ce00812a9.git
  4. Move into the cloned repository

    cd b34facfa-cea8-48f5-89f6-f11ce00812a9
  5. Create and activate your environment from the .binder/environment.yml file

    conda env create -f .binder/environment.yml
    conda activate b34facfa-cea8-48f5-89f6-f11ce00812a9
  6. Launch the jupyter interface of your preference, notebook, jupyter notebook or lab jupyter lab

References
  1. Mifdal, J., & Carmo, R. (2025). Detecting floating objects using deep learning and Sentinel-2 imagery (Jupyter Notebook) published in the Environmental Data Science book. Zenodo. 10.5281/ZENODO.8308843