Alivio 🛖

Building classification for natural disaster relief efforts

• Alivio 🛖
  • Setup
    • Prerequisites
      • Software
      • Access Keys
    • Environment Setup
    • Download & Installation
  • Scripts
    • Data Download Util
  • Directory Structure

Setup

Prerequisites

Software

The following software should be pre-installed on the system using this repository:

• conda or a virtual environment
• git for version control

Access Keys

Create the following keys if you don't have them

• GitHub Developer Access Token - to push and pull code to and from GitHub. This should be saved to the terminal or command line.
• AWS IAM Credentials - to access AWS resources remotely.
  • Access Key
  • Secret Access Key

Environment Setup

The following commands need to be run only once, during the initial setup process.

• Create a conda environment

  • Create the environment (name alivio is optional and name can be used)

    conda create --name alivio python=3.10 -y

  • Activate the environment

    conda activate alivio

  • Create a Jupyter Notebook Kernel

    conda install -c anaconda ipykernel -y
    python -m ipykernel install --user --name=alivio

• Install poetry for python dependency management

  pip install poetry

• Configure AWS Credentials. This command will open up a terminal-based prompt with 4 inputs.

  pip install awscli
  aws configure

  • Access Key: Your AWS Access Key
  • Secret Access Key: Your AWS secret access key
  • region: us-east-1
  • format: json

Download & Installation

The following commands need to be run only once, during the initial setup process.

• Clone the GitHub repository

  git clone https://github.com/cricksmaidiene/alivio

• Visit the repository locally

  cd alivio

• Install the python dependencies (make sure the alivio conda environment is active)

  poetry install --no-root

You can now start executing notebooks and code within this virtual environment.

Scripts

Data Download Util

This utility downloads relevant dataset used by the project into the /data directory

Additionally install the below package

pip install chardet

Run the below command

python src/utils/sync_data.py

Directory Structure

• /src: for all source code and notebook files

  • src/01_data_ingestion: For notebooks and source related to ingesting raw data
  • src/02_data_analysis: For EDA, visualization and other analysis tasks
  • src/03_data_engineering: For preprocessing the dataset or performing feature engineering
  • src/04_models: For model training, fine-tuning and experimentation

• /data: For all data extracts saved locally

• /docs: For internal team documentation

• /app: For the web-interface