BioCLIP Flickr Analysis

This repo serves as a proof of concept of analyzing species distribution from a social media source. It leverages Flickr as a source of input images, and BioCLIP as a species identification model.

Folder structure

This folder structure is based off a template. Not all of the folders are currently in use. The analysis entrypoing is src/Python/app.py, which calls the Flickr API and sends the results through BioCLIP. The input is a set of arguments to the Flickr API, currently representing a bounding box and a keyword search.

├── data
├── figs
├── notebooks
├── output
├── paper
├── pipeline
└── src
    └── Python

• data/ - raw data only
• figs/ - static figures generated during pipeline
• notebooks/ - literate programming files (e.g., Jupyter, Quarto) explaining the pipeline
• output/ - derived data generated during pipeline
• pipeline/ - pipeline scripts
• src/ - source files supporting the pipeline (e.g., functions, classes, constants)

Computational environment

This script is intended to be run in Docker using the commands below. This should work outside of Docker as well, provided that the data path is updated.

├── Dockerfile
└── requirements.txt

These are conventional files used for recording package dependencies.

requirements.txt is a file used to record Python package dependencies. Users can install dependencies by running pip install -r requirements.txt at the command line.

Dockerfile defines a full computational environment. You can build and run the container using:

To build:

IMAGE=bioclip-flickr
docker build -t $IMAGE .

To run as-is:

docker run -it $IMAGE

To run while changing the data or the src code directory:

docker run -it \
    -v $PWD/src/Python:/app \
    -v $PWD/data:/app/data \
    -v $PWD/output:/app/output \
    -v $PWD/notebooks:/app/notebooks \
    $IMAGE

Works in Progress

Two other branches exist with varying works in progress.