A frontend web app for viewing & labeling camera trap data by The Nature Conservancy.
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Overview
Animl is an open, extensible, cloud-based platform for managing camera trap data. We are developing this platform because there currently are no software tools that allow organizations using camera traps to:
This repository contains the frontend web application for viewing and interacting with the camera trap data. It is a React app, using Redux (specifically Redux Toolkit) for state management and Vite for tooling.
In the project directory, you can run:
npm start
Runs the app in the development mode.
Open http://localhost:5173 to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
npm run build
Builds the app for production to the build
folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
npm run build:staging
Builds the app for deployment to the staging environment.
It will request backend resources that are also in their respective staging environments.
npm run deploy-dev
& npm run deploy-prod
Builds the app for deployment and deploys it to dev/production environment.
Use caution when deploying to production, as the application involves multiple stacks (animl-ingest, animl-api, animl-frontend), and often the deployments need to be synchronized. For major deployments to prod in which there are breaking changes that affect the other components of the stack, follow these steps:
Set the frontend IN_MAINTENANCE_MODE
to true
(in animl-frontend/src/config.js
), deploy to prod, then invalidate its cloudfront cache. This will temporarily prevent users from interacting with the frontend (editing labels, bulk uploading images, etc.) while the rest of the updates are being deployed.
Set ingest-image's IN_MAINTENANCE_MODE
to true
(in animl-ingest/ingest-image/task.js
) and deploy to prod. While in maintenance mode, any images from wireless cameras that happen to get sent to the ingestion bucket will be routed instead to the animl-images-parkinglot-prod
bucket so that Animl isn't trying to process new images while the updates are being deployed.
Wait for messages in ALL SQS queues to wind down to zero (i.e., if there's currently a bulk upload job being processed, wait for it to finish).
Backup prod DB by running npm run export-db-prod
from the animl-api
project root.
Deploy animl-api to prod.
Turn off IN_MAINTENANCE_MODE
in animl-frontend and animl-ingest, and deploy both to prod, and clear cloudfront cache.
Copy any images that happened to land in animl-images-parkinglot-prod
while the stacks were being deployed to animl-images-ingestion-prod
, and then delete them from the parking lot bucket.