This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass Most nature apps try to keep you looking at your phone. WildLens was built with the opposite philosophy: make the screen the shortest part of your outdoor experience.
WildLens is an open-source field companion and naturalist guide designed for hikers, curious neighborhood walkers, biology students, and families exploring local parks.
It does three core things:
The complete source code is public and open-source under the MIT license on GitHub:
An intuitive field naturalist guide and biodiversity companion. Discover, identify, and document the living world around you.
[Overview](https://github.com/ayushg-1506/WildLens#overview) •
[Screenshots](https://github.com/ayushg-1506/WildLens#screenshots) •
[Key Features](https://github.com/ayushg-1506/WildLens#key-features) •
[Tech Stack](https://github.com/ayushg-1506/WildLens#architecture--tech-stack) •
[Project Structure](https://github.com/ayushg-1506/WildLens#project-structure) •
[Design Principles](https://github.com/ayushg-1506/WildLens#design-principles) •
[License](https://github.com/ayushg-1506/WildLens#license)
WildLens is an open-source nature companion built to get people off their screens and back into the soil. Whether you're hiking a mountain ridge, strolling through a city park, or exploring your own backyard, WildLens transforms curious outdoor walks into rich ecological learning experiences.
Point your camera or upload a photo of any flower, tree bark, raptor, pollinator, or fungi. WildLens instantly delivers taxonomic classification, field safety warnings (toxic lookalikes, edible traits, handling precautions), distinguishing morphological markers, and narrated audio guides.
When you're ready to head outside, generate a Seasonal Outdoor Quest with habitat-specific scavenger hunts and log every observation directly to your private, offline-first Nature Field Journal.
🔗 Live Deployment…
Direct link: https://github.com/ayushg-1506/WildLens WildLens is built with a lightweight, modern open-source stack designed for responsiveness and privacy:
src/lib/ai.ts) that extracts strict, structured JSON representing taxonomic hierarchy, lookalike distinguishing markers, habitat patterns, and safety warnings.localStorage, ensuring field notes, sightings, and photos stay private and accessible without cell service.
When you are out in nature, software shouldn't get in your way:
render.yaml blueprint configuration.