Inspiration
With climate change threatening biodiversity, we wanted to create a tool that helps people recognize and learn about wildlife. By using AI, we aim to raise awareness and promote conservation efforts. What it does
WildVision allows users to upload an image of an animal, and our AI-powered system identifies the species. In the future, we plan to integrate extinction risk data to educate users on conservation efforts. How we built it
Frontend: React with Vite and Tailwind CSS for a sleek and responsive UI.
Backend: Flask to handle API requests and process images.
AI Model: OpenAI's vision model for accurate animal identification.
Infrastructure: Flask API connects the frontend to the AI model, enabling seamless communication.
Challenges we ran into
Learning how to integrate OpenAI’s API with Flask.
Setting up CORS to allow communication between the frontend and backend.
Managing file uploads and handling image data properly.
Debugging and optimizing API requests for faster responses.
Accomplishments that we're proud of
Building a fully functional AI-powered application within a short time frame.
Learning and implementing React, Flask, and API integration from scratch.
Overcoming debugging challenges to create a seamless user experience.
What we learned
How to set up and structure a React- and Flask-based project.
The fundamentals of handling image uploads and API communication.
The importance of user experience and design when creating a web application.
What's next for WildVision
Integrating conservation data to provide users with extinction risk statistics.
Enhancing AI accuracy with additional datasets.
Expanding the platform to support more wildlife-related insights and community engagement.
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