This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass.
GitHub Repository: PlantGuard AI on GitHub
Live Demo: Try PlantGuard AI
In an age where developers and tech workers spend 8 to 10 hours a day glued to glowing screens, our connection with the physical, living world can easily deteriorate. When a beloved balcony tomato plant develops yellow halos or an apple tree shows olive-green spots, our modern reflex is to grab a phone, search endlessly, and sink deeper into screen fatigue.
Existing commercial plant identification apps can make this experience even more frustrating:
PlantGuard AI was built to offer a different approach.
Created for the Hacktoberfest Open-Source AI Challenge Week 1: “Touch Grass,” PlantGuard AI is an open-source plant disease screening tool and garden care companion designed to run locally.
It uses open-weight computer vision not to keep you glued to your screen, but to help you step away from your desk, get some sunlight, and reconnect with your garden.
🌱 Explore the project: GitHub Repository
PlantGuard AI uses a MobileNetV2 architecture fine-tuned on the PlantVillage dataset to identify visual patterns associated with plant diseases and healthy leaves.
These results represent the project's reported benchmark performance, not a guarantee of accuracy for every real-world garden condition.
PlantGuard AI treats AI predictions as probabilistic screening aids, not definitive diagnoses.
Each of the 38 classes includes a human-reviewed care profile designed to help users understand symptoms and choose sensible next steps.
Profiles include:
Recommendations are intended as general gardening guidance. Treatments should be selected according to the plant, likely cause, and local growing conditions.
This is the heart of PlantGuard AI.
Instead of ending with an AI prediction, the application gives users a customized checklist that encourages them to inspect their plants outdoors.
Interactive Milestone Rewards: After completing the outdoor inspection, users can click “Mark Outdoor Inspection Complete” to record their garden visit and celebrate time spent caring for living plants.
The goal is simple: use AI as a bridge to real-world action, not as another reason to stay indoors.
The desktop application stores scan history, prediction confidence, personal notes, and outdoor follow-up statuses in a local SQLite database:
data/journal.db
Features include:
Pending Outdoor Check, Grass Touched: Inspected Outdoors, and Recovering.
Privacy by design: The local desktop workflow is designed to keep plant photos, notes, and inference on the user's machine rather than up them to third-party servers.
The browser-based showcase uses browser localStorage for its client-side journal, which is separate from the desktop application's SQLite database.
Experience PlantGuard AI in two ways.
Try it here: Open the Interactive GitHub Pages Demo
You can explore the interactive showcase from a phone, tablet, or desktop browser.
What you can do:
localStorage.
Note: The browser showcase and the full local desktop application are separate experiences. Check the repository documentation for the implementation details and capabilities of each.
Run the Python application locally to explore the complete desktop workflow.
Prerequisites
Quickstart Commands
git clone https://github.com/lalit-oli-mohan-479/PlantGuard-AI---Open-Source-Plant-Disease-Detector.git
cd PlantGuard-AI---Open-Source-Plant-Disease-Detector
pip install -r requirements.txt
python app.py
Get the code: View the PlantGuard AI GitHub Repository
PlantGuard AI is built around a simple idea: technology should help us engage more meaningfully with the world around us.
By combining accessible computer vision, transparent prediction confidence, local data storage, and practical gardening checklists, the project aims to make plant health screening more approachable while encouraging users to spend less time scrolling and more time caring for their plants.
It is not about replacing hands-on gardening expertise. It is about using AI to help people ask better questions, inspect their plants more carefully, and take informed next steps.
PlantGuard AI is an open-source project, and contributions are welcome.
🌱 GitHub: Star the repository, explore the code, or contribute
🌐 Live Demo: Try PlantGuard AI
Built for Hacktoberfest. Inspired by nature. Designed to bring people back to their gardens.
Touch grass. Inspect a leaf. Let AI help you take the next step. 🌿