slvDev
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esp32-ai
A 28.9 million parameter language model runs on an $8 ESP32-S3 microcontroller entirely on-device, generating simple stories at about 9.5 tokens per second.
Plant-Disease-Detection
A Flask web application that uses a PyTorch EfficientNet-B5 model to classify plant leaf diseases from photos, returning predictions, confidence scores, treatment guidance, and location-based agriculture support.
Stars
4
7-day growth
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Forks
1
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0
License
MIT
Last updated
2026-07-29
AI repository intelligence
FR-AI / ANALYSISWhy it is worth attention
It combines a state-of-the-art deep learning model with practical, actionable outputs such as treatment advice and nearby agriculture services, all in a deployable web app.
Who it is for
- Farmers and agricultural workers
- Agricultural extension officers and advisors
- Plant pathologists and researchers
- Hobbyist gardeners and plant enthusiasts
Use cases
- Identifying plant diseases from mobile or laptop leaf images
- Getting organic and chemical treatment recommendations
- Locating nearby agriculture support services based on browser location
- Educational tool for learning about plant disease symptoms and management
Strengths
- Uses EfficientNet-B5, a powerful and efficient image classification architecture
- Provides top-3 predictions with confidence scores and detailed treatment guidance
- Supports multiple Indian languages via Deep Translator and location-based help via OpenStreetMap
- Includes Gunicorn deployment configuration and Git LFS for large model hosting
Considerations
- Requires Git LFS setup to download the large model checkpoint
- Predictions are for informational purposes only; users must consult local experts for critical decisions
- Dataset is not included and must be downloaded separately if training is desired
README quick start
Installation
Description
AI-powered Plant Disease Detection using EfficientNet-B5, Flask, PyTorch, and multilingual support.
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