AgroML

Tech: Python, Flask, PyTorch, HTML, CSS, JavaScript, Svelte, Scikit-learn, AWS

• Features: Full-stack web application Recommendation system has three features Crop Prediction, Crop Yield, and Plant Disease Detection.

• Full-stack: Machine Learning + Deep Learning based web application(Agriculture domain) develop on Svelte and integrated front-end & back-end with FLask API & deployed using AWS(EC2 instance).

• ML+DL models: Crop prediction(Multi-class classification analysis) we used Random Forest gives 99% accuracy Crop yield(Regression analysis) used DecisionTreeRegressor gives 98.2% accuracy & Plant disease used ResNet architecture gives 99.2% accuracy.

Built with 🛠️

Demo

Home Page

Crop Prediction 🌾🚜

Crop Yield Analysis 👨‍🌾

Plant Disease Detection ☘️

Supported crops

• Apple
• Blueberry
• Cherry
• Corn
• Grape
• Pepper
• Orange
• Peach
• Potato
• Soybean
• Strawberry
• Tomato
• Squash
• Raspberry

System Design