🌿 Crop Disease Detection Web Application This web application helps farmers and agricultural researchers detect and classify crop diseases from images using deep learning models like ResNet and VGG19. The model is trained on the PlantVillage dataset and deployed via a Flask backend with an intuitive frontend interface.
🚀 Features Upload crop leaf images and get disease diagnosis instantly Uses pretrained deep learning models (ResNet50 & VGG19) for accurate classification Integrated with Flask for backend model serving Responsive web frontend for ease of use Supports multiple crop types and diseases Recommends remedies based on the detected disease
🧠 Model Architecture: ResNet50 / VGG19 Dataset: PlantVillage Accuracy: ~98% on validation dataset Frameworks Used: TensorFlow / Keras
🛠️ Tech Stack Frontend: HTML, CSS, JavaScript Backend: Flask (Python) Model Serving: TensorFlow/Keras .keras model Others: OpenCV, NumPy, Matplotlib (for preprocessing and visualization)