This repository contains the code for a deep learning-based grape disease detection system. The project uses Convolutional Neural Networks (CNN) to accurately identify various grape diseases from images, achieving 98% accuracy. It also includes a web interface for users to upload images and get disease predictions and remedies.
- High Accuracy: 98% accuracy in detecting grape diseases.
- Web Interface: Upload images and get instant predictions and remedies.
- CNNs for robust image classification
- Data Augmentation
- Pooling layers to reduce dimensions
- Dropout regularization to prevent overfitting
- Hyperparameter Tuning for improving efficiency
- Tensorflow input pipelines for efficient data handling
- Basic insights on FastAPI
This project has been a fantastic opportunity to implement my understanding of deep learning concepts while exploring new technologies(like FastAPI for deployment, tf input pipelines, etc).
I am excited to continue learning and contributing to innovations that benefit our society. #MachineLearning #DeepLearning #DataScience