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It's a web application built on the Flask framework, incorporating a model trained using transfer learning with VGG16. Developed a model to classify diseases affecting Tomato plants based on images of their leaves. Utilized deep learning techniques to analyze leaf images and identify specific disease types. Implemented using TensorFlow, the model achieved accurate disease classification for effective plant health monitoring.

• Implemented a Tensorflow model using Transfer Learning.
• The model was trained on the Google Colab for 9 epochs
• Employed the VGG19 model for transfer learning.
• Achieved an impressive validation accuracy of 86%.
• Demonstrated a validation loss of less than 0.4315, highlighting strong performance in model validation.

http://188.166.153.41/

• The dataset is hosted on Kaggle.
• Dataset Link: Tomato Dataset on Kaggle
• The dataset comprises 10 categories, including 9 types of tomato diseases and one category for healthy tomatoes.