Agricultural Disease Diagnostic Platform:

• Created a Plant Disease Diagnostic platform, utilizing Computer Vision techniques with TensorFlow to build a Deep Learning Convolutional Neural Network model achieving 92% accuracy in disease Classification.
• Implemented Training, Testing and Validation on a dataset of 20000+ Images, having 15 different Classes.
• Developed a REST API using FastAPI, achieving high performance with an average response time of 100ms
• Designed the Frontend, using ReactJS to create an user interface to upload disease images.

Technologies Used :

1. Python

• TensorFlow for building CNN Neural Network
• Matplotlib for data visualization

2. Jupyter notebook, visual studio code as IDE
3. FastAPI
4. React JS