Crop Disease Detection

• Tech Stack: Python, Flask, TensorFlow, Keras
• Github URL: Project Link

Collaborated with a team of 4 to develop a deep learning model using ResNet50V2 (pre-trained on ImageNet) that achieved 95% accuracy on a dataset of 55,000 images, enabling real-time crop disease detection for farmers.

Integrated the model into a Flask app for real-time disease detection, with predictions under 5 seconds. Used the Gemini API to deliver valuable insights on cures and prevention, enhancing support for 1,000+ users