Van Seva is an innovative application that harnesses the power of image analytics and machine learning to revolutionize forestry management. By automating tree enumeration, detecting leaf diseases, analyzing green cover, optimizing pathing, and leveraging historical data, this platform empowers forestry experts to make data-driven decisions and maintain the health of our natural ecosystems.

Our tree enumeration model, trained using YOLOv5 and PyTorch, ensures high accuracy and efficiency in identifying and counting trees. The model's training involved extensive data preparation, including annotated images and data augmentation techniques, to enhance its robustness. Additionally, the application features green cover analysis to monitor vegetation health and changes over time, and optimal pathing to facilitate efficient navigation and resource allocation within forest areas.

By integrating historical data, Van Seva provides valuable insights into long-term environmental trends, enabling proactive and informed forestry management. This comprehensive approach not only enhances decision-making but also contributes to sustainable forest conservation efforts.