This project primarily focused on addressing the critical issue of elephant poaching by developing a deep learning model. The project involved the following key steps:
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Data Collection:
Collected images of elephants and poachers for training the deep learning model. Additionally, gathered population statistics of African elephants to provide context.
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YOLOv5 Object Detection:
Retrained the YOLOv5 deep learning model to detect elephants and poachers.
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Email Alert System:
Implemented an email alert system to promptly notify relevant parties when the model detected the presence of a poacher.
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Tableau Data Visualization:
Utilized Tableau to create visualizations presenting elephant population statistics, offering insights into population trends and distribution.
The final project was presented using Streamlit, a web application framework, along with interactive Tableau visualizations to showcase the model's usage and project findings. By combining deep learning techniques, data analysis, and visualizations, this project aimed to enhance the understanding of poaching and contribute to its prevention.