A Practical Implementation of the Faster R-CNN Algorithm for Object Detection; detecting guns, knives and non-weapon objects from the webcam video stream:
- Setting up deep learning in Windows OS with TensorFlow.
- Processing datasets for supervised training.
- Using Google Colaboratory for cloud training.
- Applied the fundamental mechanism of machine learning for supervised learning
This project was created for my final year project. It's about using Faster R-CNN model for detecting guns, knives and non-weapon objects (can be any non-weaponry object) in a real-time video stream. The purpose of this project was not aim for high accuracy, it was for me to study the result and effect of non-weapon objects on the accuracy. In addition, this hands-on project helped me to understand the fundamental knowledge of machine learning and computer vision.
For further information and details about how I created this project, please refer to the following report written by me:
Weapon Detection Using Neural Networks in Real-Time Surveillance Video