Customized Smart Object Detection Using Yolo and R-Cnn in Machine Learning

Abstract

In this paper work, using python and OPENCV module we are detecting objects from videos and webcam. This application consists of two modules such as ‘Browse System Videos’ and ‘Start Webcam Video Tracking’. Object detection is an important task in computer vision and has numerous applications in fields such as surveillance, robotics, and autonomous driving. In this project, we aim to develop an object tracking system using Python and the OpenCV module. The system consists of two modules: "Browse System Videos" and "Start Webcam Video Tracking." The first module allows the user to select a video file from their system to track objects in, while the second module tracks objects in real-time using the user's webcam. Our system uses a combination of computer vision techniques, such as color thresholding and blob detection, to detect and track objects in the video or webcam feed. By developing this system, we hope to demonstrate the potential of Python and OpenCV for object tracking applications and inspire further development in the field.