Course Description:

If you are interested in exploring the dynamic field of computer vision and deep learning or simply want to build small projects for fun, the Object Tracking, Detection, Car Speed, Pose Estim in Python Course is for you. This paper mainly focuses on providing learners with theoretical and practical knowledge to execute object tracking, vehicle speed estimation, object detection, segmentation, and pose estimation using Python. This course prepares individuals to develop systems capable of interpreting visual data in different environments.

Object tracking is one of the key components of Object Tracking, Detection, Car Speed, Pose Estim in Python Course, in which participants will implement techniques to detect and track the objects in videos using state-of-the-art algorithms like BotSort and ByteTrack. We also cover vehicle speed estimation, i.e. how to mathematically calculate speed from object tracking and time and distance data, which is a very practical skill for monitoring and monitoring traffic. The course also includes pose estimation, where the ability to determine the arrangement of landmarks in the spatial coordinates (i.e., the key points) of objects such as joints or landmarks is introduced.

They’ll also learn about object segmentation and detection on custom datasets (segmenting objects at the pixel level or classifying them with their bounding boxes, labels, and confidence scores). The last topic is object classification: students learn to classify entire images into pre-defined classes. Hands-on training is provided to make the course a step-by-step problem-solving exercise and practical demonstration.