Description
Course 9 Hands-On AI: Computer Vision Projects with Ultralytics and OpenCV. This fully hands-on, project-based course teaches computer vision algorithms from the YOLO family using the Ultralytics and OpenCV libraries to solve real-world problems. The course provides a comprehensive overview of the YOLO architecture, covering essential topics such as image classification, object detection and tracking, sample segmentation, state estimation, and directional bounding boxes. Instructor Mohammad Munawar walks you through the critical processes, from data annotation and model training to exporting and optimizing for maximum inference speed, in a step-by-step, hands-on manner. The course also demonstrates how to apply Ultralytics solutions to practical challenges in machine vision, along with detailed technical implementation examples, so that participants can gain the skills needed to develop powerful, practical applications.
What you will learn
- Introduction to Ultralytics and OpenCV package:
- Introduction to Computer Vision and OpenCV.
- Basic OpenCV operations on images.
- Introducing the Ultralytics Python package.
- How to use the Ultralytics package using Python.
- Data annotation and YAML:
- How to annotate data using Label Studio.
- What are YAML Dataset files and how are they created?
- Different Ultralytics tasks and modes:
- Overview of Ultralytics tasks and modes.
- Training an object recognition and inference model.
- Automatic annotation of recognition data in segmentation format.
- Training and inference for an image segmentation model.
- How to use the Pose Estimation Model.
- And…
This course is suitable for people who:
- AI enthusiasts looking for hands-on experience in machine vision projects.
- Engineers and developers who want to use YOLO and Ultralytics algorithms for object detection and tracking.
- Data scientists who want to train and export machine vision models.
- Students and researchers seeking a deep understanding of machine vision techniques (such as segmentation and state estimation).
- Anyone who wants to learn practical Ultralytics solutions to solve real-world problems.
- Those looking to optimize inference time using model export capabilities.
Course Details Hands-On AI: Computer Vision Projects with Ultralytics and OpenCV
- Publisher: LinkedIn
- Instructor: Rizwan Munawar
- Education level: Intermediate
- Training duration: 3 hours and 34 minutes
Course headings
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
1.6 GB
