Learn to build real time object detection engine using YOLO deep learning algorithm. Deep learning is popular where a machine can be trained to detect objects in video and images. Once trained, it can be used to detect objects in any video or image.
Yolo (You only look Once) algorithm has become popular because of its real time nature. It can detect objects at 45 frames per second or within 20 ms. This makes it attractive to use it in self driving car where detecting objects in real time is key to avoid collisions. Unlike its predecessor, YOLO looks at image only once.
Build a strong foundation in image search engines with this tutorial for beginners.
- Understanding fundamentals of YOLO
- Understanding fundamentals of deep learning
- Benefits of YOLO for self driving car use case
- Build a real life object detection in video using YOLO, OpenCV and Python
- A Powerful Skill at Your Fingertips Learning the fundamentals of real time object detection puts a powerful and very useful tool at your fingertips. Python, YOLO and opencv are free, easy to learn, has excellent documentation.
No prior knowledge of CNN or deep learning is assumed. I’ll be covering topics like CNN from scratch.
Jobs in object detection area are plentiful, and being able to learn real time object detection will give you a strong edge. YOLO is state of art technology that can quickly help you achieve your goal.
Learning object detection with YOLO will help you become a computer vision developer which is in high demand.
