If you’re interested in deep learning for computer vision, then you’re probably familiar with the YOLO (You Only Look Once) algorithm. Developed by Joseph Redmon, YOLO is one of the fastest and most accurate object detection deep learning models available. In this course, YOLOv7 YOLOv8: Deep Learning - Computer Vision 2023, you’ll learn how to run a YOLOv7 program from scratch and how to train a YOLOv8 model on a custom dataset. The course includes two courses in one, providing an in-depth exploration of the YOLO evolution in YOLOv1 to YOLOv8 and the advantages of YOLO compared to other deep learning models.
YOLOv7 and YOLOv8: Object Detection, Pose Estimation, Instance Segmentation, Image Classification, and More
This course covers a lot of ground, starting with the basics of how artificial neural networks work, and diving deeper into different activation functions, convolutional neural networks, and computer vision problems such as image classification, object detection, instance segmentation, and semantic segmentation.
The course provides a detailed understanding of the YOLOv7 architecture along with the latest features such as Pose Estimation and Instance Segmentation. The course also explores the new features of YOLOv8, including object tracking, along with the installation and training of YOLOv8 on a custom dataset.
In addition to learning about the algorithms themselves, you’ll learn how to find and annotate datasets using LabelImg, how to split datasets automatically, and how to visualize training results using Tensorboard. The course then provides you with the opportunity to test the trained YOLOv7 and YOLOv8 models on images, videos, and webcams.
Real World Projects using YOLOv7 and YOLOv8
The course also includes four real-world projects that allow students to apply their knowledge of YOLOv7 and YOLOv8 to practical problems. These projects include:
Robust Mask Detector
This project will teach you how to create a robust mask detector using YOLOv7 and YOLOv8, which can be deployed in public places such as hospitals, airports, and offices. This project is particularly relevant in the ongoing COVID-19 pandemic, where the use of masks is critical to preventing the spread of infection.
Weather YOLOv8 Classification Application
This project will teach you how to create a weather classification application using YOLOv8. You’ll learn how to classify images into four different weather types: sunny, cloudy, rainy, and snowy. You can use this application to automate the process of weather classification and analysis.
Coffee Leaf Diseases Segmentation Application
This project allows you to work on a challenging problem in the field of agriculture. You’ll learn how to create a coffee leaf diseases segmentation application using YOLOv8 to identify the different types of diseases that coffee crops face. This project can help farmers identify and manage crop diseases, improving crop yields and reducing waste.
YOLOv7 Squat Counter Application
If you’re interested in fitness and health, you’ll love this project. You’ll learn how to create a squat counter application using YOLOv7 that can count the number of squats performed by a person. The application can be trained to recognize correct and incorrect squat postures, providing real-time feedback and improving workout efficiency.
Course Ratings and Reviews
The YOLOv7 YOLOv8: Deep Learning - Computer Vision 2023 course has an aggregate rating of 4.57999 and has received 239 reviews. The reviews indicate that the course is well-structured, informative, and engaging, with instructors who are knowledgeable and passionate about the subject. The focus on real-world applications and projects has been particularly appreciated by students who have found the course to be practical and relevant.
In short, if you’re interested in deep learning for computer vision and want to learn the latest cutting-edge techniques, then YOLOv7 YOLOv8: Deep Learning - Computer Vision 2023 is the perfect course for you. With a combination of theory and practice, this course will provide you with the knowledge and skills you need to tackle a wide range of computer vision problems and create innovative solutions that benefit society.
