Enroll Course: https://www.udemy.com/course/opencv-2/
Are you fascinated by the power of computer vision and eager to dive into the world of deep learning? Look no further than the Udemy course, ‘[OpenCV] 파이썬 딥러닝 영상처리 프로젝트 2 – 불량사과를 찾아라!’ (OpenCV Python Deep Learning Image Processing Project 2 – Find the Defective Apples!). This comprehensive course offers a hands-on, project-driven approach to learning essential image and video processing techniques, culminating in practical deep learning applications.
The course begins by building a strong foundation in OpenCV, the cornerstone of computer vision. You’ll learn how to manipulate images and videos, preparing you for more advanced concepts. The curriculum then seamlessly transitions into the exciting realm of deep learning, with a particular focus on object detection using YOLO. You’ll gather and process custom data to train YOLO models for identifying specific objects, such as defective apples and oranges. The course leverages Google Colab and Darknet for practical training of custom data YOLO models.
Beyond object detection, you’ll explore various object tracking techniques, enabling you to follow moving objects efficiently. The course demonstrates how to count people in video streams and track faces using OpenCV’s tracking capabilities. To enhance facial recognition accuracy, you’ll delve into Face Landmark and Alignment techniques. A particularly engaging project involves using Face Landmark and EAR to build a drowsiness detection system, showcasing the practical applications of these concepts.
Furthermore, the course empowers you to estimate age and gender from facial recognition using deep learning. The importance of Face Landmark and Alignment techniques for improving facial recognition accuracy is emphasized throughout.
A significant portion of the course is dedicated to understanding and implementing YOLO for object detection in images and videos. You’ll also learn to train models using Keras with the same dataset used for YOLO, allowing for a comparative study of these powerful tools.
Tooling is a key aspect, and this course expertly guides you through setting up and utilizing essential software, primarily focusing on OpenCV and Python, the powerhouses of computer vision. Additional useful software installations are explained step-by-step within the lectures.
What sets this course apart is its practical, real-world application of deep learning and machine learning. It doesn’t just cover theoretical explanations of Computer Vision but immerses you in practical projects that solidify your understanding. The instructor emphasizes that computer vision and data science are accessible to everyone, regardless of their academic background. With passion and dedication, anyone can learn and apply these powerful techniques.
Whether you’re a beginner looking to enter the field of computer vision or an intermediate learner aiming to deepen your deep learning skills, this course provides a robust and engaging learning experience. Highly recommended for anyone wanting to build practical computer vision projects!
Enroll Course: https://www.udemy.com/course/opencv-2/