Welcome to the OpenCV with Python (Computer Vision) course. This course is designed for students who are interested in the field of computer vision or deep learning, covering core concepts for image and video processing from basic to advance. Nowadays, computer vision is used in automation in every domain, including self-driving cars, security, warehouses, object tracking, feature matching, and many more.
Course Description
The OpenCV course with Python: Using Python Learn Computer Vision Course on OpenCV in Python from Basic to Advance provides a practical approach to explain the core concepts of image and video processing. The course also covers the fundamental theoretical knowledge. This course is best for students who want to start their career as a computer vision engineer.
Distance learning has been expanding over the years, and the Covid-19 pandemic has increased the demand for online courses further. Udemy courses provide a feasible solution for learners who are interested in computer vision to pursue this field, at their own pace and convenience.
Course Content
The course contents are divided into chapters, each providing a comprehensive understanding of the core concepts of image and video processing.
- Image Read: Learn the basic operation to read an image in OpenCV.
- Image Crop: Understand how to crop an image in OpenCV.
- Image Resize: Master the technique to resize an image in OpenCV.
- Image Rotate: Obtain the knowledge to rotate an image in OpenCV.
- Image Split: Comprehend the crucial steps to split an image into RGB channels.
- Image Save: Learn how to save an image using OpenCV.
- Video Read: Get to grips with how to read a video in OpenCV.
- Video Resize: Master the technique to resize a video in OpenCV.
- Video Save: Understant how to save a video using OpenCV.
- Draw a Circle on the Image: Comprehend how to draw a circle on an image using OpenCV.
- Adding Text Messages to Images: Learn how to add text on an image using OpenCV.
- Draw Line Segment on Image: Discover how to draw line segments on an image using OpenCV.
- Draw a Rectangle on the Image: Obtain the skills to draw rectangles on an image using OpenCV.
- Draw an Ellipse on the Image: Learn the technique to draw ellipses on images using OpenCV.
- Arithmetic Operation: Understand how to perform basic arithmetic operations such as addition and subtraction using OpenCV.
- Image Blending: Get to grips with the blending of two images in OpenCV.
- Threshold and Blurring: Comprehend how to perform thresholding and blurring of images in OpenCV.
- Area and Perimeter of Contours: Master the technique to calculate the area and perimeter of contours in OpenCV.
- Find Contours in an Image: Learn how to find contours in an image using OpenCV.
- Fitting Shape on the Contours: Comprehend how to fit the shape of contours into a rectangular box using OpenCV.
- Checkpoint if inside, outside, or on the Contours: Obtain the skills to check if a point is inside, outside, or on the contour using OpenCV.
- SIFT - (Scale - Invariant Feature Transform): Learn how to use the SIFT algorithm for feature detection and description in OpenCV.
- Feature Matching: Master the technique to match features extracted from two images using OpenCV.
- And Much More!
If you have any queries regarding the course, please don't hesitate to message the instructor through the Udemy Q&A board. The course has received a rating aggregate of 4.44878 from 38 reviews, which indicates the course's quality and relevance to today's industrial needs.
Why Learn OpenCV with Python (Computer Vision)?
The field of computer vision is expanding very fast, and salient opportunities are emerging in every domain. For instance, self-driving cars use computer vision to make decisions based on the environmental data recorded through many sensors mounted on the vehicle. Similarly, security cameras use computer vision to detect faces to reduce crime rates and secure people's belongings. In addition, warehouses use computer vision to shorten their storage and retrieval processes.
Moreover, various applications of computer vision use deep learning, neural networks, and machine learning algorithms to attain good results and accuracy. The OpenCV with Python (Computer Vision) course provides essential knowledge and skills for students to pursue a career in computer vision.
Who Should Take This Course?
The course is designed for students who are interested in computer vision and want to gain a comprehensive understanding of the core concepts of image and video processing. No prior knowledge is required to take this course.
The course does not require you to have a powerful system or a NVIDIA graphics card to run deep learning models. The course is designed for beginners, intermediate-level students, and experienced learners who want to brush up their knowledge of Python and computer vision.
After completing this course, students can start their career as a computer vision engineer or data scientist. The course's project-based approach strengthens the student's understanding and skills to apply theoretical knowledge to perform real-world tasks.
Wrapping Up
The OpenCV with Python (Computer Vision) course covers all necessary topics, providing a comprehensive understanding of the core concepts of image and video processing from basic to advance. The course's practical approach, along with theoretical knowledge, enhances the student's understanding and applications in computer vision.
The course is best suited for beginners, intermediate-level learners, and experienced students, who want to gain or brush up their skills in computer vision. The course has received a rating aggregate of 4.44878 from 38 reviews, indicating the course's quality and relevance to today's industrial needs. So, if you're interested in pursuing a career in computer vision, then the OpenCV with Python (Computer Vision) course is for you.
