Learn Computer Vision with OpenCV Library using Python

When you watch the promo above you, can see that I have taken a practical approach in explaining computer vision concepts using the image and video processing library OpenCV. Furthermore the practical approach I have taken, involves writing and implementing code in a way that a complete beginner will be able to follow along and understand.

What you will love about this course ,is that it is easy to follow along with. All you have to do is watch what I do and try to implement it yourself. I have tried to explain some the functions as simple and brief as possible so that a complete beginner would be able to understand.This course is for you if you are interested in computer vision and want to learn how to use the OpenCv library.

🏫 **Course Overview:** The course offers a basic introduction to OpenCV and computer vision concepts for beginners. It is generally well-received for its free offering, with the instructor being commended for their clear and detailed explanations in earlier sections of the course. The tutorials before chapter 6 are considered good and understandable. **Pros:** - **Beginner-Friendly:** Ideal for those just starting out with OpenCV, providing a solid foundation. - **Clear Instructions:** Earlier parts of the course are praised for their clarity and concise explanations. - **Sample Code:** Useful examples that help learners understand how to implement OpenCV functions. - **Engaging Content:** For most learners, the initial videos are very good and the content is engaging. - **Comprehensive Coverage:** Covers a wide range of topics relevant to image processing and computer vision. - **Gratitude for Effort:** Some learners expressed gratitude for the course and suggested additional tutorials they would like to see. **Cons:** - **Pace and Depth:** Starting from chapter 6, some learners felt the course goes too fast, making it hard to follow and desiring more comprehensive explanations. - **Audio Clarity:** Some learners pointed out the audio being less audible, necessitating them to listen closely. - **Lack of Explanation:** There is a common theme across reviews that more explanation of algorithms, syntax, and functions used is needed for better understanding. - **Assumptions in Code:** Assumptions made in the code, such as where images are coming from, may confuse newcomers to CV. - **Incomplete Explanations:** Some learners felt the course lacked complete explanations of terms like "kernel," "translation matrix," and other crucial concepts. - **Practical Application:** There is a need for exercises or quizzes to apply what's been learned and practice it. - **Resources Availability:** A few reviews mentioned the absence of images and videos used in the course, which would help learners follow along more effectively on their own machines. - **Background Noise:** Some distracting noises in the background of later videos may hinder learning. - **Course Limitations:** The course is seen as somewhat below expectations for those looking for detailed inner workings of the code and a deeper dive into OpenCV's libraries. - **Content Depth:** The content is described as skeletal and would benefit from being more fleshed out, especially in sections that feel repetitive or lack depth. **General Feedback:** The course receives mixed reviews with a positive leaning towards its introduction to OpenCV and computer vision. The instructor's efforts are generally commended, and the course is seen as a good starting point for beginners. However, there is a consensus that to enhance the learning experience, more comprehensive explanations, practical exercises, better audio clarity, and additional resources would be beneficial. **Recommendation:** For those new to OpenCV and computer vision, this course provides a solid foundation with clear instructions and useful examples. However, advanced learners or those seeking in-depth knowledge of the underlying algorithms and code mechanics may find the course lacking in certain areas. It is recommended that learners supplement this course with additional resources for a more comprehensive understanding.