Computer Vision - Object Detection with OpenCV and Python from Coursera

In this 1-hour long project-based course, you will learn how to do Computer Vision Object Detection from Images and Videos. At the end of the project, you'll have learned how to detect faces, eyes and a combination of them both from images, how to detect people walking and cars moving from videos and finally how to detect a car's plate. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should have a fundamental knowledge of Python and OpenCV. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

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Well-suited for learners with a fundamental understanding of Python and OpenCV, making it accessible to learners with intermediate-level programming skills

Instructs learners on detecting faces, eyes, people, cars, and license plates in images and videos, providing practical skills in computer vision

Utilizes hands-on project-based learning in a cloud desktop environment, offering learners real-world experience with the tools and technologies used in computer vision

Access to pre-configured cloud desktops with necessary software and data eliminates setup hassles and allows learners to focus on the project

Note that the cloud desktop has limited access (5 times), which may be a potential limitation for learners who require more practice

Designed for learners in the North America region, indicating geographical limitations for accessibility

Reviews summary

Object detection with opencv and python

This beginner-friendly course teaches you how to do Computer Vision Object Detection from Images and Videos using OpenCV and Python. After completing this project, you will be able to detect faces, eyes, bodies, cars, and car plates in images and videos.

Hands-on learning experience.

"The Hands on Project is Always best to learn as you implement while you are doing ."

"The link for ungraded external tool leads to another project named "Video Basics with OpenCV and Python" on Rhyme, please fix it soon. Everything else is good."

"The course was pretty amazing, especially the tutor was nice and I could understand everything he explained and I am in love with Rhyme, it makes learning so easy."

Suitable for learners with little to no experience.

"Good for beginers."

"This course is good for beginners"

Great project for beginners.

"The course was quite good , and I learn a lot of things which are required for my project"

The course is incomplete.

"The Course is not Complete,why can i only watch the first week?"

"This course is incomplete. Only has face detection, the cloud desktop lags a lot."

"The link added to this course is that of "Computer Vision: Video Basics with OpenCV and Python", no point in enrolling for this course."

"The instructor does NOT know how to code in Python I do NOT recommend him. He does not explain the classification methods in any way."

"Unfortunately I was not satisfied with this course. For all tasks the same method of detection is used and theory and method parameters are not explained."

"Total waste of time. Instructor is using prepared files as classifiers and he didn't even bother to explain how they really work. And they work bad (detect other objects on images), but he didn't care. Course is about writing some short Python snippets, not CV or Object Detection. Also instructor speaks English very poorly."

"The tasks addressed in this guided project are all the same. No explanation is provided about why the process or the functions used. It feels like a 30 minute youtube tutorial that could be cut to 5 (since the 6 tasks are the same) where the "instructor" reads what he writes."

The course material is repetitive.

"Fun use cases, but too repetitive."

"It is really bad, it is just a video copy pasting code lines without giving any information / input about the libraries and how they works. The instructor does not give any value added, he does not explain anything and the detections he is running are even not working (a lot of missed persons / cars / faces and false positives) and he does not even explain how to fix. All notebooks consists of the same 4-5 OpenCV APIs, so it is really a waste of time and money."

"I finished it in less than 10 minutes as all the topics were sort of repetition of the first topic."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Computer Vision - Object Detection with OpenCV and Python with these activities:

Review Python Fundamentals

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By reviewing Python fundamentals, you can build a strong foundation for the course topics.

Browse courses on Python

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Review core Python syntax, including variables, data types, and control flow.
Practice writing simple Python programs.

Practice Image Processing with OpenCV

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Targeted practice with OpenCV will help you develop proficiency in image processing techniques.

Browse courses on OpenCV

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Complete a series of OpenCV tutorials on basic image operations.
Solve coding challenges involving image manipulation.

Build a Computer Vision Object Detection App

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Solidify your understanding of Computer Vision Object Detection by applying the concepts to a practical project.

Browse courses on Computer Vision

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Gather the necessary data and resources
Design and implement a pipeline for object detection
Evaluate the performance of your model

Two other activities

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Explore Object Detection Techniques

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Exploring object detection techniques beyond the course will broaden your understanding.

Browse courses on Object Detection

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Follow online tutorials on advanced object detection algorithms.
Read research papers on state-of-the-art object detection models.

Develop a Simple Object Detection Application

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Hands-on application development will solidify your understanding of object detection.

Browse courses on Object Detection

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Design and implement an object detection application using Python and OpenCV.

Career center

Learners who complete Computer Vision - Object Detection with OpenCV and Python will develop knowledge and skills that may be useful to these careers:

Computer Vision Engineer

Computer Vision Engineers build and maintain computer systems that can "see" and analyze images and videos. They often specialize in a particular area of computer vision, such as object detection. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection. It will help you develop foundational skills in computer vision and object detection, which can prepare you for a career as a Computer Vision Engineer.

See salaries and explore the career path for Computer Vision Engineer

Machine Learning Engineer

Machine Learning Engineers build and maintain machine learning systems. They may use computer vision to train models to detect objects. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers design, develop, and maintain software applications. They may use computer vision to add features such as object detection to software applications. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Software Engineer.

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Data Scientist

Data Scientists use data to solve business problems. They may use computer vision to analyze images and videos to extract insights. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Data Scientist.

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Robotics Engineer

Robotics Engineers design and build robots. They may use computer vision to help robots navigate and interact with their environment. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Robotics Engineer.

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Product Manager

Product Managers are responsible for the development and launch of new products. They may use computer vision to understand customer needs and develop products that meet those needs. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Product Manager.

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Market Researcher

Market Researchers study consumer behavior and trends. They may use computer vision to analyze images and videos to understand consumer preferences. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Market Researcher.

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Business Analyst

Business Analysts use data to help businesses make better decisions. They may use computer vision to analyze images and videos to extract insights. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Business Analyst.

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Data Analyst

Data Analysts use data to help businesses make better decisions. They may use computer vision to analyze images and videos to extract insights. The course you are considering, Computer Vision - Object Detection with OpenCV and Python, provides a foundation in the fundamentals of computer vision and object detection, which may be helpful for a career as a Data Analyst.

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Product Designer

Product Designers design the user experience for products. They may use computer vision to improve the user experience by making it easier for users to interact with products.

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Interaction Designer

Interaction Designers design how users interact with products. They may use computer vision to improve the user experience by making it easier for users to interact with products.

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User Experience Designer

User Experience Designers design the user interface for websites and apps. They may use computer vision to improve the user experience by making it easier for users to interact with products.

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Back-End Developer

Back-End Developers design and develop the server-side logic for websites and apps. They may use computer vision to add features such as object detection to websites and apps.

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Front-End Developer

Front-End Developers design and develop the user interface for websites and apps. They may use computer vision to add features such as object detection to websites and apps.

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Full-Stack Developer

Full-Stack Developers design and develop both the front-end and back-end of websites and apps. They may use computer vision to add features such as object detection to websites and apps.

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