OpenCV For Beginners (2024)

OpenCV For Beginners - Start Your AI Journey!

Learn to build exciting Computer Vision applications.

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Have you ever wondered howInstagram filterswork?

Or, how computers performface detectionin crowds?

Are you curious how virtual meeting applicationsblur the backgroundor replace the background with other images?

How doself-driving cars navigate safelyin a busy city environment?

Also, isn’t it amazing how theball is trackedwith such accuracy in televised sporting events such as Tennis, Soccer, and Basketball?

If we’ve piqued your curiosity then this course is what you need. Learn about topics in Computer Vision such as Object Tracking, Augmented Reality, Face Detection, Optical Flow, Human Pose Estimation and many more.

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Unlike many Computer Vision courses available online, thishands-on courseapproaches Computer Visionmore practically, experientially and intuitively.All you need is a working knowledge of the Python programming language. And, if you are not confident about your Python skills, we will direct you to some of the best-curated resources on Python, so that you come up to speed with Python in the shortest possible time.

In short,beginners, coding enthusiasts, start-up owners, Tony Stark fans – everyone is welcometo this introductory course.

This course includes advanced topics like:

– Super Resolution Using OpenCV

– Deploying Applications On The Cloud

– Build Gesture Based Applications Using Facial Landmarks

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OpenCV isthe largest and the most popular Computer Vision library in the world.It is utilized by thousands of companies, products and devices, and is tested for scalability and performance every single day.

We, at OpenCV.org, are on a mission to educate a global workforce. We have been offering verycomprehensive online courses in Computer Visionto professionals, job-seekers and enthusiasts fromover 100 countries.

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The unique curriculum offered in this course is aimed at providing you with a solid foundation in the field of Computer Vision. We will take great pride in each and everyone who completes it successfully. Upon completion of the course, we will award you with a digital certificate from OpenCV.org. You can showcase it across your social profiles and give a kickstart to your career and continued studies in the field of Computer Vision.

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Have a look at some of the applications we plan to offer in this course.

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Getting Started With Images

– Image basics (reading, displaying and writing images)

– Working with video files (reading, displaying and writing videos)

– Color space conversion and different color spaces

– Basic image manipulation (resizing, cropping, annotating, creating a Region of Interest)

Basic Image Operations

– Mathematical operations on images (brightness and contrast)

– Image thresholding, bitwise operations and masking

– Image blending and the alpha channel

Image Enhancement Techniques

– Image filtering using convolution

– Image blurring, noise reduction and sharpness

– Artistic rendering

Image Analysis

– Edge detection

– Hough transforms

– Contour and shape detection

– Working with different types of image data such as satellite imagery

Augmented Reality

– ArUco markers and augmented reality

– Human-Computer Interaction (HCI) using gestures

Computational Photography

– Image Restoration

Image Retrieval and Object Detection

– Finding good features in images like SIFT, ORB

– Image hashing

– Geometric transformations like affine transformation and hom*ography

Video Processing

– Object tracking

– Optical flow and motion estimation

OpenCV DNN Module

– OpenCV DNN inference module

– Face detection using Deep Learning

– Object detection using Deep Learning

– Human pose estimation using Deep Learning

Text In Images (OCR)

– Text spotting and detection using Deep Learning

– Text recognition and Optical Character Recognition (OCR) using Deep Learning

Using OpenCV High-Level GUI For Creating Applications

– Using mouse and keyboard with OpenCV

Creating Web Applications Using Streamlit

– Streamlit framework for building web-based applications

Ethical And Socially Responsible Ways Of Using OpenCV

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All courses by OpenCV are only official and certified courses by OpenCV.org available online.

The courses are created in collaboration with Big Vision LLC, a California-based Computer Vision and Machine Learning consulting company. Big Vision LLC owns the popular Computer Vision blogLearnOpenCV.com, and is the exclusive and official course provider of OpenCV.org. Have a look at the industry experts that form our core course team.

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  • One of the top 30 AI influencers to follow on Twitter as per IBM Watson blog (2017)
  • Alumnus of Indian Institute of Technology (IIT), Kharagpur and Ph.D. from the University of California (San Diego)
  • Author of Computer Vision blog LearnOpenCV.com
  • Work featured in publications such as BBC, Time, Huffington Post, Wall Street Journal, Oprah Magazine, TechCrunch and TheRegister.co.uk

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  • BS from University of California, Berkeley and Ph.D. from Boston University in AI, Machine Learning and Neuro-Modelling
  • Served as a Visiting Professor at Computer Science Department, Stanford University for 7 years
  • Founder of the most powerful and popular Computer Vision library in the world, OpenCV.org
  • Organized the Computer Vision team for Stanley, the autonomous car that won the $2M DARPA Grand Challenge and currently displayed at the Smithsonian Air and Space Museum

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  • Ph.D. in Computer Science from the University of South Florida
  • Pioneered the development of automated systems for the Deaf community, helping them sign and communicate with others by translating American Sign Language to English text
  • Published multiple research papers in top scientific conferences including IEEE Conference on Computer Vision and Pattern Recognition, and high-impact scientific journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence

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  • AI & Computer Vision Researcher and an Alumnus of Indian Institute of Science (IISc), Bangalore
  • Leading planning and development of our Computer Vision and AI courses, in partnership with OpenCV
  • Over a decade of rich experience as Professor, AI Engineer and Data Scientist
  • Worked on various Deep Learning and Computer Vision projects with Samsung and Snapdeal
  • Interested in doing research in the field of Machine Perception, Scene Understanding, Deep Learning and Robotics

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  • Masters degree in Aeronautics and Astronautics from Massachusetts Institute of Technology (MIT), including graduate course work in Machine Learning and Image Processing at Stanford University
  • Extensive experience in the space science and defense industries, supporting several major development programs and research efforts for over two decades
  • Background in modelling and simulations, satellite systems, orbital analysis and machine learning
OpenCV For Beginners (2024)

FAQs

Is OpenCV easy to learn? ›

Like most high level libaries, OpenCV is not that hard to learn you just need to refer to the OpenCV documentation while coding with OpenCV. If you know basic programming in Python, Java or C++ then you can use OpenCV right away.

How many days it will take to learn OpenCV? ›

Computer Vision I : 3 months. Computer Vision II : 3 months. Deep Learning with PyTorch : 4 months. Note that you can finish the courses earlier if you devote more time.

Is Python or C++ better for OpenCV? ›

- C++: C++ generally offers better performance than Python when it comes to computational-intensive tasks. This makes it a preferred choice for real-time computer vision applications or scenarios where speed is crucial.

Should I learn TensorFlow or OpenCV? ›

The major difference between OpenCV and TensorFlow lies in their primary focus as well as functionality. OpenCV specializes in traditional computer vision which includes tasks like the production of images and video processing. On the contrary, TensorFlow is better known for its deep learning applications.

Do people still use OpenCV? ›

Today, OpenCV is still highly popular, with over 29'000 downloads every week. OpenCV is written in C and C++. It runs under the most popular operating systems, such as GNU/Linux, OS X, Windows, Android, iOS, etc. It is available for free under the Apache 2 license.

Which is better PyTorch or OpenCV? ›

In the Data Science And Machine Learning market, PyTorch has a 21.76% market share in comparison to OpenCV's 21.44%. Since it has a better market share coverage, PyTorch holds the 2nd spot in 6sense's Market Share Ranking Index for the Data Science And Machine Learning category, while OpenCV holds the 3rd spot.

Is OpenCV AI or machine learning? ›

OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library.

What is the salary of OpenCV developer? ›

Employees who knows Opencv earn an average of ₹25.3lakhs, mostly ranging from ₹15.5lakhs to ₹109.0lakhs based on 66 profiles.

Does OpenAI use PyTorch or TensorFlow? ›

OpenAI uses PyTorch, which was developed at FAIR. PyTorch 2.0 uses the Triton back-end compiler which was developed at OpenAI. OpenAI use transformers and RLHF which originated at Google & DeepMind.

Is ChatGPT based on TensorFlow? ›

ChatGPT is another text-based application that has taken the industry by storm. Although ChatGPT uses PyTorch, developers can use TensorFlow to build, optimize, and manage its models efficiently.

Should I start with PyTorch or TensorFlow? ›

If you're just starting to explore deep learning, you should learn PyTorch first due to its popularity in the research community. However, if you're familiar with machine learning and deep learning and focused on getting a job in the industry as soon as possible, learn TensorFlow first.

How hard is OpenCV? ›

opencv is easy to use and install. The goal of this course is to provide you with a working knowledge of OpenCV with Python. We'll start with the basics, starting from installing OpenCV with Python on Windows, Mac, and Ubuntu. Then we will see how to create your first OpenCV python script.

Is it worth learning OpenCV? ›

For those pursuing professional advancement, skill acquisition, or even a new career path, these OpenCV courses can be a valuable resource. Take the next step in your professional journey and enroll in a OpenCV course today!

Is OpenCV a deep learning? ›

The Dominance of OpenCV

The field of computer vision has evolved significantly with the advent of deep learning, shifting from traditional, rule-based methods to more advanced and adaptable systems. Earlier techniques, such as thresholding and edge detection, had limitations in complex scenarios.

Does OpenCV have deep learning? ›

Deep Learning is the most popular and the fastest growing area in Computer Vision nowadays. Since OpenCV 3.1 there is DNN module in the library that implements forward pass (inferencing) with deep networks, pre-trained using some popular deep learning frameworks, such as Caffe.

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