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The fastest way to learn OpenCV, Object Detection, and Deep Learning.

– Discover the “hidden” face detector in OpenCV.
– Develop a super-simple object tracker.
– Use neural networks for object detection.
Learn how to do all this and more for free in 17 simple to follow, obligation free email lessons starting today.
“PyImageSearch’s course converted me from a Python beginner to a published computer vision practitioner.” – Dr. Paul Lee

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Need help learning Computer Vision, Deep Learning, and OpenCV?Let me guide you.

Whether you’re brand new to the world of computer vision and deep learning or you’re already a seasoned practitioner, you’ll find tutorials for both beginners and experts alike. Here are some of the most popular categories and tutorials on the PyImageSearch blog.

How Do I Get Started?

You’re interested in Computer Vision, Deep Learning, and OpenCV…but you don’t know how to get started. Follow these tutorials to get OpenCV installed on your system, learn the fundamentals of Computer Vision, and graduate to more advanced topics, including Deep Learning, Face Recognition, Object Detection, and more!

Featured articles

pip install OpenCV

September 19, 2018

In this tutorial, you will learn how to pip install OpenCV on Ubuntu, macOS, and the Raspberry Pi. In previous OpenCV install tutorials I have recommended compiling from source; however, in the past year it has become possible to install…

OpenCV Tutorial: A Guide to Learn OpenCV

July 19, 2018

Whether you’re interested in learning how to apply facial recognition to video streams, building a complete deep learning pipeline for image classification, or simply want to tinker with your Raspberry Pi and add image recognition to a hobby project, you’ll…

Bubble sheet multiple choice scanner and test grader using OMR, Python, and OpenCV

October 3, 2016

Over the past few months I’ve gotten quite the number of requests landing in my inbox to build a bubble sheet/Scantron-like test reader using computer vision and image processing techniques. And while I’ve been having a lot of fun doing…

See more How Do I Get Started Articles

Deep Learning

Deep Learning algorithms are revolutionizing the Computer Vision field, capable of obtaining unprecedented accuracy in Computer Vision tasks, including Image Classification, Object Detection, Segmentation, and more. Follow these tutorials and you’ll have enough knowledge to start applying Deep Learning to your own projects.

Featured articles

Face Recognition with Siamese Networks, Keras, and TensorFlow

January 9, 2023

Table of Contents Face Recognition with Siamese Networks, Keras, and TensorFlow Face Recognition Face Recognition: Identification and Verification Identification via Verification Metric Learning: Contrastive Losses Contrastive Losses Summary Credits Citation Information Face Recognition with Siamese Networks, Keras, and TensorFlow In…

Automatic Differentiation Part 2: Implementation Using Micrograd

December 26, 2022

Table of Contents Automatic Differentiation Part 2: Implementation Using Micrograd Introduction What Is a Neural Network? Having Problems Configuring Your Development Environment? About micrograd Imports and Setup The Value Class Addition Compute Gradient Multiplication Compute Gradient Power Compute Gradient Negation…

Automatic Differentiation Part 1: Understanding the Math

December 5, 2022

Table of Contents Automatic Differentiation Part 1: Understanding the Math Introduction Jacobian Chain Rule Mix the Jacobian and Chain Rule Forward and Reverse Accumulations Forward Accumulation Reverse Accumulation Summary References Citation Information Automatic Differentiation Part 1: Understanding the Math In…

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Face Applications

Computer Vision algorithms can be used to perform face recognition, enhance security, aid law enforcement, detect tired, drowsy drivers behind the wheel, or build a virtual makeover system. Follow these tutorials learn the basics of facial applications using Computer Vision.

Featured articles

OpenCV Eigenfaces for Face Recognition

May 10, 2021

In this tutorial, you will learn how to implement face recognition using the Eigenfaces algorithm, OpenCV, and scikit-learn. Our previous tutorial introduced the concept of face recognition — detecting the presence of a face in an image/video and then subsequently…

Face Recognition with Local Binary Patterns (LBPs) and OpenCV

May 3, 2021

In this tutorial, you will learn how to perform face recognition using Local Binary Patterns (LBPs), OpenCV, and the cv2.face.LBPHFaceRecognizer_create function. In our previous tutorial, we discussed the fundamentals of face recognition, including: The difference between face detection and face…

What is face recognition?

May 1, 2021

In this tutorial, you will learn about face recognition, including: How face recognition works How face recognition is different from face detection A history of face recognition algorithms State-of-the-art algorithms used for face recognition today Next week we will start…

See more face applications articles

All Topics

  • Image Processing
  • Machine Learning
  • Deep Learning
  • Raspberry Pi
  • OpenCV Tutorials
  • Object Detection
  • Interviews
  • dlib
  • Optical Character Recognition (OCR)
  • Keras and TensorFlow
  • Embedded/IoT and Computer Vision
  • Face Applications
  • Object Tracking
  • Medical Computer Vision

Student Success Stories

What People Are Saying

Adrian has helped me with my Computer Vision journey more than anyone ever has. If I need to learn anything his courses or the blog are the first thing I refer to. And if still in doubt just comment on the blog and he is very likely to respond to each and every question. Thanks Adrian.

Harsh Balot,
Android Developer and Computer Vision Practitioner

Adrian’s deep learning book book is a great, in-depth dive into practical deep learning for computer vision. I found it to be an approachable and enjoyable read: explanations are clear and highly detailed. You’ll find many practical tips and recommendations that are rarely included in other books or in university courses. I highly recommend it, both to practitioners and beginners.

Francois Chollet,
Creator of Keras and AI researcher at Google

I consider PyImageSearch the best collection of tutorials for beginners in computer vision. Adrian’s explanations are easy to get started with and at the same time cover enough depth to quickly feel at home in the official documentation. This combination is a rare treasure in today’s overload of carelessly written tutorials. I’ve recommended PyImageSearch already numerous times.

Sandro Kalbermatter,
Student at ETH Zürich

Adrian’s Practical Python and OpenCV is the perfect first step if you are interested in computer vision but don’t know where to start…You’ll be glued to your workstation as you try out just one more example.

Jason Brownlee,
Creator of MachineLearningMastery.com

I highly recommend grabbing a copy of Deep Learning for Computer Vision with Python. It goes into a lot of detail and has tons of detailed examples. It’s the only book I’ve seen so far that covers both how things work and how to actually use them in the real world to solve difficult problems. Check it out!

Adam Geitgey,
Author of Machine Learning is Fun! blog series

Practical Python and OpenCV is a non-intimidating introduction to basic image processing tasks in Python. While reading the book, it feels as if Adrian is right next to you, helping you understand the many code examples without getting lost in mathematical details.

Dr. Tomasz Malisiewicz,
Principal Engineer and Deep Learning Practitioner at MagicLeap

Phenomenal. The concepts on deep learning are so well explained that I will be recommending this book [Deep Learning for Computer Vision with Python] to anybody not just involved in computer vision but AI in general.

Dr. Zig Zdziarski,
PhD in CV and ML, author at Zbigatron

PyImageSearch is the go to place for computer vision. The blog and books show excellent use cases from simple to more complex, real world scenarios. The step guides are all working out of the box. I use them as a perfect starting point and enhance them in my own solutions.

Zoltan Szalontay,
Chief Technology Officer at Makerspace.hu

The PyImageSearch Gurus course is one of the best education programs I have ever attended. No matter whether you are a beginner or advanced computer vision developer, you’ll definitely learn something new and valuable inside the course. I highly recommend PyImageSearch Gurus to anyone interested in learning computer vision.

Peter IP,
Data Scientist and Big Data Architect

My Books & Courses

My books and courses work. Students of mine have gone on to land high profile jobs at R&D companies, land $100,000+ in grant funding, publish novel papers in reputable journals, win Kaggle competitions, and completely change their career from developer to Computer Vision/Deep Learning practitioner.
Pick up a copy of my books/courses today and join them in CV/DL mastery.

PyImageSearch University Image

PyImageSearch University

Inside PyImageSearch University, you get access to centralised code repos of high-quality source code for all 500+ tutorials on the PyImageSearch blog, Jupyter Notebooks in pre-configured Google Colab instances, video tutorials, and new courses released every month!

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Deep Learning for Computer Vision with Python

An in-depth dive into the world of computer vision and deep learning. Start by learning the basics of DL, move on to training models on your own custom datasets, and advance to implementing state-of-the-art models.

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FREE CV, DL, and OpenCV Crash Course

You can learn the fundamentals of Computer Vision, Deep Learning, and OpenCV in this totally practical, super hands-on, and absolutely FREE 17-day email crash course.

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Practical Python and OpenCV

A gentle introduction to the world of Computer Vision and Image Processing through the OpenCV library and Python programming language.

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PyImageSearch Gurus Course

Similar to a college survey course in computer vision but far more hands on and practical. Includes 168 lessons covering 13 modules and 2,161 pages of content. Most comprehensive comptuer vision course available today.

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Raspberry Pi for Computer Vision

Apply Computer Vision, Deep Learning, and OpenCV to resource constrained/embedded devices, including the Raspberry Pi, Movidius NCS, Google Coral, and NVIDIA Jetson Nano.

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About Me

You’re stuck learning Computer Vision and Deep Learning. So was I.

Hi there, I’m Adrian Rosebrock, PhD.

I started the PyImageSearch community to help fellowdevelopers, students, and researchers:

  • Get started with Computer Vision and OpenCV
    (without a decade of mathematics and theory).
  • Learn how to successfully apply Computer Vision, Deep Learning, and OpenCV to their own projects and research.
  • Avoid the same mistakes and pitfalls I made when studying Computer Vision and Deep Learning.
Read More About Adrian

Recent Blog Posts and Tutorials

Every Monday for the past five years I published a brand new tutorial on Computer Vision, Deep Learning, and OpenCV. Here are my most recent tutorials and guides.

Applications
CV and DL Applications
CV for Education
DL for Education
Tutorial

Computer Vision and Deep Learning for Education

January 30, 2023

Table of Contents Computer Vision and Deep Learning for Education Benefits Smart Content Task Automation Closing Skill Gap Applications Student Learning and Welfare Personalized Learning Social, Emotional Growth, and Well-Being Acquiring 21st-Century Skills Educators Parent Engagement School and Institution Management…

Machine Learning
Tutorial
XGBoost

Scaling Kaggle Competitions Using XGBoost: Part 4

January 23, 2023

Table of Contents Scaling Kaggle Competitions Using XGBoost: Part 4 What Is XGBoost? Our Dummy Dataset Breaking Down the Math Configuring Your Development Environment Having Problems Configuring Your Development Environment? Applying XGBoost on a Problem Statement Applying XGBoost to Our…

Decision Trees
Ensemble Learning
Kaggle
XGBoost

Scaling Kaggle Competitions Using XGBoost: Part 3

January 16, 2023

Table of Contents Scaling Kaggle Competitions Using XGBoost: Part 3 Gradient Boost at a Glance AdaBoost vs. Gradient Boosting Gradient Boosting Dissected Configuring Your Development Environment Having Problems Configuring Your Development Environment? Setting Up Our Project Comparing XGboost and Gradient…

Computer Vision
Deep Learning
Face Identification
Face Recognition
Keras
Siamese Networks
TensorFlow

Face Recognition with Siamese Networks, Keras, and TensorFlow

January 9, 2023

Table of Contents Face Recognition with Siamese Networks, Keras, and TensorFlow Face Recognition Face Recognition: Identification and Verification Identification via Verification Metric Learning: Contrastive Losses Contrastive Losses Summary Credits Citation Information Face Recognition with Siamese Networks, Keras, and TensorFlow In…

Applications
CV and DL Applications
CV for Healthcare
DL for Healthcare

Computer Vision and Deep Learning for Healthcare

January 2, 2023

Table of Contents Computer Vision and Deep Learning for Healthcare Benefits Unlocking Data for Health Research Healthcare Efficiency Reaching Underserved Communities Applications Medical Research in Genetics and Genomics Clinical Care Medical Imaging and Radiology Pathology Dermatology Neurology Mental Health Diabetes…

Agile and Scrum

The 2023 Guide To Grooming in Agile

December 29, 2022

Grooming is taking your product’s to-do list of work and transforming it into a product backlog. If you’d like to learn how to groom or refine your backlog so you’re ready for your Sprint, just keep reading. Let’s start with…

See All Tutorials

You can learn Computer Vision, Deep Learning, and OpenCV.

Get your FREE 17 page Computer Vision, OpenCV, and Deep Learning Resource Guide PDF. Inside you’ll find our hand-picked tutorials, books, courses, and libraries to help you master CV and DL.


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Topics

  • Deep Learning
  • Dlib Library
  • Embedded/IoT and Computer Vision
  • Face Applications
  • Image Processing
  • Interviews
  • Keras
  • Machine Learning and Computer Vision
  • Medical Computer Vision
  • Optical Character Recognition (OCR)
  • Object Detection
  • Object Tracking
  • OpenCV Tutorials
  • Raspberry Pi

Books & Courses

  • PyImageSearch University
  • FREE CV, DL, and OpenCV Crash Course
  • Practical Python and OpenCV
  • Deep Learning for Computer Vision with Python
  • PyImageSearch Gurus Course
  • Raspberry Pi for Computer Vision

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Inside the course you'll:

  • Learn by doing.
  • Get your hands dirty with code and implementations.
  • And most importantly, you won’t get bogged down with complex theory and equations.

I did deeplearning.ai, Udacity AI Nanodegree, and bunch of other courses…but for the last month I have always started the day by first finishing one day of your course. The projects are not too overwhelming but each project gets a key thing done, so they are super useful. I keep on finding myself getting back and looking at the source code from your projects, much more than I do from other courses.

Igor MarjanovicResearcher and business owner