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s Unlocking Image Clarity: A Comprehensive Guide to Super-Resolution Techniques Introduction Configuring Your Development Environment Need Help Configuring Your Development Environment? What Is Super-Resolution? Usual Problems with Low-Resolution Imagery Traditional Computer Vision Algorithms for Super-Resolution Nearest-Neighbor Interpolation: Efficient… Integrating Document Embedding in Gemini Pro: An Approach to Retrieval-Augmented Generation April 22, 2024 Table of Contents Integrating Document Embedding in Gemini Pro: An Approach to Retrieval-Augmented Generation Introduction to Document Embedding with Gemini Pro The Essential Role of Embeddings Setting Up Gemini Pro for Document Embedding and Generation Implementing Document Embedding: Code Integration… Exploring GAN Code Generation with Gemini Pro and ChatGPT-3.5: A Comparative Study April 15, 2024 Table of Contents Exploring GAN Code Generation with Gemini Pro and ChatGPT-3.5: A Comparative Study Introduction to GAN Development with Gemini Pro Expectations from the Generated Code Understanding Generative Adversarial Networks Configuring Gemini Pro for PyTorch GAN Code Creation and… See more deep learning articles 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 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! Learn More 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. Learn More 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. Learn More Practical Python and OpenCV A gentle introduction to the world of Computer Vision and Image Processing through the OpenCV library and Python programming language. Learn More 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. Learn More 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. Learn More About Me You’re stuck learning Computer Vision and Deep Learning. So was I. Hi there, I’m Adrian Rosebrock, PhD. I...