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 Marjanovic, Researcher and business owner
Igor Marjanovic
Researcher and business owner
The course was PERFECT. The amount of knowledge (on point and hands on) I could attain in these 17 days was way more than what I could gather in the last 3-4 months from my academics. I am really thankful to this course. Its simple yet effectively designed. I have already started suggesting this to my colleagues in my research lab.
Pratik Kulkarni, Computer Vision Intern at WelchLabs
Pratik Kulkarni
Computer Vision Intern at WelchLabs

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Continuing our trend of building practical computer vision applications, you'll learn how to build an OpenCV program capable of scanning and grading exams (i.e., an OMR system).

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Use OpenCV and computer vision to build an automatic test grader and OMR system.
Thank you for the 17 day crash course, man, they are really easy to understand and implement on my laptop. I'm on day 14 and have been consistent. It's amazing.
My thesis unexpectedly turned towards computer vision with machine learning, forcing me to very quickly dive into this topic which is brand-new to me (I specialized in networking and software engineering). The learning curve has been extreme in the past weeks and the PyImageSearch blog has made my life A LOT easier. I consider this website today's best collection of tutorials for beginners in computer vision. Your explanations are easy to get started with and at the same time cover enough depth to quickly feel at home 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
Sandro Kalbermatter
Student at ETH Zürich
Track objects in real-time using OpenCV


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Detect blinks in real-time video with OpenCV and dlib.
Detect tired drivers using OpenCV, dlib, and computer vision.


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Excessive blinking and drooping eyelids may be a sign of fatigue. While facial landmarks may show use how to localize regions of the face, including the eyes, we need a separate algorithm, called the Eye Aspect Ratio (EAR) to detect when the eyes are closed. Inside this lesson you'll 星耀娱乐网址网址官网 and even 星耀娱乐网址官方地址 To learn how to build such a system, you'll need to join the crash course.

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Just wanted to thank you [Adrian] for the great work you are doing with PyImageSearch blog. The site has often been our main go-to place for solving Computer Vision problems for image and video analysis. I particularly appreciate the code samples you provide which are easy to understand. This site has helped us apply Computer Vision and Deep Learning techniques to analyze videos from industrial domain (like railways) and extract valuable outcomes. Keep up the great job sharing your knowledge!
Dattaraj Rao, Chief Architect at GE
Dattaraj Rao
Chief Architect at GE
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, CIO/CO at újHÁZ Centrum
Zoltan Szalontay
CIO/CO at újHÁZ Centrum


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Perform deep learning with OpenCV and Python.
Create your own custom dataset for deep learning.


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Train your very first Convolutional Neural Network using Keras, Deep Learning, and OpenCV.
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In my honest opinion Adrian has helped me with 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
Harsh Balot
Android Developer and Computer Vision Practitioner
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Shubham Bengani, Student at Bangalore Institute of Technology
Shubham Bengani
Student at Bangalore Institute of Technology

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The PyimageSearch tutorials have been the most to the point content I have seen. I have always been able to get straightforward solutions for most of my Computer Vision and Deep Learning problems that I face in my day-to-day work life. Courses like this is what helps people and industries around the world to make quick and efficient solutions to their problems in real time.
Swastik Mahapatra, DeepLearning Intern - Computer Vision at Analog Devices
Swastik Mahapatra
DeepLearning Intern - Computer Vision at Analog Devices
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Amit Roy, Senior Principal Expert and Distinguished Inventor
Amit Roy
Senior Principal Expert and Distinguished Inventor

Here are some common questions that I get asked about the course...星耀娱乐网址平台地址

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Adrian Rosebrock

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