Detect Eyes Using Haar Cascades and Hough Transformation you own this product

prerequisites
basics of Python • basics of OpenCV
skills learned
reading and writing images • using Haar Cascade Classifier for eye detection • using Hough Circle Transform for circle detection
Vishwesh Shrimali
1 week · 3-6 hours per week · INTERMEDIATE
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In this liveProject, you’ll upgrade facial recognition security to more complex iris recognition. You will read an image, draw bounding boxes around the detected eyes and detect the circular eye area region, then save the output image.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Vishwesh Shrimali
Vishwesh Ravi Shrimali is an AI and computer vision engineer with a mechanical engineering background. In his previous company, he was involved in developing the official OpenCV AI course series. He has also written multiple books on OpenCV and machine learning. He has recently joined Mercedes Benz R&D India as an engineer in the ADAS domain. He is also pursuing his master's in ML & AI from LJMU.

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These liveProjects are for aspiring OpenCV developers with some knowledge of Python. To begin these liveProjects, you will need to be familiar with:

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    • Displaying images using OpenCV

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