The challenge is to take the previous method of haar cascading and apply it to detect and draw circles around eyes found in an image. Note that a new training set on eyes is included to perform this task.
- [Instructor] Let's complete this chapter with a challenge.…Specifically, let's try and find all…the eyes in an image and place circles around them.…To do this, leverage a haarcascade method similar…to how we detected faces in the previous module.…This time, use the provided haarcascade_eye.xml file,…which has specifically been pre-trained…for detecting eyes in an image.…Additionally, try to reduce the number…of false positives and false negatives as much as possible.…In this scenario, a false positive…is drawing a circle where there's not…an eye, and a false negative is not drawing…a circle where there is an eye.…
This exercise should take between…10 and 15 minutes to complete.…
AuthorPatrick W. Crawford
- Installing and configuring OpenCV
- Data types and structures
- Image types
- Manipulating pixels
- Scaling and rotating images
- Using video inputs
- Creating custom interfaces
- Object detection
- Face and feature detection
- Template matching
Skill Level Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
Python: Programming Efficientlywith Michele Vallisneri2h 15m Intermediate
1. Install and Configure OpenCV
2. Basic Image Operations
3. Object Detection
4. Face and Feature Detection
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