A naukri.com initiative
Medium
1M
399
Image Credit: Medium
Face Detection with Python Using OpenCV
- OpenCV is a powerful library for face detection used by organizations like Google, Microsoft, IBM, and Intel.
- Face detection uses visual input to identify a person's face in images or videos, which requires training models with sufficient diversity in the dataset.
- OpenCV has pre-trained models for face detection using a machine learning technique called Haar Cascade to identify objects in visual data.
- Haar Cascade method involves using a cascade of classifiers to detect different features in an image and is combined into one strong classifier.
- OpenCV provides pre-trained models to detect different objects within an image like a person's eyes, upper body, and a vehicle's license plate.
- A bounding box is created around the detected faces to display them in OpenCV.
- To perform face detection on a live video stream, the camera is accessed to read a live stream of video data.
- The same parameters such as scaleFactor, minNeighbors, and minSize can be used to detect faces in a live video stream in OpenCV.
- OpenCV provides an accessible entry point for developers to create efficient and scalable solutions for computer vision applications.
- By mastering the techniques covered in this tutorial, developers will be well-equipped to explore more advanced applications of computer vision in their projects.
Read Full Article
24 Likes
For uninterrupted reading, download the app