OpenCV implements facial landmark detection

Facial landmark detection is an important task in computer vision, which is achieved by identifying the locations of key points on the human face. OpenCV is a popular computer vision library that provides many functions for face detection and landmark detection. In this article, I will introduce in detail how to use OpenCV for face landmark detection, and attach the corresponding source code.

First, make sure you have the OpenCV library installed. OpenCV can be installed in Python using the following command:

pip install opencv-python

Next, we will use OpenCV’s pre-trained model to detect faces and mark their keypoints. The models we will use are face detectors and keypoint detectors based on the dlib library. Here is the complete code example:

import cv2
import dlib

# 加载人脸检测器和关键点检测器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat'