Python--基于OpenCV数据集的人脸定位和识别

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就是调个库，没什么好说的。上代码：

事前准备：

• python安装两个库。

pip install opencv-python
pip install opencv-contrib-python

到cv2文件夹下取出三个文件，复制到工作区：

• haarcascade_frontalcatface.xml
• haarcascade_frontalcatface_extended.xml
• haarcascade_frontalface_default.xml

人脸定位：

import cv2 as cv
import numpy as np
from matplotlib import pyplot as pltdef face_detect_demo():gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)face_detector = cv.CascadeClassifier('D:/anaconda3/Lib/site-packages/cv2/data/haarcascade_frontalface_alt_tree.xml')faces = face_detector.detectMultiScale(gray, scaleFactor=1.008, minNeighbors=4, maxSize=(47, 47), minSize=(28 ,28))for x, y, w, h in faces:cv.rectangle(img, (x, y), (x+w, y+h), color=(0, 0, 255), thickness=2)cv.circle(img, center=(x+w//2, y+h//2), radius=w//2, color=(0, 255, 0), thickness=2)cv.imshow('result', img)img = cv.imread('test05.jpg')face_detect_demo()
cv.waitKey(4000)
cv.destroyAllWindows()

视频人脸定位：

import cv2 as cv
import numpy as np
from matplotlib import pyplot as pltdef face_detect_demo(img):gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)face_detector = cv.CascadeClassifier('../trainer/haarcascade_frontalface_default.xml')faces = face_detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4, minSize=(30 ,30))for x, y, w, h in faces:cv.rectangle(img, (x, y), (x+w, y+h), color=(0, 0, 255), thickness=2)cv.circle(img, center=(x+w//2, y+h//2), radius=w//2, color=(0, 255, 0), thickness=2)cv.imshow('result', img)cap = cv.VideoCapture('../src/test06_Trim2.mp4')#save files
fps = 5
size = (int (cap.get(cv.CAP_PROP_FRAME_WIDTH)), int (cap.get(cv.CAP_PROP_FRAME_HEIGHT)))
videowrite = cv.VideoWriter('../result/result_1.mp4', cv.VideoWriter_fourcc('I', '4', '2', '0'), fps, size)while True:flag, frame = cap.read()if not flag:breakface_detect_demo(frame)videowrite.write(frame)if ord('q') == cv.waitKey(10):breakcv.destroyAllWindows()
cv.release()

效果：

 

打开摄像头，摄像头定位：

import cv2 as cv
import numpy as np
from matplotlib import pyplot as pltdef face_detect_demo(img):gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)face_detector = cv.CascadeClassifier('./data/haarcascade_frontalface_default.xml')faces = face_detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=4, minSize=(30 ,30))for x, y, w, h in faces:cv.rectangle(img, (x, y), (x+w, y+h), color=(0, 0, 255), thickness=2)cv.circle(img, center=(x+w//2, y+h//2), radius=w//2, color=(0, 255, 0), thickness=2)cv.imshow('result', img)#cap = cv.VideoCapture('../src/test06_Trim2.mp4')
cap = cv.VideoCapture(0)
#save files
fps = 5
size = (int (cap.get(cv.CAP_PROP_FRAME_WIDTH)), int (cap.get(cv.CAP_PROP_FRAME_HEIGHT)))
videowrite = cv.VideoWriter('../result/result_1.mp4', cv.VideoWriter_fourcc('I', '4', '2', '0'), fps, size)while True:flag, frame = cap.read()if not flag:breakface_detect_demo(frame)videowrite.write(frame)if ord('q') == cv.waitKey(10):breakcv.destroyAllWindows()
cv.release()

 

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