Python--基于OpenCV数据集的人脸定位和识别

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.xmlhaarcascade_frontalcatface_extended.xmlhaarcascade_frontalface_default.xml

人脸定位：

import cv2 as cv import numpy as np from matplotlib import pyplot as plt def 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 plt def 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: break face_detect_demo(frame) videowrite.write(frame) if ord('q') == cv.waitKey(10): break cv.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 plt def 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: break face_detect_demo(frame) videowrite.write(frame) if ord('q') == cv.waitKey(10): break cv.destroyAllWindows() cv.release()