一、對(duì)照片進(jìn)行人臉識(shí)別
1.代碼
import cv2
img = cv2.imread('image',1)
face_engine = cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')
faces = face_engine.detectMultiScale(img,scaleFactor=1.3,minNeighbors=5)
for (x,y,w,h) in faces:
? ? img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.imwrite('new.jpg',img)
2.效果圖
二芥吟、利用攝像頭進(jìn)行實(shí)時(shí)人臉識(shí)別
1.代碼
import cv2
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades+'haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades +'haarcascade_eye.xml')
cap = cv2.VideoCapture(0)
while (True):
# 獲取攝像頭拍攝到的畫面
? ? ret, frame = cap.read()
faces = face_cascade.detectMultiScale(frame, 1.3, 5)
img = frame
for (x, y, w, h)in faces:
# 畫出人臉框，藍(lán)色颇蜡，畫筆寬度微
? ? ? ? img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
# 框選出人臉區(qū)域，在人臉區(qū)域而不是全圖中進(jìn)行人眼檢測，節(jié)省計(jì)算資源
? ? ? ? face_area = img[y:y + h, x:x + w]
eyes = eye_cascade.detectMultiScale(face_area)
# 用人眼級(jí)聯(lián)分類器引擎在人臉區(qū)域進(jìn)行人眼識(shí)別九火，返回的eyes為眼睛坐標(biāo)列表
? ? ? ? for (ex, ey, ew, eh)in eyes:
# 畫出人眼框冈闭，綠色俱尼，畫筆寬度為1
? ? ? ? ? ? cv2.rectangle(face_area, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 1)
# 實(shí)時(shí)展示效果畫面
? ? cv2.imshow('frame2', img)
# 每5毫秒監(jiān)聽一次鍵盤動(dòng)作
? ? if cv2.waitKey(5) &0xFF ==ord('q'):
break
# 最后，關(guān)閉所有窗口
cap.release()
cv2.destroyAllWindows()
2.效果圖
