LBPH人臉識別
import cv2 import numpy as np images=[] #劉詩詩 images.append(cv2.imread("./lss/1.png",0)) images.append(cv2.imread("./lss/2.png",0)) images.append(cv2.imread("./lss/3.png",0)) images.append(cv2.imread("./lss/4.png",0)) images.append(cv2.imread("./lss/5.png",0)) #劉亦菲 images.append(cv2.imread("./lyf/1.jpg",0)) images.append(cv2.imread("./lyf/2.jpg",0)) images.append(cv2.imread("./lyf/3.jpg",0)) images.append(cv2.imread("./lyf/4.jpg",0)) images.append(cv2.imread("./lyf/5.jpg",0)) #標簽 labels=[0,0,0,0,0,1,1,1,1,1] #獲取識別器 recognizer = cv2.face.LBPHFaceRecognizer_create() #訓練 recognizer.train(images, np.array(labels)) #待識別照片 predict_image=cv2.imread("001.jpg",0) #識別 label,confidence= recognizer.predict(predict_image) print("label=",label) print("confidence=",confidence)
confidence為識別結果與模型之間的距離，0表示百分百準確，正常情況下小于50都可以認為可信，還是要根據專案的實際情況去跑大量測驗來確定閾值，
EigenFaces人臉識別
import cv2 import numpy as np images=[] #劉詩詩 images.append(cv2.imread("./lss/1.jpg",0)) images.append(cv2.imread("./lss/2.jpg",0)) images.append(cv2.imread("./lss/3.jpg",0)) images.append(cv2.imread("./lss/4.jpg",0)) images.append(cv2.imread("./lss/5.jpg",0)) #劉亦菲 images.append(cv2.imread("./lyf/1.jpg",0)) images.append(cv2.imread("./lyf/2.jpg",0)) images.append(cv2.imread("./lyf/3.jpg",0)) images.append(cv2.imread("./lyf/4.jpg",0)) images.append(cv2.imread("./lyf/5.jpg",0)) #標簽 labels=[0,0,0,0,0,1,1,1,1,1] #獲取識別器 recognizer = cv2.face.EigenFaceRecognizer_create() #訓練 recognizer.train(images, np.array(labels)) #待識別照片 predict_image=cv2.imread("10.jpg",0) #識別 label,confidence= recognizer.predict(predict_image) print("label=",label) print("confidence=",confidence)
confidence為識別結果與模型之間的距離，0表示百分百準確，正常情況下小于5000都可以認為可信，
Fisherfaces人臉識別
import cv2 import numpy as np images=[] #劉詩詩 images.append(cv2.imread("./lss/1.jpg",0)) images.append(cv2.imread("./lss/2.jpg",0)) images.append(cv2.imread("./lss/3.jpg",0)) images.append(cv2.imread("./lss/4.jpg",0)) images.append(cv2.imread("./lss/5.jpg",0)) #劉亦菲 images.append(cv2.imread("./lyf/1.jpg",0)) images.append(cv2.imread("./lyf/2.jpg",0)) images.append(cv2.imread("./lyf/3.jpg",0)) images.append(cv2.imread("./lyf/4.jpg",0)) images.append(cv2.imread("./lyf/5.jpg",0)) #標簽 labels=[0,0,0,0,0,1,1,1,1,1] #獲取識別器 recognizer = cv2.face.FisherFaceRecognizer_create() #訓練 recognizer.train(images, np.array(labels)) #待識別照片 predict_image=cv2.imread("10.jpg",0) #識別 label,confidence= recognizer.predict(predict_image) print("label=",label) print("confidence=",confidence)
confidence為識別結果與模型之間的距離，0表示百分百準確，正常情況下小于5000都可以認為可信，
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