face_distance 函数参数说明
接下来我们来看代码
代码实现
import cv2
import face_recognition
# 加载图像文件
img1 = face_recognition.load_image_file('lyf1.png')
img2 = face_recognition.load_image_file('lyf2.png')
# 将图像从 BGR 格式转换为 RGB 格式
img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2RGB)
img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2RGB)
# 第一个人的人脸位置信息
faceloc1 = face_recognition.face_locations(img1)[0]
faceloc2 = face_recognition.face_locations(img2)[0]
# 提取人脸编码
face_encoding1 = face_recognition.face_encodings(img1, [faceloc1])[0]
face_encoding2 = face_recognition.face_encodings(img2, [faceloc2])[0]
#框出人脸
cv2.rectangle(img1, (faceloc1[3], faceloc1[0]), (faceloc1[1], faceloc1[2]), (0, 255, 0), 3)
cv2.rectangle(img2, (faceloc2[3], faceloc2[0]), (faceloc2[1], faceloc2[2]), (0, 255, 0), 3)
#比对人脸特征
res = face_recognition.compare_faces([face_encoding1],face_encoding2)
facedis = face_recognition.face_distance([face_encoding1],face_encoding2)
print(res,round(facedis[0],2))
cv2.putText(img1,f'{res}{round(facedis[0],2)}',(50,50),cv2.FONT_HERSHEY_COMPLEX,1,(0,255,0),3)
#打印人脸位置信息
# print(faceloc1)
# print(faceloc2)
cv2.imshow('lyf1', img1)
cv2.imshow('lyf2', img2)
cv2.waitKey(0)
效果演示
这样就完成了
