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# 人脸识别 | ||
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人脸识别,需要使用的库是face_recognition做人脸对比,OpenCV读取摄像头数据,OpenCV安装请看:[《环境搭建》](https://github.com/vipstone/faceai/blob/master/doc/huanjingdajian.md)face_recognition安装使用命令: | ||
>pip3 install face_recognition | ||
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#coding=utf-8 | ||
import cv2 | ||
import face_recognition | ||
import os | ||
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path = "img/face_recognition" # 模型数据图片目录 | ||
cap = cv2.VideoCapture(0) | ||
total_image_name = [] | ||
total_face_encoding = [] | ||
for fn in os.listdir(path): #fn 表示的是文件名q | ||
print(path + "/" + fn) | ||
total_face_encoding.append( | ||
face_recognition.face_encodings( | ||
face_recognition.load_image_file(path + "/" + fn))[0]) | ||
fn = fn[:(len(fn) - 4)] #截取图片名(这里应该把images文件中的图片名命名为为人物名) | ||
total_image_name.append(fn) #图片名字列表 | ||
while (1): | ||
ret, frame = cap.read() | ||
# 发现在视频帧所有的脸和face_enqcodings | ||
face_locations = face_recognition.face_locations(frame) | ||
face_encodings = face_recognition.face_encodings(frame, face_locations) | ||
# 在这个视频帧中循环遍历每个人脸 | ||
for (top, right, bottom, left), face_encoding in zip( | ||
face_locations, face_encodings): | ||
# 看看面部是否与已知人脸相匹配。 | ||
for i, v in enumerate(total_face_encoding): | ||
match = face_recognition.compare_faces( | ||
[v], face_encoding, tolerance=0.5) | ||
name = "未知" | ||
if match[0]: | ||
name = total_image_name[i] | ||
break | ||
# 画出一个框,框住脸 | ||
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2) | ||
# 画出一个带名字的标签,放在框下 | ||
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), | ||
cv2.FILLED) | ||
font = cv2.FONT_HERSHEY_DUPLEX | ||
cv2.putText(frame, | ||
name.encode("gbk").decode("gbk"), (left + 6, bottom - 6), | ||
font, 1.0, (255, 255, 255), 1) | ||
# 显示结果图像 | ||
cv2.imshow('Video', frame) | ||
if cv2.waitKey(1) & 0xFF == ord('q'): | ||
break | ||
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cap.release() | ||
cv2.destroyAllWindows() |
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import cv2 | ||
import dlib | ||
import face_recognition | ||
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print(cv2.__version__) # 输出:3.4.1 | ||
print(dlib.__version__) # 输出:19.8.1 | ||
print(face_recognition.__version__) #输出:1.2.2 |
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