pip install dlib==19.7.0 pip install face_recognition 3.简单使用 face_recognition基于dli封装很多常用人脸识别相关算法,这里举两个常用例子 1).人脸检测 import face_recognition import cv2 img_path = "gril.jpg" imgs = cv2.imread(img_path,cv2.IMREAD_COLOR) face_locations = face_recognition.face_lo...
pip install opencv-python 5 修改你的pip镜像源为清华镜像,然后使用pip install face_recognition,可以自动帮你安装各种依赖,包括dlib。只是在安装dlib的时候可能会出问题,因为dlib需要编译pip install -ihttps://pypi.tuna.tsinghua.edu.cn/simpleface_recognition 在Anaconda创建的虚拟环境中运行相应的pip 如: cd /...
cv2_img = cv2.imread(img_path)# 判断图片中是否存在人脸img_location = face_recognition.face_locations(cv2_img)ifnotimg_location:continue# 计算图片编码,多次编码可通过num_jitters设置重复计算次数,所用时间也会相应增加face_encode_list = face_recognition.face_encodings(cv2_img)# 取人脸列表中的第一张...
import face_recognition import cv2 frame = cv2.imread("test_img/obama.jpg") # 缩小图像以加快速度 small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25) # 找到人脸 face_locations = face_recognition.face_locations(small_frame, model="cnn") for top, right, bottom, left in face_l...
I am beginner at using OpenCv2, I am trying to detect faces with the following function: def faceDetection(test_img): gray_img=cv2.cvtColor(test_img,cv2.COLOR_BGR2GRAY)#convert color image to grayscale face_haar_cascade=cv2.CascadeClassifier(cv2.data.haarcascades +'haarcascade_frontalface_def...
face_recognition.api.face_locations(img, number_of_times_to_upsample=1, model=‘hog’) 用途:人脸检测,返回图像中人脸边界框的数组 img:输入图像,numpy数组 number_of_times_to_upsample:对图像进行上采样次数以找到更小的人脸,默认为1 model:检测模型,默认是hog机器学习模型,另外可设置cnn选择卷积神经网络模...
Default face recognition model is VGG-Face. Try to use Facenet or ArcFace model to have a faster results in your real time application. The default detector is opencv which is fast but coming with low precision. Mediapipe gives better results than opencv but still mtcnn is the best option...
测试 importface_recognitionimportcv2img_path="./test.jpg"img=cv2.imread(img_path)# 获取位置信息...
pip install face_recognition 3.简单使用 face_recognition基于dli封装很多常用人脸识别相关算法,这里举两个常用例子 1).人脸检测 import face_recognitionimport cv2 img_path = "gril.jpg"imgs = cv2.imread(img_path,cv2.IMREAD_COLOR) face_locations = face_recognition.face_locations(imgs) ...
Face recognition based attendance based system will be used in the near future in classrooms instead of the traditional system; it may replace even biometric attendance systems. The purpose of the present work is to devise a novel attendance system using cv2. Facebook also uses face recognition ...