%matplotlib inlineimportmatplotlib.pyplotaspltfromPILimportImageimportface_recognition# 通过PIL加载图片image=face_recognition.load_image_file("test_img/obama.jpg")# 基于cnn识别人脸,是否使用gpu看装机环境face_locations=face_re
import face_recognition import cv2 import numpy as np # This is a demo of running face recognition on live video from your webcam. It's a little more complicated than the # other example, but it includes some basic performance tweaks to make things run a lot faster: # 1. Process each ...
# import librariesimport cv2import face_recognition# Get a reference to webcam video_capture = cv2.VideoCapture("/dev/video1")# Initialize variablesface_locations = []while True: # Grab a single frame of video ret, frame...
High Quality Face Recognition with Deep Metric Learning(Davis,http://blog.dlib.net/2017/02/high-quality-face-recognition-with-deep.html) Modern Face Recognition with Deep Learning( Adam,https://medium.com/@ageitgey/machine-learning-is-fun-part-4-modern-face-recognition-with-deep-learning-c3cffc...
首先,创建一个face_detector.py文件同时复制下面的代码: # import librariesimport cv2import face_recognition# Get a reference to webcam video_capture = cv2.VideoCapture("/dev/video1")# Initialize variablesface_locations = []while True: # Grab a single frame of video ret, frame = video_capture....
pip install face_recognition 人脸识别通用流程一般有人脸检测,人脸对齐和人脸识别三步: 1 人脸检测/人脸定位 face detection and location:人脸检测就是在图片中找到人脸的具体位置,并输出包含人脸位置的边界矩形框。某些检测算法可以同时输出人脸相应的关键点。
face_locations = face_recognition.face_locations(unknown_image, number_of_times_to_upsample=0, model="cnn")#执行HOG模型检测并返回人脸位置(相对慢),使用神经网络检测number_of_times_to_upsample=0, model="cnn",初加载会比较慢,加载后再检测就很快了。plt.figure(figsize=(10,10))#figsize里面的系数...
代码:https://github.com/ageitgey/face_recognition/blob/master/examples/facerec_from_webcam_faster.py 安装要求 Python 3+ 或 Python 2.7 macOS 或Linux(Windows未测试) 还可在树莓派 2+上运行(按照具体指令来安装运行:https://gist.github.com/ageitgey/1ac8dbe8572f3f533df6269dab35df65) ...
import face_recognition import cv2 import numpy as np # This is a super simple (but slow) example of running face recognition on live video from your webcam. # There's a second example that's a little more complicated but runs faster. ...
# take pictures from webcam cap = cv2.VideoCapture(0)while True: success, img = cap.read() imgS = cv2.resize(img, (0,0), None, 0.25,0.25) imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB) faces_in_frame = face_recognition.face_locations(imgS) encoded_faces = face_recognition.face...