python利用dlib获取人脸的68个landmark
人气:0(1) 单人脸情况
import cv2 import dlib path = "1.jpg" img = cv2.imread(path) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #人脸检测画框 detector = dlib.get_frontal_face_detector() # 获取人脸关键点检测器 predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") #获取人脸框位置信息 dets = detector(gray, 1)#1表示采样(upsample)次数 0识别的人脸少点,1识别的多点,2识别的更多,小脸也可以识别 for face in dets: shape = predictor(img, face) # 寻找人脸的68个标定点 # 遍历所有点,打印出其坐标,并圈出来 for pt in shape.parts(): pt_pos = (pt.x, pt.y) cv2.circle(img, pt_pos, 2, (0, 0, 255), 1)#img, center, radius, color, thickness cv2.imshow("image", img) cv2.waitKey(0) cv2.destroyAllWindows()
(2) 多人脸情况
import cv2 import dlib path1 = "zxc.jpg" img = cv2.imread(path1) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #人脸检测画框 detector = dlib.get_frontal_face_detector() # 获取人脸关键点检测器 predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") #获取人脸框位置信息 dets = detector(gray, 1)#1表示采样(upsample)次数 0识别的人脸少点,1识别的多点,2识别的更多,小脸也可以识别 for i in range(len(dets)): shape = predictor(img, dets[i]) # 寻找人脸的68个标定点 # 遍历所有点,打印出其坐标,并圈出来 for pt in shape.parts(): pt_pos = (pt.x, pt.y) cv2.circle(img, pt_pos, 2, (0, 0, 255), 1)#img, center, radius, color, thickness cv2.imshow("image", img) cv2.waitKey(0)#等待键盘输入 cv2.destroyAllWindows()
(3) 获取电脑摄像头实时识别标定
import cv2 import dlib import numpy as np cap = cv2.VideoCapture(0)#打开笔记本的内置摄像头,若参数是视频文件路径则打开视频 cap.isOpened() def key_points(img): points_keys = [] PREDICTOR_PATH = "shape_predictor_68_face_landmarks.dat" detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor(PREDICTOR_PATH) rects = detector(img,1) for i in range(len(rects)): landmarks = np.matrix([[p.x,p.y] for p in predictor(img,rects[i]).parts()]) for point in landmarks: pos = (point[0,0],point[0,1]) points_keys.append(pos) cv2.circle(img,pos,2,(255,0,0),-1) return img while(True): ret, frame = cap.read()#按帧读取视频,ret,frame是cap.read()方法的两个返回值。其中ret是布尔值,如果读取帧是正确的则返回True,如果文件读取到结尾,它的返回值就为False。frame就是每一帧的图像,是个三维矩阵。 # gray = cv2.cvtColor(frame) face_key = key_points(frame) cv2.imshow('frame',face_key) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release()#释放摄像头 cv2.destroyAllWindows()#关闭所有图像窗口
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