dlib库人脸

import cv2 as cvimport dlib# 打开filename = 'C:/Users/to_bo/Desktop/1.jpg'img = cv.imread(filename)# 返回检测器detector = dlib.get_frontal_face_detector()# 返回人脸框faces = detector(img, 1)# 假设有多个人脸框被返回，依次遍历for i, d in enumerate(faces): # 画框框 cv.rectangle( img, tuple([d.left(), d.top()]), tuple([d.right(), d.bottom()]), (0, 255, 255), 2 )# 输出cv.imshow('img', img)# 结束cv.waitKey(0)cv.destroyAllWindows()

import cv2 as cvimport dlib# 打开path = 'C:/Users/to_bo/Desktop/1.jpg'img = cv.imread(path)# 返回检测器detector = dlib.get_frontal_face_detector()# 返回人脸框faces = detector(img, 1)# 返回定位关键点predictor = dlib.shape_predictor( 'C:/Users/to_bo/Desktop/1.dat')# 假设有多个人脸框被返回，依次遍历for face in faces: # 框框里面定位人脸关键点 shape = predictor(img, face) # 遍历所有（68）点，打印出其坐标，并标记 for p in shape.parts(): cv.circle(img, (p.x, p.y), 1, (255, 0, 0), -1) # 输出 cv.imshow("image", img)# 结束cv.waitKey(0)cv.destroyAllWindows()

predictor = dlib.shape_predictor()关键点预测器用法

detector = dlib.get_frontal_face_detector()获取人脸框的用法

import cv2 as cvimport dlibdetector = dlib.get_frontal_face_detector()predictor = dlib.shape_predictor( 'C:/Users/to_bo/Desktop/1.dat')cap = cv.VideoCapture(0, cv.CAP_DSHOW)if not cap.isOpened(): print("Can not open camera") exit(0)while True: ret, frame = cap.read() if not ret: print("Can not receive frame") break faces = detector(frame, 1) for face in faces: shape = predictor(frame, face) for p in shape.parts(): cv.circle(frame, (p.x, p.y), 2, (0, 255, 0), -1) cv.imshow('img', frame) if cv.waitKey(1) & 0xFF == 27: breakcap.release()cv.destroyAllWindows()

detector.run()的识别（不太精确）

import cv2 as cvimport dlibimg = cv.imread('C:/Users/to_bo/Desktop/2.jpg')gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY)detector = dlib.get_frontal_face_detector()# predictor = dlib.shape_predictor('C:/Users/to_bo/Desktop/1.dat')faces = detector(gray, 1)# for face in faces:# points = predictor(gray, face)# for p in points.parts():# cv.circle(img, (p.x, p.y), 1, (0, 255, 0), -1)# cv.namedWindow('img', cv.WINDOW_NORMAL)# cv.imshow('img', img)# cv.waitKey(0)# cv.destroyWindow('img')dets, scores, idx = detector.run(img, 1, -1)for i, d in enumerate(dets): print("Detection {}, score: {}, face_type:{}".format( d, scores[i], idx[i])) if scores[i] > 0.8: cv.rectangle(img, (d.left(), d.top()), (d.right(), d.bottom()), (0, 255, 255), 2) cv.putText( img, str(scores[i]), (d.left(), d.bottom()), cv.FONT_HERSHEY_TRIPLEX, 1, (0, 255, 0), 2, cv.LINE_AA )cv.namedWindow('img', cv.WINDOW_NORMAL)cv.imshow('img', img)cv.waitKey(0)cv.destroyAllWindows()