上代码:

#coding=utf-8

import cv2
import dlib

path = "imagePath/9.jpg"
img = cv2.imread(path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

#人脸分类器
detector = dlib.get_frontal_face_detector()
# 获取人脸检测器
predictor = dlib.shape_predictor(
  "shape_predictor_68_face_landmarks.dat"
)
color = (0, 255, 0) # 定义绘制颜色

dets = detector(gray, 1)
for face in dets:
  shape = predictor(img, face) # 寻找人脸的68个标定点
  chang=[]
  kuan= []
  # 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)
    chang.append(pt.x)
    kuan.append(pt.y)
    #cv2.circle(img, pt_pos, 1, (0, 255, 0), 1)
  x1 = max(chang)
  x2 = min(chang)
  y1 = max(kuan)
  y2 = min(kuan)
  cv2.rectangle(img, (x2, y2), (x1, y1), color, 1)
  cropped = img[y2 + 1:y1, x2 + 1:x1] # 裁剪坐标为[y0:y1, x0:x1]
  cv2.imshow("image", cropped)
  k = cv2.waitKey(0)
  if k == ord("s"):
    cv2.imwrite("imagePath/9-7.png", cropped)
cv2.destroyAllWindows()

识别效果:

Python用dilb提取照片上人脸的示例

以上就是Python用dilb提取照片上人脸的示例的详细内容,更多关于python 提取人脸的资料请关注其它相关文章!

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