OpenCV与图像处理（七）

Must

发布于 2020-07-28 11:33:04

3120

发布于 2020-07-28 11:33:04

以下代码均在python3.6，opencv4.2.0环境下试了跑一遍，可直接运行。

1、基于OpenCV中自带的HOG的行人检测分类器，实现行人检测

# *_*coding:utf-8 *_*
import cv2
import numpy as np

img = cv2.imread('person.jpg')
hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector()) #使用opencv默认的模型
rects, _ = hog.detectMultiScale(img, winStride=(4,4), padding=(8,8), scale=1.05)
for (x,y,w,h) in rects:
    cv2.rectangle(img, (x,y), (x+w,y+h), (0,0,255), 2)
cv2.imshow('img', img)
cv2.waitKey(0)
cv2.destroyAllWindows()

运行结果：

2、基于OpenCV中自带的Haar的人脸检测分类器，实现人脸人眼检测

1）人脸检测

# -*- coding: utf-8 -*-
import cv2
import numpy as np

face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")

img_path = 'face.jpg'
img = cv2.imread(img_path)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faceRects = face_cascade.detectMultiScale(gray,1.1,5)
for faceRect in faceRects:
    x, y, w, h = faceRect
    cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2, 8, 0) 
cv2.namedWindow("image", cv2.WINDOW_AUTOSIZE)
cv2.imshow("image", img)

cv2.waitKey(0)
cv2.destroyAllWindows()

运行结果：

2）人脸人眼检测

# -*- coding: utf-8 -*-
import cv2
import numpy as np

face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
eye_cascade = cv2.CascadeClassifier("haarcascade_eye_tree_eyeglasses.xml")

img_path = 'face.jpg'
img = cv2.imread(img_path)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faceRects = face_cascade.detectMultiScale(gray,1.1,5)
l=len(faceRects)
print(l)
for faceRect in faceRects:
    x, y, w, h = faceRect
    cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2, 8, 0)

    roi_gray = gray[y:y+h,x:x+w]
    roi_color = img[y:y+h,x:x+w]
    
    eyes = eye_cascade.detectMultiScale(roi_gray,1.1,1,cv2.CASCADE_SCALE_IMAGE,(2,2))
    for (ex,ey,ew,eh) in eyes:
        cv2.rectangle(roi_color, (ex,ey), (ex+ew,ey+eh), (0,255,0), 2)

cv2.namedWindow("image", cv2.WINDOW_AUTOSIZE)
cv2.imshow("image", img)

cv2.waitKey(0)
cv2.destroyAllWindows()

运行结果：

3、基于OpenCV中自带的LBP的人脸检测分类器，实现人脸检测

# -*- coding: utf-8 -*-
import cv2
import numpy as np

face_cascade = cv2.CascadeClassifier("lbpcascade_frontalface.xml")

img_path = 'face.jpg'
img = cv2.imread(img_path)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

faceRects = face_cascade.detectMultiScale(gray,1.1,5)
for faceRect in faceRects:
    x, y, w, h = faceRect
    cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2, 8, 0)

cv2.namedWindow("image", cv2.WINDOW_AUTOSIZE)
cv2.imshow("image", img)

cv2.waitKey(0)
cv2.destroyAllWindows()

运行结果：