OpenCV中的视频人脸检测
代码实现:
import cv2
import os
import numpy as np
import matplotlib.pyplot as plt
import cv2 as cv
from PIL import Image
import pytesseract as test
#视频人脸检测
def video_detect(img):
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 加载分类器
faces_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt_tree.xml")
eyes_cascade = cv2.CascadeClassifier("haarcascade_eye.xml")
# detectMultiScale()第三个参数数值越大,检测错误率越低,但需要图像足够清晰,若不够清晰可能检测失败
faces = faces_cascade.detectMultiScale(gray, 1.02, 2)
eyes = eyes_cascade.detectMultiScale(gray, 1.02, 25)
for x, y, w, h in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
for x, y, w, h in eyes:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.namedWindow('detect', cv2.WINDOW_AUTOSIZE)
cv2.imshow('detect', img)
cv2.waitKey(10)
video = cv2.VideoCapture('output.avi')
while True:
ret,frame = video.read()
frame = cv2.flip(frame,1)
video_detect(frame)
这段代码展示了如何利用OpenCV库在Python中进行视频处理,实现人脸和眼睛的检测。通过加载预训练的Haar级联分类器,对灰度图像进行多尺度检测,然后在原始图像上绘制矩形框来标识检测到的区域。代码在视频每一帧上运行,实时显示检测结果。
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