一些基础知识

import cv2

def Basic_Knowledge():
    """
    imread 读取一张图片文件,第二个参数默认为1(代表为彩色图片)
    imshow 用于展示一张图片,第一个参数为图片名,第二个参数为已经读取过的图片文件
    resize 可以重新规划图片的大小,第一个参数为已经读取过的图片文件,第二个参数为图片的长和高
    img.shape 代表图片的参数
    cv2.waitKey 代表等待用户的输入
    cv2.destroyAllWindows 代表关闭所有窗口
    :return:null
    """
    img = cv2.imread('../static/b9.png', 1)

    # cv2.imshow('smile_face', img)

    # new_img = cv2.resize(img, (640, 640))
    new_img = cv2.resize(img, (int(img.shape[1]*5), int(img.shape[0]*5)))

    cv2.imshow('smile_face', new_img)

    cv2.waitKey(2000)  # wait 2000ms

    cv2.destroyAllWindows()


Basic_Knowledge()

识别图片中的人脸

import cv2

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

img = cv2.imread('../static/liuyifei.png')

gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

faces = face_cascade.detectMultiScale(gray_img, scaleFactor=1.05,  minNeighbors=5)

for x, y, w, h in faces:
    """
        在 img上创建矩形, 左上顶点坐标为 (x, y), 右下顶点坐标为 (x+w, y+h)
    矩形颜色为 (0, 255, 0), 矩形线条粗度为 3px
    """
    img = cv2.rectangle(img, (x, y), (x+w, y+h), (0, 255, 0), 3)

resized = cv2.resize(img, (int(img.shape[1]/2), int(img.shape[0]/2)))

cv2.imshow("liuyifei", resized)

cv2.waitKey(0)

cv2.destroyAllWindows()

识别自己设备中的人脸

import cv2

video = cv2.VideoCapture(0)  # 数字 0表示使用内置摄像头
face_cascade = cv2.CascadeClassifier("../static/haarcascade_frontalface_default.xml")

index = 1
while True:
    index += 1
    check, frame = video.read()  # frame 代表每桢的图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.05, minNeighbors=5)

    if index % 3 == 0:
        print('发现了%s个人脸' % len(faces))

    for x, y, w, h in faces:
        img = cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
    cv2.imshow('Capturing', frame)

    if cv2.waitKey(1) == 113:  # q键
        break

print(index)
video.release()
cv2.destroyAllWindows()

识别视频中的人脸

import cv2

video = cv2.VideoCapture('../static/九龄｜冬日jk女友｜当她眼角带笑.mp4')
face_cascade = cv2.CascadeClassifier("../static/haarcascade_frontalface_default.xml")

index = 1
while True:
    index += 1
    check, frame = video.read()  # frame 代表每帧的图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.05, minNeighbors=5, minSize=(50, 50))

    if index % 3 == 0:
        print('发现了%s个人脸' % len(faces))

    for x, y, w, h in faces:
        img = cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 5)

    new_frame = cv2.resize(frame, (int(frame.shape[1]/3), int(frame.shape[0]/3)))
    cv2.imshow('Capturing', new_frame)

    if cv2.waitKey(1) == 113:  # q键
        break

print(index)

video.release()
cv2.destroyAllWindows()