• opencv计算机视觉学习笔记四

    第五章 人脸检测和识别

    1 haar级联的概念

    2 获取haar级联数据

    在opencv源码中data/haarcascades目录下存放了用于人脸检测的xml文件.用于检测静止图像,视频和摄像头中的人脸

    用于人脸眼睛 鼻子和嘴的跟踪

    haarcascade_profileface

    haarcascade_smile

    haarcascade_russian_plate_number

    haarcascade_upperbody

    haarcascade_righteye_2splits

    3 使用opencv进行人脸检测

    3.1 静态图像中的人脸检测

    示例代码如下:

    import cv2

filename='../zz.jpg'

def detect(filename):
    #用于人脸检测xml
    face_cascade=cv2.CascadeClassifier('../cascades/haarcascade_frontalface_default.xml')

    #读入图像
    img=cv2.imread(filename)
    #更换颜色空间
    gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    faces=face_cascade.detectMultiScale(gray,
                                        1.3,#图像的压缩率
                                        5)#人脸矩形保留邻近数目的最小值
    #在原始图像上绘制蓝色矩形
    for (x,y,w,h) in faces:
        img=cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
    cv2.namedWindow('Vikings Detected!!')
    cv2.imshow("Vikings Detected!!",img)
    cv2.imwrite('../vikings.jpg',img)
    cv2.waitKey(0)

if __name__=='__main__':
    detect(filename)

    执行结果:老同桌的脸居然识别不出来

    3.2 视频中的人脸检测

    示例代码如下:

    #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time    : 2016/12/3 13:36
# @Author  : Retacn
# @Site    : 视频中的人脸检测
# @File    : fact_detection_video.py
# @Software: PyCharm
__author__ = "retacn"
__copyright__ = "property of mankind."
__license__ = "CN"
__version__ = "0.0.1"
__maintainer__ = "retacn"
__email__ = "zhenhuayue@sina.com"
__status__ = "Development"

import cv2

def detect():
    # 加载haar级联文件
    face_cascade = cv2.CascadeClassifier('../cascades/haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('../cascades/haarcascade_eye.xml')
    camera = cv2.VideoCapture(0)

    # 捕获视频帧
    while (True):
        ret, frame = camera.read()
        # 转换颜色空间
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5)

        for (x, y, w, h) in faces:
            #绘制检测到的人脸矩形
            img = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
           # roi_gray = gray[y:y + h, x:x + w]

            #检测眼睛
            # eyes = eye_cascade.detectMultiScale(roi_gray, 1.03, 5, 0, (40, 40))
            eyes = eye_cascade.detectMultiScale(img, 1.03, 5, 0, (40, 40))

            #绘制检测到的眼睛矩形
            for (ex, ey, ew, eh) in eyes:
                cv2.rectangle(img, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
            #print(x,y,w,h,ex,ey,ew,eh)
        #显示图像
        cv2.imshow('Camers', frame)
        #按q键退出
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    camera.release()
    cv2.destroyAllWindows()
    
if __name__ == '__main__':
    detect()

    3.3 人脸视别

    人脸数据库:

    The yale facedatabase

    http://version.ucsd.edu/content/yale-face-database

    The AT&T

    http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

    The extendedyale or yale b

    http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

    A 生成人脸数据

    生成图像角本

    图像像是灰度格式的.pgm文件,形状为正方式,大小要一样

    示例代码如下:

    #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time    : 2016/12/3 15:14
# @Author  : Retacn
# @Site    : 生成人脸识别数据
# @File    : createData.py
# @Software: PyCharm
__author__ = "retacn"
__copyright__ = "property of mankind."
__license__ = "CN"
__version__ = "0.0.1"
__maintainer__ = "retacn"
__email__ = "zhenhuayue@sina.com"
__status__ = "Development"

import cv2

def generate():
    face_cascade = cv2.CascadeClassifier('../cascades/haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('../cascades/haarcascade_eye.xml')

    camera = cv2.VideoCapture(0)
    count = 0
    while (True):
        ret, frame = camera.read()
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5)

        for (x, y, w, h) in faces:
            img = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
            f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
            cv2.imwrite('../data/at/retacn/%s.pgm' % str(count), f)
            count += 1
        cv2.imshow("Camera", frame)
        if cv2.waitKey(33) & 0xFF == ord("q"):
            break
    camera.release()
    cv2.destroyAllWindows()

if __name__ == '__main__':
    generate()

    B 人脸视别

    C 准备训练数据

    生成csv文件的方法,示例代码如下:

    #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time    : 2016/12/3 15:14
# @Author  : Retacn
# @Site    : 生成人脸识别数据
# @File    : createData.py
# @Software: PyCharm
__author__ = "retacn"
__copyright__ = "property of mankind."
__license__ = "CN"
__version__ = "0.0.1"
__maintainer__ = "retacn"
__email__ = "zhenhuayue@sina.com"
__status__ = "Development"

import cv2

def generate():
    face_cascade = cv2.CascadeClassifier('../cascades/haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('../cascades/haarcascade_eye.xml')

    camera = cv2.VideoCapture(0)
    count = 0
    while (True):
        ret, frame = camera.read()
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5)

        for (x, y, w, h) in faces:
            img = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
            f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
            cv2.imwrite('../data/at/retacn/%s.pgm' % str(count), f)
            count += 1
        cv2.imshow("Camera", frame)
        if cv2.waitKey(33) & 0xFF == ord("q"):
            break
    camera.release()
    cv2.destroyAllWindows()

if __name__ == '__main__':
    generate()

    D 加载数据并识别人脸

    示例代码如下：

    
# 加载识别数据
def read_image(path, sz=None):
    c = 0
    x, y = [], []
    for dirname, dirnames, filenames in os.walk(path):
        for subdirname in dirnames:
            subject_path = os.path.join(dirname, subdirname)
            for filename in os.listdir(subject_path):
                try:
                    if (filename == '.directory'):
                        continue
                    filepath = os.path.join(subject_path, filename)
                    img = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
                    if (sz is not None):
                        im = cv2.resize(im, (200, 200))
                    x.append(np.asanyarray(im, dtype=np.uint8))
                    y.append(c)
                except IOError as ioe:
                    print(ioe)
                except:
                    print('Unexpected error:', sys.exc_info()[0])
                    raise
            c += 1
    return [x, y]

    E 基于eignfaces的人脸识别

    示例代码如下：

    #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time    : 2016/12/3 22:07
# @Author  : Retacn
# @Site    : TODO 需要重新编译opencv扩展包，人脸检测与识别
# @File    : face_detection.py
# @Software: PyCharm
__author__ = "retacn"
__copyright__ = "property of mankind."
__license__ = "CN"
__version__ = "0.0.1"
__maintainer__ = "retacn"
__email__ = "zhenhuayue@sina.com"
__status__ = "Development"

import cv2
import numpy as np
import sys
import os.path


# 生成人脸识别数据
def generate():
    face_cascade = cv2.CascadeClassifier('../data/cascades/haarcascade_frontalface_default.xml')
    eye_cascade = cv2.CascadeClassifier('../data/cascades/haarcascade_eye.xml')

    # 读取摄像头视频数据
    camera = cv2.VideoCapture(0)
    count = 0
    while (True):
        ret, frame = camera.read()
        # 更换颜色空间
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, 1.3, 5)

        for (x, y, w, h) in faces:
            img = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
            f = cv2.resize(gray[y:y + h, x:x + w], (200, 200))
            cv2.imwrite('../data/at/retacn/%s.pgm' % str(count), f)
            count += 1
        cv2.imshow("Camera", frame)
        if cv2.waitKey(1000 / 12) & 0xFF == ord("q"):
            break
    camera.release()
    cv2.destroyAllWindows()


# 加载识别数据
def read_image(path, sz=(200, 200)):
    c = 0
    x, y = [], []
    for dirname, dirnames, filenames in os.walk(path):
        for subdirname in dirnames:
            subject_path = os.path.join(dirname, subdirname)
            for filename in os.listdir(subject_path):
                try:
                    if (filename == '.directory'):
                        continue
                    filepath = os.path.join(subject_path, filename)
                    img = cv2.imread(filepath, cv2.IMREAD_GRAYSCALE)
                    if (sz is not None):
                        img = cv2.resize(img, (200, 200))
                    x.append(np.asarray(img, dtype=np.uint8))
                    y.append(c)
                except IOError as ioe:
                    print(ioe)
                except:
                    print('Unexpected error:', sys.exc_info()[0])
                    raise
            c += 1
    return [x, y]


# 基于eigenfaces的人脸识别
def face_rec():
    names = ['Yue', 'Retacn', 'Three']
    # 需要输入样本数据的存放路径
    if len(sys.argv) < 2:
        print('USAGE: facerec_defo.py </path/to/images> [/path/to/store/images/at]')
        sys.exit()
    # 读入图像数组,第二个参数为样本图像的存放位置
    [x, y] = read_image(sys.argv[1])
    y = np.asarray(y, dtype=np.int32)
    # [x, y] = read_image('D:/workspace_pycharm/opencv3_python/data/at')


    # 如果有三个参数,则将第三个参数设为输出目录
    if len(sys.argv) == 3:
        out_dir = sys.argv[2]

    # 创建人脸识别模型
    # model = cv2.face.createEigenFaceRecognizer()
    # 基于Fisherfaces的人脸识别
    # model = cv2.face.createFisherFaceRecognizer()
    # 基于lbph的人脸识别
    model = cv2.face.createLBPHFaceRecognizer()
    model.train(np.asarray(x), np.asarray(y))
    camera = cv2.VideoCapture(0)
    face_cascade = cv2.CascadeClassifier('../data/cascades/haarcascade_frontalface_default.xml')

    while (True):
        read, img = camera.read()
        faces = face_cascade.detectMultiScale(img, 1.3, 5)
        for (x, y, w, h) in faces:
            img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
            gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            roi = gray[x:x + w, y:y + h]
            try:
                roi = cv2.resize(roi, (200, 200), interpolation=cv2.INTER_LINEAR)
                # roi = cv2.resize(gray, (200, 200), interpolation=cv2.INTER_LINEAR)

                # 置信度评分
                params = model.predict(roi)
                print(params)
                print('Lable:%s,Confidence:%02f' % (params[0], params[1]))
                cv2.putText(img, names[params[0]], (x, y - 20), cv2.FONT_HERSHEY_SIMPLEX, 1, 255, 2)
            except:
                continue
        cv2.imshow("camera", img)
        if cv2.waitKey(33) & 0xFF == ord('q'):
            break
    cv2.destroyAllWindows()


if __name__ == '__main__':
    # generate()
    # [X, y] = read_image('D:/workspace_pycharm/opencv3_python/data/at')
    face_rec()
    # generate()

    F 基于fisherfaces的人脸识别

    #基于Fisherfaces的人脸识别
       #model=cv2.face.createFisherFaceRecognizer()

    G 基于LBPH的人脸识别

    #基于lbph的人脸识别
# model=cv2.face.createLBPHFaceRecognizer()

    H 通过置信度评分来丢弃结果

    Predict（）
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  • 原文地址：https://www.cnblogs.com/retacn-yue/p/6194154.html
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