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__ = "[e-mail]"
__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__ = "[e-mail]"
__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__ = "[e-mail]"
__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__ = "[e-mail]"
__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（）