opencv计算机视觉学习笔记四
转载来自https://blog.csdn.net/retacn_yue/article/details/53608388
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 = “[email protected]”
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 = “[email protected]”
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 = “[email protected]”
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 = “[email protected]”
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/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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