opencv計算機視覺學習筆記四

轉載來自https://blog.csdn.net/retacn_yue/article/details/53608388
第五章 人臉檢測和識別

1 haar級聯的概念

2 獲取haar級聯數據

在opencv源碼中data/haarcascades目錄下存放了用於人臉檢測的xml文件.用於檢測靜止圖像,視頻和攝像頭中的人臉

用於人臉眼睛 鼻子和嘴的跟蹤

haarcascade_profileface

haarcascade_smile

haarcascade_russian_plate_number

haarcascade_upperbody

haarcascade_righteye_2splits

3 使用opencv進行人臉檢測

3.1 靜態圖像中的人臉檢測

示例代碼如下:

import cv2

filename=’../zz.jpg’

def detect(filename):
#用於人臉檢測xml
face_cascade=cv2.CascadeClassifier(‘../cascades/haarcascade_frontalface_default.xml’)

#讀入圖像
img=cv2.imread(filename)
#更換顏色空間
gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray,
                                    1.3,#圖像的壓縮率
                                    5)#人臉矩形保留鄰近數目的最小值
#在原始圖像上繪製藍色矩形
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)

執行結果:老同桌的臉居然識別不出來

3.2 視頻中的人臉檢測

示例代碼如下:

!/usr/bin/env python

-- coding: utf-8 --

@Time : 2016/12/3 13:36

@Author : Retacn

@Site : 視頻中的人臉檢測

@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():
# 加載haar級聯文件
face_cascade = cv2.CascadeClassifier(‘../cascades/haarcascade_frontalface_default.xml’)
eye_cascade = cv2.CascadeClassifier(‘../cascades/haarcascade_eye.xml’)
camera = cv2.VideoCapture(0)

# 捕獲視頻幀
while (True):
    ret, frame = camera.read()
    # 轉換顏色空間
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = face_cascade.detectMultiScale(gray, 1.3, 5)

    for (x, y, w, h) in faces:
        #繪製檢測到的人臉矩形
        img = cv2.rectangle(frame, (x, y), (x + w, y + h), (255, 0, 0), 2)
       # roi_gray = gray[y:y + h, x:x + w]

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

        #繪製檢測到的眼睛矩形
        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)
    #顯示圖像
    cv2.imshow('Camers', frame)
    #按q鍵退出
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
camera.release()
cv2.destroyAllWindows()

if name == ‘main‘:
detect()

3.3 人臉視別

人臉數據庫:

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 生成人臉數據

生成圖像角本

圖像像是灰度格式的.pgm文件,形狀爲正方式,大小要一樣

示例代碼如下:

!/usr/bin/env python

-- coding: utf-8 --

@Time : 2016/12/3 15:14

@Author : Retacn

@Site : 生成人臉識別數據

@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 人臉視別

C 準備訓練數據

生成csv文件的方法,示例代碼如下:

!/usr/bin/env python

-- coding: utf-8 --

@Time : 2016/12/3 15:14

@Author : Retacn

@Site : 生成人臉識別數據

@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 加載數據並識別人臉

示例代碼如下：

加載識別數據

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 基於eignfaces的人臉識別

示例代碼如下：

!/usr/bin/env python

-- coding: utf-8 --

@Time : 2016/12/3 22:07

@Author : Retacn

@Site : TODO 需要重新編譯opencv擴展包，人臉檢測與識別

@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

生成人臉識別數據

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

# 讀取攝像頭視頻數據
camera = cv2.VideoCapture(0)
count = 0
while (True):
    ret, frame = camera.read()
    # 更換顏色空間
    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()

加載識別數據

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]

基於eigenfaces的人臉識別

def face_rec():
names = [‘Yue’, ‘Retacn’, ‘Three’]
# 需要輸入樣本數據的存放路徑
if len(sys.argv) < 2:
print(‘USAGE: facerec_defo.py [/path/to/store/images/at]’)
sys.exit()
# 讀入圖像數組,第二個參數爲樣本圖像的存放位置
[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’)

# 如果有三個參數,則將第三個參數設爲輸出目錄
if len(sys.argv) == 3:
    out_dir = sys.argv[2]

# 創建人臉識別模型
# model = cv2.face.createEigenFaceRecognizer()
# 基於Fisherfaces的人臉識別
# model = cv2.face.createFisherFaceRecognizer()
# 基於lbph的人臉識別
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)

            # 置信度評分
            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 基於fisherfaces的人臉識別

基於Fisherfaces的人臉識別

#model=cv2.face.createFisherFaceRecognizer()

G 基於LBPH的人臉識別

基於lbph的人臉識別

model=cv2.face.createLBPHFaceRecognizer()

H 通過置信度評分來丟棄結果

Predict（）